constructed wetlands for urban stormwater nutrient

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Constructed wetlands for urban stormwater nutrient attenuation: Diurnal to decadal dynamics Tanveer Mehedi Adyel B.Sc. (Hons.) in Environmental Sciences M.S. in Environmental Sciences This thesis is presented in fulfilment of the requirements for the degree of Doctor of Philosophy of The University of Western Australia School of Civil, Environmental and Mining Engineering & UWA School of Agriculture and Environment May 2017

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Page 1: Constructed wetlands for urban stormwater nutrient

Constructed wetlands for urban stormwater nutrient

attenuation: Diurnal to decadal dynamics

Tanveer Mehedi Adyel

B.Sc. (Hons.) in Environmental Sciences

M.S. in Environmental Sciences

This thesis is presented in fulfilment of the requirements for the degree of

Doctor of Philosophy of The University of Western Australia

School of Civil, Environmental and Mining Engineering

&

UWA School of Agriculture and Environment

May 2017

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Abstract

Stormwater runoff supplies organic and inorganic nutrients that have been

mobilised and redistributed from point and non-point sources within urban

catchments. Stormwater nutrient loads create challenges for the downstream receiving

waters, leading to water quality impairment, eutrophication and dissolved oxygen

(DO) depletion, and a reduction in recreational amenity. Therefore, strategies for

stormwater nutrient attenuation are necessary to maintain the ecological health and

amenities of such downstream waters. Constructed wetlands (CWs) as Water

Sensitive Urban Design options are widely used for stormwater nutrient attenuation

owing to their economic and environmental benefits. The surface flow (SF) and

subsurface flow (SSF) CWs are two of the most common types of CW. However,

optimisation of CW function remains challenging, particularly under Mediterranean

climates. CWs under Mediterranean climates receive nutrient-rich episodic

stormwater pulses during the wet winters. The same CWs experience prolonged low

to near-zero flow conditions and macrophyte senescence during the dry summers.

Furthermore, although CWs act as lentic systems during summer low flows, episodic

storm events during the winter convert the CWs into lotic systems, and frequent

lentic-lotic transitions make optimization of CW function difficult and prediction of

their nutrient reduction challenging.

This research aimed to assess stormwater nutrient attenuation in two CWs on

the Swan Coastal Plain, Western Australia, under different hydrological,

biogeochemical and climatic conditions. The first CW, a meandering SF CW, was

constructed in 2004 with a restoration effort after six years of operation. The second

CW, a hybrid system consisting of multiple alternating SF and laterite-based SSF

compartments, started operation in 2009. Baumea articulata and Schoenoplectus

validus were the dominant macrophytes in both CWs. The research adopted a holistic

approach to investigate nutrient attenuation at diurnal, event, seasonal, annual and

decadal scale through a synthesis of meteorological, water quality and quantity,

sediment quality and macrophyte data.

Nutrient species, except filtered total oxidised nitrogen (NOx), attenuated

immediately after the SF CW restoration. However, NOx attenuation started to

increase significantly three years after the restoration. Over decadal scales, attenuation

of inorganic and dissolved nitrogen, such as NOx and ammonia (NH3) was higher than

the attenuation of total nitrogen (TN) and dissolved organic nitrogen (DON). Three

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years after the restoration, the SF CW was consistently hypoxic, and started to release

phosphorus. The hybrid CW showed higher nutrient attenuation than the SF CW.

Although the SF and SSF compartments of the hybrid CW periodically released DON

and NOx, respectively, these nutrients attenuated in the subsequent alternating

compartments. A potential attenuation pattern between NH3 (highest under oxic

conditions) and NOx (highest under anoxic conditions) was observed in both CWs.

The sediments were a larger nutrient sink than macrophytes in both CWs. In addition,

during the summer low flows, senescent and floating macrophytes shaded the water

column and caused persistent low DO concentrations in the CW, and subsequently

suppressed nutrient attenuation. DO levels increased in the CWs after the removal of

the floating and senescent macrophytes.

A distinct diurnal DO signature was observed in the SF CW, with anoxia at

night, while groundwater was hypoxic throughout the year. The research developed a

low-cost proxy “metabolism” indicator using the diurnal change in DO. This proxy

“metabolism” was correlated with available solar radiation, water temperature, CW

volume and antecedent dry condition, and most importantly with the nutrient

attenuation capacity of the SF CW. This research specifically targeted systems under a

Mediterranean climate that experience large variability in hydrology, compared to

other regions of the world. This proxy indicator could be used to indicate CW function

when resources constrain the intensity of routine sampling. CWs also provide other

potential services and benefits for ensuring urban liveability and resilience.

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Statement of originality

The research presented in this thesis is an original contribution to the field of

constructed wetland for urban stormwater management. All materials presented here

are original except where due acknowledgment is given, and has not been accepted for

any other degree or diploma. Besides, it has been substantially completed during my

enrolment at The University of Western Australia.

The body of this thesis (Chapters 3 to 5) is presented as a series of self-

contained papers intended for journal publication, and some repetition of the literature

review, study site details and methodology has therefore been necessary. I have been

solely responsible for all data analysis and figures contained in this thesis, and have

led all of the writing of the text with feedback from my supervisors.

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Acknowledgements

My sincere thanks to my supervisors, Carolyn Oldham and Matthew Hipsey,

for their guidance, truthful criticism and sensible advice throughout my doctoral

journey. My thanks to Ana Deletic (Monash University) for her deep interest on the

progress of this research. A very big thanks to Peter Adkins and Christie Atkinson

(Department of Parks and Wildlife, WA) for taking care of the field sites over decade

and allowing me to work in these sites and their continuous assisting with historical

data, information and comments on writing. Thanks to Ryan Vogwill and Nicki

Mitchell for their instrumental support, and Anas Ghadouani and Jason Beringer for

making the official procedure smooth.

Thanks also to Ana Ruibal-Conti, Benya Wang, Carlos Ocampo, Gayan

Gunaratne and Jana Coletti for their assistance during the fieldwork, experiment and

data analysis. Special thanks to Hasnein Tareque for his support in GIS and

Mahmudur Rahman for giving me his inflatable boat during a field trip. My sincere

acknowledgement also to Taj Sarker for his help during fieldwork, particularly at

night in the cold, wind and rain. Thanks to Krish Seewraj (Department of Water, WA)

for his comments on early version of different chapters. Special thanks to Joanne

Edmondston for her constructive comments on academic writing during the doctoral

journey. My thanks to Chris Brouwer, Dave and James Hehre for their efforts and help

at field and lab.

Thanks go to my eldest brother Ferdous Sohel, for his deep interest in my

research. My sister-in-law, nephew, and niece have made my Ph.D. journey easy.

I acknowledge the help of the Department of Agriculture and Food, WA;

Department of Water, WA; the Department of Parks and Wildlife, WA; Water

Corporation, WA; City of Canning; the Bureau of Meteorology and the South East

Regional Centre for Urban Landcare (SERCUL) for their assistance with data and

information.

This study was funded by Cooperative Research Centre for Water Sensitive

Cities under Project C4.1 “Multi-functional urban water systems” and Project B2.4

“Hydrology and nutrient transport processes in groundwater/surface water systems”.

I was financially supported by UWA with Scholarship for International Research

Fees, University International Stipend, Safety Net Top-Up Scholarship and Ad Hoc

Scholarship.

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Dedication

To my beloved parents

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Potential publications arising from this thesis

Peer reviewed journal papers:

1. Tanveer M. Adyel, Matthew R. Hipsey and Carolyn E. Oldham (2017) Temporal

dynamics of stormwater nutrient attenuation by an urban constructed wetland

experiencing summer low flows and macrophytes senescence. Ecological

Engineering, 102, 641-661; [Chapter 3].

2. Tanveer M. Adyel, Carolyn E. Oldham and Matthew R. Hipsey (2016)

Stormwater nutrient attenuation in a constructed wetland with alternating surface

and subsurface flow pathways: event to annual dynamics. Water Research, 107,

66-82; [Chapter 4].

3. Tanveer M. Adyel, Matthew R. Hipsey and Carolyn E. Oldham (2017). Storm

event-scale nutrient attenuation in constructed wetlands experiencing a

Mediterranean climate: A comparison of surface flow and hybrid surface-

subsurface flow system. Science of the Total Environment, 598, 1001-1014;

[Chapter 5].

Technical reports:

4. Tanveer M. Adyel, Carlos Ocampo, Hasnein Tareque, Carolyn Oldham and

Matthew R. Hipsey (2015) Performance assessment of Wharf St Constructed

Wetland 2009-2014. Cooperative Research Centre for Water Sensitive Cities,

Australia, pp. 1-74.

5. Ana Ruibal-Conti, Carlos Ocampo, Tanveer M. Adyel, Matthew R. Hipsey and

Carolyn Oldham (2015) Performance assessment the of Anvil Way Compensation

Basin living stream: 2004-2013. Cooperative Research Centre for Water Sensitive

Cities, Australia, pp. 1-83.

Conference papers, abstracts and posters:

6. Tanveer M. Adyel, Matthew R. Hipsey, Carolyn E. Oldham (2017) Stormwater

nutrient dynamics during riparian zone saturation and lentic-lotic transition. 7th

International Multidisciplinary Conference on Hydrology and Ecology (HydroEco

2017), to be held in Birmingham, UK from 18-23 June 2017 (accepted).

7. Tanveer M. Adyel, Matthew R. Hipsey and Carolyn Oldham (2016) Comparative

assessment of nutrient attenuation in constructed wetlands during episodic

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stormwater pulses. 10th

INTECOL International Wetlands Conference, 19-24

September 2016, Changshu, China, pp. 71-72.

8. Tanveer M. Adyel, Matthew R. Hipsey and Carolyn Oldham (2016) Constructed

wetlands to support urban waterway protection from stormwater pollutants.

Stormwater Conference, 29 August-03 September 2016, Gold Coast, Qld,

Australia, pp. 1-8.

9. Tanveer M. Adyel, Matthew R. Hipsey and Carolyn Oldham (2015) Multi-

functional and multi-compartment constructed wetland for urban waterway

restoration. Singapore International Water Week, 10-16 July 2016, Singapore,

pp.1- 6.

10. Tanveer M. Adyel, Ana L. R. Conti, Carlos Ocampo, Jana Z. Coletti, Matthew

Hipsey and Carolyn Oldham (2015) Ecohydrology and stormwater nutrient

attenuation performance of constructed wetland in Western Australia. 34th

IAHR

World Congress, 28 June-03 July 2015, The Hague, the Netherlands. pp. 1-11.

11. Tanveer M. Adyel, Hasnein Tareque, Matthew R. Hipsey and Carolyn Oldham

(2015) A multi-functional and multi-compartment constructed wetland to support

urban waterway restoration. Poster presented at 2nd

Water Sensitive Cities

Conference, 8-9 September 2015, Brisbane, Australia.

12. Tanveer M. Adyel, Matthew Hipsey and Carolyn Oldham (2015) Stormwater

nutrient attenuation by constructed wetlands on the Swan Coastal Plain,

Hydropolis Conference, 21-22 April 2015, Perth, Australia.

13. Tanveer M. Adyel, Ana Ruibal, Carolyn Oldham and Matthew Hipsey (2014)

Stormwater nutrient attenuation by Anvil Way Compensation Basin. Poster

presented at 1st Water Sensitive Cities Conference, October 10 2014, Melbourne,

Australia.

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List of Acronyms and Variables

General:

ADD: Antecedent dry day

AGB: Above ground biomass

AHD: Australian Height Datum

ANAMMOX: Anaerobic ammonium oxidation

ANZECC: Australian and New Zealand Environment and

Conservation Council

AWCB: Anvil Way Compensation Basin

BCD: Bebington Court Drain

BGB: Below ground biomass

BMPs: Best Management Practices

BOD: Biochemical oxygen demand

BoM: Bureau of Meteorology

CANON: Completely autotrophic nitrate removal over

the nitrate

CE: Cation exchange

COD: Chemical oxygen demand

CR: Community respiration

CW: Constructed wetland

DAFWA: Department of Agriculture and Food

DEM: Digital Elevation Model

DNRA: Dissimilatory nitrate reduction

DO: Dissolved oxygen

DoW: Department of Water

DWC: Dry weather concentration

EC: Electric conductivity

Eh: Oxidation-reduction potential

FF: First flush

FFM: Floating macrophytes

GPP: Gross primary production

HF: Horizontal flow

HRAP: Healthy River Action Plan

HRT: Hydraulic retention time

HSSF: Horizontal subsurface flow

ISWMS: Integrated Stormwater Management System

LID: Low Impact Design or Development

MSD: Mars Street Drain

MSMD: Mills Street Main Drain

MUSIC: Model for Urban Stormwater Improvement

Conceptualisation

NEP: Net ecosystem production

OL: Ornamental lake

PND: Partial nitrification and denitrification

R: Respiration

RCM: Recycled concrete material

SCP: Swan Coastal Plain

SDC: Standardised delta concentration

SDC_ave: Standardised delta concentration_averaged

SERCUL: South East Regional Centre for Urban

Landcare

SF: Surface flow

SOD: Sediment oxygen demand

Element, chemical, nutrient:

Al: Aluminium

Al3(OH)3(PO4)2·5H2O: Avellite

Al(PO4)·2H2O: Variscite

C: Carbon

Ca: Calcium

CaCO3: Calcite

Ca5(Cl,F)(PO4)3: Apatite

Ca5(OH)(PO4)3: Hydroxylapatite

CH4: Methane

CO2: Carbon dioxide

DIC: Dissolved inorganic carbon

DIN: Dissolved inorganic nitrogen

DOC: Dissolved organic carbon

DON: Dissolved organic nitrogen

DOP: Dissolved organic phosphorous

Fe: Iron

Fe(PO4)·2H2O: Strengite

Fe3(PO4)2·8H2O: Vivianite

FRP: Filtered reactive phosphorus

FTN: Filtered total nitrogen

FTP: Filtered total phosphorus

Mg: Magnesium

Mn: Manganese

N: Nitrogen

N2: Nitrogen gas

NH3: Filtered ammonia

NO: Nitric oxide or nitrogen monoxide

N2O: Nitrous oxide

NO2: Filtered nitrite

NO3: Filtered nitrate

NOx: Filtered total oxidised nitrogen

NUON: Filtered non-urea organic

nitrogen

P: Phosphorus

PH3: Phosphine gas

PN: Particulate nitrogen

PP: Particulate phosphorus

S: Sulphur

SS: Suspended solid

TDC: Total dissolved carbon

TDS: Total dissolved solid

TKN: Total Kjeldahl nitrogen

TN: Unfiltered total nitrogen

TOC: Total organic carbon

TP: Unfiltered total phosphorus

TSS: Total suspended solid

UreaN: Filtered urea nitrogen

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SSF: Subsurface flow

SUDS: Sustainable Urban Drainage Systems

VCUA: Volumetric contribution from ungauged area

VF: vertical flow

VSSF: Vertical subsurface flow

WA: Western Australia

WSC: Water Sensitive Cities

WSCW: Wharf Street Constructed Wetland

WSMD: Wharf Street Main Drain

WSUD: Water Sensitive Urban Design

Numerical:

A: Active surface of the catchment that effectively contributed to runoff (ha)

Ab: Biomass area (m2)

As: Sediment area (m2)

Bs: Sediment bulk density (kg/m3)

C*: Average nutrient concentration at the inlet and MSD (mg/L)

Ci: Nutrient concentration at ith timestep (mg/L)

Cinlet: Nutrient concentration at the inlet (mg/L)

Coutlet: Nutrient concentration at the outlet (mg/L)

DOmax: Maximum DO concentration (mg/L) or saturation (%) during the afternoon

𝐷𝑂𝑚𝑎𝑥𝑖: Average maximum DO saturation per day during the afternoon before the storm

perturbation over four consecutive days (%)

DOmin: Minimum DO concentration (mg/L) or saturation (%) during the morning

𝐷𝑂𝑚𝑖𝑛𝑖: Average minimum DO saturation per day during the morning before the storm perturbation

over four consecutive days (%)

Ds: Sediment depth (m)

DWb: Dry weight of the biomass (kg)

EC: Electric conductivity (μS/cm)

EF: Event flux (kg/ha)

EMC: Event mean concentration (mg/L)

L: Nutrient load (mg/s)

LA: Nutrient load attenuation (%)

Li: Load at the inlet (mg/s)

Lo: Load at the outlet (mg/s)

NCb: Biomass nutrient concentration (mg/kg)

NCs: Sediment nutrient concentration (mg/kg)

NMb: Biomass nutrient mass (kg)

NMs: Sediment nutrient mass (kg)

Qb: Quadrat area as 0.0625 m2

Qi: Flow rate at ith timestep (m3/s)

Qoutflow: Discharge rate at the outflow (m3/s)

SMC: Site mean concentration (mg/L)

V: Volume of the AWCB (m3)

VE: Total run-off volume across an event (m3)

Vi: Volume proportional to flow rate at ith timestep (m3)

ΔDO: Delta dissolved oxygen (mg/L or %)

ΔDOsat: Delta dissolved oxygen saturation (%)

∆𝐷𝑂̅̅ ̅̅ ̅̅𝑝𝑟𝑒: Average metabolism over four consecutive days before the storm perturbation (%)

∆𝐷𝑂̅̅ ̅̅ ̅̅𝑝𝑜𝑠𝑡: Average metabolism over four consecutive days after the storm perturbation (%)

∆(∆𝐷𝑂̅̅ ̅̅ ̅̅ ): Average change in metabolism due to a storm perturbation (%)

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Table of Contents

Abstract .................................................................................................................................................. iii

Statement of originality .......................................................................................................................... v

Acknowledgements ................................................................................................................................. vi

Chapter 1 ................................................................................................................................................. 1

Introduction ............................................................................................................................................. 1

1.1 Background .................................................................................................................................... 2

1.2 Research aim and questions ........................................................................................................... 4

1.3 Research approach ......................................................................................................................... 5

1.4 Thesis outline .................................................................................................................................. 5

Chapter 2 ................................................................................................................................................. 7

Constructed wetlands for urban stormwater management: current research and future needs ..... 7

2.1 Background .................................................................................................................................... 8

2.2 Urban stormwater management ..................................................................................................... 9 2.2.1 Sources of stormwater nutrient ............................................................................................... 9 2.2.2 WSUD and WSC aspect for stormwater management ......................................................... 10

2.3 Constructed wetland and its biotic-abiotic component ................................................................ 12

2.4 Nutrient attenuation pathways...................................................................................................... 14 2.4.1 Attenuation of nitrogen ......................................................................................................... 15 2.4.2 Attenuation of phosphorus .................................................................................................... 18

2.5 Research needs and knowledge gaps ............................................................................................ 20 2.5.1 Performance variability due to CW design and type ............................................................ 20 2.5.2 Filter media as an effective nutrient sink .............................................................................. 25 2.5.3 Nutrient attenuation variability during flow dynamics ......................................................... 25 2.5.4 Role of macrophyte growth and decay in wetland performance ........................................... 27 2.5.5 Does the overall ‘metabolism’ of wetlands impact their attenuation ability ......................... 27 2.5.6 Effectiveness of CW restoration to improve nutrient attenuation ......................................... 29

Chapter 3 ............................................................................................................................................... 31

Nutrient attenuation in a surface flow constructed wetland experiencing summer low flow and

macrophyte senescence ......................................................................................................................... 31

3.1 Introduction .................................................................................................................................. 33

3.2 Materials and methods ................................................................................................................. 36 3.2.1 Site background and restoration works ................................................................................. 36 3.2.2 Data collection ...................................................................................................................... 36 3.2.3 Data analysis ......................................................................................................................... 41

3.3 Results .......................................................................................................................................... 44 3.3.1 Long term changes in wetland properties ............................................................................. 44 3.3.2 Nutrient accumulation or uptake in the sediment and macrophytes ..................................... 46 3.3.3 Hydrological variability on nutrients dynamics .................................................................... 53 3.3.4 Diurnal changes in wetland function .................................................................................... 58

3.4. Discussion ................................................................................................................................... 62 3.4.1 Restoration improves attenuation of specific nutrient species .............................................. 62 3.4.2 Hydrological and biogeochemical controls on nutrient attenuation ...................................... 66 3.4.3 DO as a proxy indicator of wetland metabolism ................................................................... 70

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3.5 Conclusions .................................................................................................................................. 71

Chapter 4 ............................................................................................................................................... 73

Stormwater nutrient attenuation in a multi-compartment constructed wetland ............................ 73

4.1 Introduction .................................................................................................................................. 75

4.2 Materials and methods ................................................................................................................. 77 4.2.1 Site background .................................................................................................................... 77 4.2.2 Data collection ...................................................................................................................... 80 4.2.3 Data analysis ......................................................................................................................... 82

4.3 Results .......................................................................................................................................... 85 4.3.1 Long term dynamics of nutrient quality ................................................................................ 85 4.3.2 Nutrient attenuation across compartments ............................................................................ 88 4.3.3 Impact of hydrological variability on nutrient attenuation ................................................... 88 4.3.4 Nutrients storage within sediments and macrophytes ........................................................... 95 4.3.5 DO variability ....................................................................................................................... 97

4.4 Discussion .................................................................................................................................... 98 4.4.1 Variability in performance within the system and over time ................................................ 98 4.4.2 ΔDO as an indicator of wetland metabolism ...................................................................... 106 4.4.3 Benefits of multi-functional system .................................................................................... 107

4.5 Conclusions ................................................................................................................................ 109

Chapter 5 ............................................................................................................................................. 111

Storm event-scale nutrient attenuation and metabolism in constructed wetlands ........................ 111

5.1 Introduction ................................................................................................................................ 113

5.2 Materials and methods ............................................................................................................... 114 5.2.1 Study sites ........................................................................................................................... 114 5.2.2 Data and field campaign ..................................................................................................... 115 5.2.3 Water balance ..................................................................................................................... 120 5.2.4 Nutrient attenuation estimation during events .................................................................... 120 5.2.5 Metabolism estimation ........................................................................................................ 122

5.3 Results ........................................................................................................................................ 123 5.3.1 Water balance during events ............................................................................................... 123 5.3.2 Water quality and nutrient attenuation during events ......................................................... 123 5.3.3 Changes of soil porewater properties due to riparian saturation ......................................... 126 5.3.4 DO dynamics during events ................................................................................................ 130

5.4 Discussion .................................................................................................................................. 131 5.4.1 Hydro-climate and catchment character determine nutrient export .................................... 131 5.4.2 CWs design and hydrological variability control nutrient attenuation................................ 135 5.4.3 Diurnal DO and metabolism shape nutrient dynamics ....................................................... 138

5.5 Conclusions ................................................................................................................................ 139

Chapter 6 ............................................................................................................................................. 141

Conclusions .......................................................................................................................................... 141

References ............................................................................................................................................ 145

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List of Figures

Figure 2. 1 Conceptual model indicating how stormwater flows in undeveloped or natural area

and urbanized area .............................................................................................................. 10

Figure 2. 2 Cross section of a surface flow constructed wetland with groundwater

connectivity.. ....................................................................................................................... 16

Figure 2. 3 Schematic representation of the main phase of above ground biomass of

macrophytes including leaf expansion, maturity and senescence. ...................................... 29

Figure 2. 3 Schematic representation of the main phase of above ground biomass of

macrophytes including leaf expansion, maturity and senescence. ...................................... 29

Figure 3. 1 Map of the Anvil Way Compensation Basin showing monitoring and sampling

points ................................................................................................................................... 38

Figure 3. 2 Nutrient attenuation (as SDC) in the Anvil Way Compensation Basin over pre- and

post-restoration regimes ...................................................................................................... 48

Figure 3. 3 Nutrient attenuation (as SDC) in the Anvil Way Compensation Basin over pre- and

post-restoration regimes ...................................................................................................... 49

Figure 3. 4 Change of attenuation (as SDC_ave) of N species by the Anvil Way Compensation

Basin over the pre- and post-restoration regimes ............................................................... 51

Figure 3. 5 Change of attenuation (as SDC_ave) of P species by the Anvil Way Compensation

Basin over the pre- and post-restoration regimes. .............................................................. 52

Figure 3. 6 Nutrient pools of TN, TP and TOC at the in-stream and bench sediments of the

Anvil Way Compensation Basin from November 2011 to May 2015. ............................... 53

Figure 3. 7 Nutrient pools in AGB and BGB of the Anvil Way Compensation Basin from

October 2012 to October 2013. ........................................................................................... 54

Figure 3. 8 Monthly total rainfall, total discharge and average flow rate at and around the

Anvil Water Compensation Basin from 2012 to 2014. ....................................................... 56

Figure 3. 9 Selected rainfall amount and rainfall duration at and around the Anvil Way

Compensation Basin along with flow discharge in 2012 and 2013. ................................... 56

Figure 3. 10 Spatial and temporal trend of water level and porewater oxidation-reduction

potential within a riparian zone transect, and nutrients from 11 to 17 March 2015. .......... 60

Figure 3. 11 Changes of delta DO saturation in response of solar exposure and stream

coverage with floating macrophytes in the Anvil Way Compensation Basin .................... 61

Figure 3. 12 Changes of delta DO saturation in response of solar exposure and stream

coverage with floating macrophytes in the Anvil Way Compensation Basin .................... 62

Figure 3. 13 Diurnal pattern of meteorology and water quality in the Anvil Way

Compensation Basin from 12 to 13 March 2015.. .............................................................. 63

Figure 4. 1 Map of the Wharf Street Constructed Wetland indicating sampling locations of

surface water, flow, sediment and macrophyte and DO. .................................................... 79

Figure 4. 2 Trends of NH3, NOx, TKN, DON, TN, FRP and TP nutrient concentrations along

the Wharf Street Constructed Wetland from 2009 to 2015.. .............................................. 86

Figure 4. 3 Nutrient attenuation in the Wharf Street Constructed Wetland from 2009 to 2015.

............................................................................................................................................ 89

Figure 4. 4 Nutrient attenuation in the SF1 and SSF1 compartment of the Wharf Street

Constructed Wetland from 2009 to 2015 ............................................................................ 90

Figure 4. 5 Nutrient attenuation within different compartments of the Wharf Street

Constructed Wetland ........................................................................................................... 91

Figure 4. 6 Hydrograph at the inlet and outlet of the Wharf Street Constructed Wetland during

different hydro-climatological conditions ........................................................................... 93

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Figure 4. 7 Nutrient concentration and flow patterns at the main inlet and main outlet of the

Wharf Street Constructed Wetland during a storm event (17–21 November 2009).. ......... 94

Figure 4. 8 Nutrient pools of TN, TP and TOC from June 2010 to May 2014 at three sediment

sampling sites of the Wharf Street Constructed Wetland. .................................................. 96

Figure 4. 9 Dry biomass and nutrient pools in AGB and BGB of B. articulata from November

2010 to May 2012 at three sampling sites of the Wharf Street Constructed Wetland. ....... 96

Figure 4. 10 Spatial and temporal trend of DO concentrations in water samples of different

compartments of the Wharf Street Constructed Wetland from 2009 to 2015..................... 99

Figure 4. 11 Relationship between DO and nutrient concentrations in different compartments

of the Wharf Street Constructed Wetland ......................................................................... 100

Figure 4. 12 Relationship between DO and nutrient concentrations in different compartments

of the Wharf Street Constructed Wetland ......................................................................... 101

Figure 4. 13 Relationship between inlet nutrient concentrations and nutrient attenuation in

different compartments of the Wharf Street Constructed Wetland. .................................. 103

Figure 4. 14 Conceptual relationships between different attenuation pathways of NH3 and

NOX ................................................................................................................................... 104

Figure 4. 15 Monthly ΔDO saturation as a function of solar exposure during the wet and dry

periods in the Wharf Street Constructed Wetland ............................................................ 107

Figure 4. 16 Some multi-functional aspects of the Wharf Street Constructed Wetland. ....... 108

Figure 5. 1 Map of the Wharf Street Constructed Wetland indicating different sampling points

.......................................................................................................................................... 116

Figure 5. 2 Map of the Anvil Way Compensation Basin indicating different sampling points...

.......................................................................................................................................... 117

Figure 5. 3 TN and TP concentrations at the inlet and outlet of the Wharf Street Constructed

Wetland and Anvil Way Compensation Basin during different storm events.. ................ 124

Figure 5. 4 Nutrient concentrations at the inlet and outlet of the Anvil Way Compensation

Basin during three storm events ........................................................................................ 125

Figure 5. 5 Stormwater hydrographs, pollutographs and nutrients dynamics in the Wharf

Street Constructed Wetland and the Anvil Way Compensation Basin ............................. 129

Figure 5. 6 Temporal variability of soil porewater properties in the transect of the Anvil Way

Compensation Basin ......................................................................................................... 129

Figure 5. 7 Nutrient concentrations in porewater samples of the Anvil Way Compensation

Basin ................................................................................................................................. 130

Figure 5. 8 Temporal variability of metabolism in the SF1 compartment of the Wharf Street

Constructed Wetland and the Anvil Way Compensation Basin during four consecutive

days of pre-storm events and post-storm events ............................................................... 132

Figure 5. 9 Principal component analysis of different parameters (average over four

consecutive days) during the pre-event and post-event in the Anvil Way Compensation

Basin.. ............................................................................................................................... 133

Figure 5. 10 Intra-storm variability flow and EMC of TN and TP in the Wharf Street

Constructed Wetland and Anvil Way Compensation Basin ............................................. 134

Figure 5. 11 Nutrient loads attenuation as a function of travel time of water flow in the Wharf

Street Constructed Wetland and Anvil Way Compensation Basin. Relationship between

nutrient load attenuation and changes in metabolism due to storm perturbation in the

AWCB .............................................................................................................................. 137

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List of Tables

Table 2. 1 Traits to categorize constructed wetlands ............................................................... 14

Table 2. 2 A comparison of surface, subsurface, vertical flow and horizontal flow CWs. ...... 15

Table 2. 3 Nitrogen and phosphorus attenuation and transformation dynamics within and

around constructed wetlands ............................................................................................... 21

Table 2. 4 Attenuation of nutrients and physicochemical parameters from urban stormwater

runoff from some site-specific investigations. .................................................................... 23

Table 3. 1 Summary table of spatial and temporal dynamics of studied nutrient parameters,

data type, sampling frequency and data source for the Anvil Way Compensation Basin

assessment ........................................................................................................................... 40

Table 3. 2 Spatial and temporal variability of nutrient concentrations in the Anvil Way

Compensation Basin. The dry and wet periods represent December to May and June to

November, respectively ...................................................................................................... 47

Table 3. 3 Nutrient attenuation as SDC and SDC_ave during the dry and wet periods over pre-

and post-restoration regimes of the Anvil Way Compensation Basin.. .............................. 50

Table 3. 4 Spatial and temporal changes of physical properties of above ground biomass of

aquatic macrophytes per quadrate in the Anvil Way Compensation Basin. ....................... 55

Table 3. 5 Spatial and temporal variation of groundwater nutrient concentrations at four bores

in the Anvil Way Compensation Basin from 2010 to April 2015. ..................................... 57

Table 3. 6 Conceptual consequences of the Anvil Way Compensation Basin restoration

initiatives on nutrient attenuation and transformation pathways. ....................................... 64

Table 4. 1 Summary table of spatial and temporal dynamics of studied parameters, data type,

sampling frequency and data source for the Wharf Street Constructed Wetland assessment

............................................................................................................................................ 81

Table 4. 2 Spatial and temporal variability of nutrient concentration in the WSCW .............. 87

Table 4. 3 Nutrient attenuation during the dry and wet period in the Wharf Street Constructed

Wetland ............................................................................................................................... 92

Table 4. 4 Nutrient attenuation during the dry and wet period in the Wharf Street Constructed

Wetland ............................................................................................................................... 92

Table 4. 5 Estimation of nutrient load attenuation in the Wharf Street Constructed Wetland

during the base and high flow conditions. .......................................................................... 95

Table 4. 6 Spatial and temporal variability of physical properties of above ground biomass of

B. articulata per quadrate in the Wharf Street Constructed Wetland. ................................ 97

Table 5. 1 Comparative description of the Wharf Street Constructed Wetland and the Anvil

way Compansatin Basin .................................................................................................... 118

Table 5. 2 Event campaigns and associated hydro-meteorology for the assessment of the

Wharf Street Constructed Wetland and the Anvil Way Compensation Basin. ................. 119

Table 5. 3 Variation of EMC, SMC, EF, load and load attenuation of TN and TP during storm

events in the Wharf Street Constructed Wetland and the Anvil Way Compensation Basin

.......................................................................................................................................... 126

Table 5. 4 EMC and load variability at the inlet and outlet for nutrient species in the Anvil

Way Compensation Basin during different storm events. ................................................ 127

List of Box

Box 2. 1 Main objectives and principles of WSUD for stormwater management. .................. 12

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Chapter 1

Introduction

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2

1.1 Background

Stormwater runoff carries nutrients from point and non-point sources of urban

catchment (Hatt et al. 2009; Gasperi et al. 2011; Burns et al. 2012; Zgheib et al.

2012). Due to the rapid expansion of impervious areas in cities around the globe, the

magnitude of nutrient loads associated with untreated stormwater is increasing, and

subsequently creating significant challenges for the downstream receiving waterways

(Walsh et al. 2005b; Brown et al. 2009; Burns et al. 2012; Fletcher et al. 2013). These

challenges include issues associated with water quality impairment due to the

formation of algal blooms and eutrophication, the depletion of dissolved oxygen (DO)

and generation of anoxia, the decline in aquatic biodiversity and in extreme cases, the

mortality of fish; all of these challenges can reduce the ecological and recreational

amenity of watercourses (Taylor et al. 2004; Miller & Boulton 2005; Kaushal et al.

2008; Cuffney et al. 2010; Hathaway et al. 2012). A holistic management plan to

attenuate excess stormwater nutrient is therefore needed to restore ecological services

and mitigate adverse effects within and around the receiving watercourses, and to

improve urban liveability (Hatt et al. 2007; Wong et al. 2012; Deletic et al. 2013;

Managi et al. 2016). A paradigm shift in stormwater management has been taking

place in many cities based on Integrated Stormwater Management System (ISWMS)

and through the adoption of Best Management Practices (BMPs) (Fletcher et al.

2014). Water Sensitive Urban Design (WSUD) is such an approach that is widely

practiced in Australia (Lloyd 2001). WSUD is based on the idea that the management,

protection and conservation of the urban water cycle must take place to ensure that the

urban water environment is sensitive to natural hydrological and ecological processes,

and that the ecological services of urban waterways are maintained (Deletic et al.

2013). A commonly used WSUD element is the constructed wetland (CW) often

implemented prior to a watercourse, to provide stormwater retention and nutrient

attenuation (Hatt et al. 2006; Burns et al. 2012; Fletcher et al. 2013).

CWs are engineered green bioreactors (Mitsch & Jorgensen 2003), that can

attenuate stormwater nutrients through different hydrological and biogeochemical

processes within the water, soils/sediments, aquatic macrophytes and associated

microbial communities (Malaviya & Singh 2012; Saeed & Sun 2012; Vymazal &

Kröpfelová 2015). These engineered wetlands are economically viable and

environmentally sustainable in comparison with other conventional stormwater

treatment systems, due to low construction and maintenance costs, relatively simple

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3

operation, and low energy requirements (Kadlec 2000; Puigagut et al. 2008; Kadlec &

Wallace 2009). Individual CWs can be classified into different groups (Fonder &

Headley 2013), where surface flow (SF) and subsurface flow (SSF) CWs are the two

most common types. In isolation, a SF or SSF CW may attenuate a particular nutrient

more than another, while multi-compartment or hybrid CW can combine the

advantages of individual SF and SSF CW into a single system, and provide better

overall nutrient attenuation (Ávila et al. 2014; Ayaz et al. 2015; Vymazal &

Kröpfelová 2015). However, optimization of nutrient attenuation in a CW over diurnal

to decadal timescales is challenging. Moreover, the extent of nutrient attenuation

within different compartments of a CW needs to be investigated under different

hydro-climatological and biogeochemical regimes.

The performance of a CW varies depending on its geological settings and

available hydro-biological conditions. CWs in Mediterranean climates such as on the

Swan Coastal Plain (SCP) of Western Australia (WA), experience prolonged periods

of low or near zero surface flows during the dry summer and therefore CW can

become stagnant or lentic system. However frequent rainfall events during the wet

winter and possible groundwater inputs increase water levels, generate a continuous

flow and convert CW as a lotic system. Periodic lentic-lotic transition of CW across

events, days and seasons makes the nutrient attenuation estimation challenging.

Moreover, CWs of the Mediterranean climates also experience macrophytes

senescence during the summer. Therefore, nutrient attenuation varies over time, and

how to optimization nutrient attenuation within this context is not well understood.

Furthermore, CWs function most effectively in the first few years after the

construction (Kadlec & Wallace 2009; Mustafa et al. 2009; Vymazal 2013b), however

nutrient attenuation can decrease with time, due to the senescence and accumulation

of plant material that subsequently releases nutrients back into the system (Hancock

2002; Kröger et al. 2007), the accumulation of nutrients and organic matter in the

sediments (Craft 1996), the degradation of the riparian zones and development of

preferential flow paths (Harrison et al. 2012), the diffusion and bioturbation of

nutrients from the sediments into water column (O'Brien et al. 2012), the development

of anoxic environments and the input of polluted groundwater (Gabriele et al. 2013;

Teufl et al. 2013). Income cases, over the long term CWs can become a source of

nutrients and may require periodic restoration. Understanding the trend in nutrient

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4

attenuation after the restoration or indeed the optimum time for restoration is

challenging and needs further investigation.

Whilst the focus of understanding CW function is traditionally on their ability

to reduce nutrients, CWs are highly dynamic and transition between autotrophic to

heterotrophic metabolism at the ecosystem-scale, depending on available light and

organic matter. Measurements of autotrophy/heterotrophy and CW metabolism can be

complex and costly, and methodology varies between lentic and lotic systems. Low-

cost alternative approaches, or proxies, offer potential advantages to assess CW

function and their metabolism. One suggested proxy is the net variation diurnal

oxygen as delta DO (ΔDO), defined as the net effect of biogeochemical processes that

consume oxygen (e.g., respiration) and processes that deliver oxygen to the water

column (e.g., photosynthesis and reaeration or exchange with the atmosphere). If ΔDO

can be shown to be an effective proxy, under a range of hydrological conditions, this

low-cost high resolution sensor data could be easily used as an indicator of function

and nutrient dynamics in the CW.

1.2 Research aim and questions

The main goal of this thesis was to investigate stormwater nutrient attenuation

from diurnal to decadal scales, in two CWs: (a) a single stage mender SF CW and (b)

a hybrid CW with multiple alternating SF and SSF compartments. These CWs on the

SCP in WA experience a Mediterranean climate with prolonged low flow conditions

and macrophytes senescence during the dry summer, high flow conditions during the

wet winter and episodic flows after a storm event. The research also investigated DO

based metabolism as a proxy indicator of two CWs during different flow regimes.

The major research questions were:

1. How does nutrient attenuation vary over diurnal, event, seasonal and long-term

time-scales?

a) How do prolonged low flows and senescence of macrophytes during the

summer impact nutrient attenuation?

b) How does nutrient attenuation vary during episodic storm pulses?

c) How do antecedent conditions influence nutrient attenuation?

2. Can diurnal DO fluctuation be used as a proxy of wetland metabolism to gain

insight into biogeochemical processes controlling nutrient attenuation?

d) How does diurnal DO fluctuation impact nutrient attenuation?

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1.3 Research approach

Regular field sampling was undertaken from December 2012 to December

2015 to collect surface water and soil porewater samples and analysed them for

nutrients (details in Chapters 3 to 5). DO loggers, a multi-parameter water quality

sonde, oxidation-reduction potential (Eh) sensors and conductivity, temperature and

water depth (CTD) loggers were installed to receive high resolution spatial and

temporal data (details in Chapters 3 to 5). Historical data of water quality, water flow,

sediment quality, macrophytes properties, and meteorology were also collected,

synthesised and analysed. The thesis accounted nutrient attenuation in two different

types of CWs using extensive dataset which spanned over diurnal, event, seasonal and

annual time-scales. The standardised delta concentration (SDC), defined as the

standardised difference in nutrient concentrations between the inlet and outlet, was

used as an index to assess nutrient attenuation in the CWs, particularly during the low

flow conditions. SDC concept also used when there were ungauged water inputs to the

systems. Relative contribution of sediments, macrophytes, CW design, hydrological

seasonality and biogeochemical processes on overall nutrient dynamics was reported.

DO based metabolism was explored to find its effectiveness for using it as a proxy

indicator of CW function under hydrological variability.

1.4 Thesis outline

This thesis contains six chapters. A general background of stormwater nutrient

dynamics and attenuation in CWs is presented in Chapter 2. Chapters 3 to 5 are

presented in the style of manuscripts for journal publication. As a result these chapters

are self-contained and may be viewed independent of the rest of the thesis. Due to the

choice of this format, there may be some repetition in the literature review, site

description and methodology for these chapters. In Chapter 3, the research focuses on

nutrient attenuation in a surface flow CW that experiences prolonged low flows and

macrophyte senescence during the summer periods. The site was built in 2004 as a

drainage compensation basin and restored in 2010. Water quality data, water flow

data, sediment quality, macrophyte biomass, soil porewater and DO are assessed to

investigate diurnal to long-term (2004 to 2015) nutrient dynamics. In Chapter 4, the

research describes nutrient attenuation in a hybrid CW that contains alternating SF and

SSF compartments across episodic event to long term (2009 to 2015) time-scale.

Water quality data, water flow data, sediments quality, macrophytes quality and DO

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6

data are also assessed for this chapter. We also quantified nutrient load attenuation in

Chapter 4 over baseflow/low flow and highflow conditions. Chapter 5 shows a

comparison of nutrient attenuation in the two CWs during episodic storm events. This

chapter also deals with metabolism over fourteen storm events from 2014 to 2015 to

gain insight into metabolism dynamics due to storm perturbation. Chapter 6 presents

overall findings and conclusions, and also indicates some research gaps and

recommends future works.

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Chapter 2

Constructed wetlands for urban stormwater

management: current research and future needs

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8

2.1 Background

One of the key functions and ecological services of urban watercourses is their

ability to attenuate nutrients from inflowing stormwater runoff. The stormwater runoff

can modify the morphological and hydrological characteristics within and around the

watercourses, and can impact groundwater flow and affect nutrient cycles of

downstream river and estuary (Walsh et al. 2012; Fletcher et al. 2013). Watercourses

nurture ecological resources and support embedded environmental and economic

services. However, excessive nutrient loads can be transported into the watercourses

by stormwater runoff, resulting from growing urbanisation, industrial activities,

shifting catchment properties and climate variability (Figure 2. 1). Excess nutrients

can trigger algal blooms, deplete dissolved oxygen (DO), hamper fish production,

fragment habitat, endanger biodiversity and lower the amenity in the water bodies

(Taylor et al. 2004; Hathaway et al. 2012). Holistic management plans are therefore

required to reduce nutrient (source control in urban catchment), mitigate nutrient

(nutrient attenuation) and subsequently protect stormwater receiving urban waterways

and support ecological services of such waterways.

The use of Integrated Stormwater Management Systems (ISWMS) and the

adaptation of Best Management Practices (BMPs) resulted in a paradigm shift in

stormwater management at both local and regional scales. In particular, some current

initiatives for stormwater management include Low Impact Design (LID) in the USA

and New Zealand, Sustainable Urban Drainage Systems (SUDS) in the UK and Water

Sensitive Urban Design (WSUD) in Australia (Fletcher et al. 2014). Under WSUD,

different aspects of the management, protection and conservation of urban water,

including stormwater, are prescribed (Deletic et al. 2013). WSUD (Box 1. 1) approach

ultimately minimizes the connection between the impervious surface and receiving

watercourses, and maximises the storage stormwater temporarily within the watershed

using retention-based or infiltration-based treatment facilities (Fletcher et al. 2013).

WSUD has promoted the use of constructed wetlands (CWs) as a retention-based

technology for attenuating nutrients from stormwater runoff (Deletic et al. 2013;

Fletcher et al. 2013; Payne et al. 2014). Soils/sediments, amended substrates, aquatic

macrophytes and microbial communities within CWs can attenuate stormwater

nutrient through hydrological, biological and biogeochemical processes (Vymazal

2013b). CWs, as engineered systems, are economically viable and environmentally

sustainable in comparison with other conventional wastewater treatment systems, with

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9

low construction and maintenance costs, easy operation and low energy requirements

(Puigagut et al. 2008; Kadlec & Wallace 2009). In addition, CWs can provide multi-

functional benefits and services in the urban landscape, including regulatory services

(flood control, micro climate improvement and soil erosion control), biogeochemical

services (soil formation, carbon retention and trace element storage), ecological

services (ecosystem maintenance and food web support), provisioning services (plant

biomass production, biodiversity support and stormwater harvest) and cultural

activities (recreational and aesthetic benefits, and educational programs enhancement)

(MEA 2005; De Groot 2006). As background to the subsequent research chapters

within this thesis, the present chapter provides an overview of nutrient attenuation

mechanisms within CWs, focusing on nitrogen (N) and phosphorus (P) sourced from

urban stormwater runoff. An improved understanding of nutrient attenuation is

essential to optimize the urban CW performance and support water management

practices. Finally, some knowledge gaps and future research needs are highlighted.

2.2 Urban stormwater management

2.2.1 Sources of stormwater nutrient

Urban stormwater traditionally refers to water runoff over fully or partially

impervious surfaces or points and non-point sources within urban catchments during

and/or after any precipitation event (Barbosa et al. 2012). Excess nutrient

concentrations and composition have been measured by collecting water samples

along the flow path, from the house, garden and carpark, to the ditch and outlet drain,

and finally in the downstream river, estuary or coastal zone. Stormwater quality can

be highly variable, and is a function of (a) meteorology or climate (rainfall intensity,

antecedent dry/wet period between storm events and evaporation), (b) location (site,

urban condition and land use pattern), (c) catchment characteristics (size, impervious

surface fraction, connectivity of paved surfaces and atmospheric deposition), and (d)

drainage infrastructure (separate or combined, open channels/streams or pipes, age,

cross-connections, sewer overflows, connection to surrounding groundwater or

existing septic tanks) (Gasperi et al. 2011; Zgheib et al. 2012). For instance,

sometimes intense rainfall can mobilise nutrients from the catchment and deliver them

as a higher load, the phenomenon known as the first flush (FF) effect (Deletic 1998;

Bach et al. 2010). However, subsequent rainfall dilutes nutrient concentrations. More

nutrients can be washed away from semi-impervious surfaces, while impervious

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10

surfaces deliver nutrients quickly to the downstream water courses. The ratio between

infrastructure coverage and open space influences the quantity of water runoff and

infiltration during and after storm events. The drainage network accelerates water

runoff through increased surface water connectivity, and reduces stormwater

infiltration into the groundwater.

Figure 2. 1 Conceptual model indicating how stormwater flows in undeveloped or natural area

and urbanized area. (a) Stormwater flows in undeveloped or natural area and (b) in urbanized

area, roof runoff is diverted into soakwells (shallow vertical infiltration wells) and road runoff

is locally infiltrated, leading to an increasing groundwater table and a reduction of

evapotranspiration. The symbols P, ET, In, Ir, SI and A represent precipitation,

evapotranspiration, infiltration, irrigation, stormwater infiltration and abstraction, respectively.

The figure is modified after Locatelli et al. (2017).

2.2.2 WSUD and WSC aspect for stormwater management

Australia has developed WSUD approach in recent decades to integrate water

supply systems, wastewater treatment processes and stormwater management into

urban planning and design, considering ecological sustainability, environmental

assimilation capacity and economic viability (Whelans et al. 1994; Lloyd 2001; Wong

et al. 2012). The concept comprises of several objectives and principles based on

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11

multi-disciplinary planning and practices for stormwater management (Box 2. 1). The

approach involves pro-active structural planning for urban development, that

recognises the opportunities for urban design, landscape architecture and

infrastructure interventions (Wong & Eadie 2000). WSUD consists of two parts:

‘water sensitive’ and ‘urban design’. The meaning of WSUD varies amongst

practitioners, reflecting its framework, application and coverage. Wong et al. (2012)

defined WSUD, for instance, as “a new paradigm in planning and design of urban

environments that is ‘sensitive’ to the issues of water sustainability and environmental

protection”. The agreement of the National Water Initiative by Australian

governments expresses WSUD as “the integration of urban planning with the

management, protection and conservation of the urban water cycle that ensures that

urban water management is sensitive to natural hydrological and ecological processes”

(COAG 2004). The approach also consolidates the urban water cycle, including

stormwater, groundwater and wastewater management and water supply, into urban

design in order to minimise environmental degradation, improve aesthetic and

recreational attractions (Lloyd 2001), enhance urban stream health (Mitchell et al.

2007), provide protection for waterways from being contaminated, elevate urban

discharge system (Li et al. 2009), beautify urban landscape and improve micro-

climate by enhancing evapotranspiration (Endreny 2008).

In the last couple of decades, several urban stormwater treatment technologies

and WSUD elements have been developed for achieving Water Sensitive City (WSC)

(Wong & Brown 2008; Brown et al. 2009; Wong et al. 2012). The WSC approach

aims for collaboration between multi-sectoral stakeholders in the urban planning and

designing of future cities, improving existing poorly equipped water services to

support the projected population growth and tackling economic and meteorological

uncertainties (Brown et al. 2009; Deletic et al. 2013). The approach utilizes different

elements of resilient, liveable, productive and sustainable cities with a view to

providing water security for social need and economic prosperity. Such planning shifts

the focus from water supply and wastewater disposal to more holistic systems that

integrate different water sources, enables the combination of centralized and

decentralized water operations and expands the range of functional and ecological

services provided by urban water to achieve ‘the cities of the future’ (Wong et al.

2012). WSUD elements for stormwater management can be grouped broadly as (a)

infiltration-based technologies and (b) retention-based technologies (Fletcher et al.

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12

2013). CWs are generally retention-based technologies that can be used to treat, re-

cycle and re-use stormwater to achieve relevant WSUD objectives.

Box 2. 1 Main objectives and principles of WSUD for stormwater management.

Major objectives of WSUD

A. Reduce impact on receiving waters

1. Minimise impacts on existing natural features, ecological processes and natural

hydrologic behaviour of catchments

2. Improve the quality of and minimise polluted stormwater discharges to the natural

environment.

3. Improve waterway health through restoring or preserving the natural hydrological regime

of catchments through treatment and reuse technologies

4. Reduce runoff and peak flows from urban developments during storm events

5. Harmonise water cycle practices across and within the institutions responsible for

waterway health, flood management, pollution prevention and protection of social

amenity

B. Promote re-use

6. Adopt a fit-for-purpose approach to the use of potential alternative sources of water

including stormwater

7. Incorporate collection, treatment and/or reuse of runoff, including roof water and other

stormwater

8. Treat stormwater to meet water quality objectives for reuse and/or discharge by capturing

sediments, pollution and nutrients through the retention and slow release of stormwater

C. Protection of “social” water services

9. Increase social amenity and aesthetic with water for the urban dwellers through multi-

purpose green space, landscaping and integrating water into the landscape to enhance

visual, social, cultural and ecological values

10. Account for the nexus between water use and wider social and resource issues

11. Promote a significant degree of water-related self-sufficiency within urban settings by

optimizing the use of water sources to minimise potable storm and waste water inflows

and outflows through the incorporation into urban design of localised water storage

Modified after Lee & Yigitcanlar (2010)

2.3 Constructed wetland and its biotic-abiotic component

In general, wetlands are highly productive and biologically diverse ecotones

between terrestrial and aquatic environments, which are characterized by shallow

water overlaying waterlogged soil and interspersed with submerged or emergent

vegetation. Wetlands are broadly two types: natural wetlands and CWs. CWs are

extensively engineered systems built for specific purposes such as providing domestic,

industrial and urban stormwater management and nutrient treatment. Overall CWs can

be categorized into different types (Table 2. 1) according to water level, saturation of

media, presence of vegetation, hydraulic and flow patterns particularly for domestic

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13

and industrial wastewater treatment. However these classifications can be also applied

for urban stormwater nutrient attenuation. There are two classes of CW based on

water level: (a) free water or surface flow (SF) CWs and (b) subsurface flow (SSF)

CWs (Kadlec & Wallace 2009). A combination of SF and SSF CWs generates hybrid

CW. Flows within the CWs can be vertical flow (VF) and horizontal flow (HF), and

they have specific advantages and disadvantages (Table 2. 2).

CWs contain both biotic and abiotic components. Macrophytes and microbes

are the main biotic components of CWs, while soils/sediments and filter media are the

main abiotic components. Aquatic macrophytes vary depending on water level,

geographic setting and tolerance to variable environmental conditions. Details of

macrophyte classifications in CWs are described elsewhere (Brix 1994; Vymazal

2011; Saeed & Sun 2012; Vymazal 2013a), however they can be summarised as four

categories:

(a) Emergent macrophytes: These are typically rooted on saturated or

submerged soil, containing extensive root and rhizome systems, with leaves and stems

extending out of the waterbody.

(b) Floating leaf macrophytes: These are usually rooted in submerged

sediments but leaves and flowers float on the water surface.

(c) Free-floating macrophytes: This group grows and floats freely on or under

the water surface. Root systems, if present, generally hang beneath the plant and are

not attached to the bottom sediments.

(d) Submerged macrophytes: These grow underwater, particularly in oxygen

rich areas. The photosynthetic tissues are also submerged.

Microbial organisms play important roles in the processing of nutrients in

CWs. Major microbial organisms include bacteria, algae and fungi. Bacteria can be

both autotrophic and heterotrophic. Autotrophic bacteria use carbon (C) from carbon

dioxide (CO2) while heterotrophic bacteria utilise organic carbon for the formation of

cell tissue. Phototrophic organisms use light as an energy source. Phototrophs can be

either autotroph e.g., photosynthetic bacteria or heterotrophic e.g., Sulphur (S)

reducing bacteria. In contrast chemotrophs, derive energy from chemical reactions.

Nitrosonomas and Nitrobacter are the common examples of autotrophic chemotrophs

(Reddy et al. 1984; US EPA 1993; Kadlec & Knight 1996; Paul & Clark 1996).

Sediments/soils are the main abiotic components of CWs. Stormwater nutrient usually

settles in the sediments. Different filter media are also used in the CWs to enhance

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specific nutrient attenuation. The artificial media or substrates can be made up of

natural particles i.e., sand, clay, gravel, calcite or calcium carbonate (CaCO3), peat,

zeolite and limestone; industrial by-products i.e., slag, fly ash, coal cinder and alum

sludge; or artificial products i.e., activated carbon, light weight aggregate, compost

and calcium silicate hydrate (Saeed & Sun 2012; Wu et al. 2015).

Table 2. 1 Traits to categorize constructed wetlands.

Physical

attribute

Specific

trait

Description Defined classes

for each trait

Sub-class

Hydrology

Water

position

Position of water surface

relative to soil or substrate

Surface flow –

Subsurface flow –

Flow

direction

Predominant direction of

flow through system

Horizontal –

Vertical

Down flow

Up flow

Mixed flow

Saturation

of media

Degree of saturation in

media-based systems

Free-draining –

Intermittent –

Constant –

Influent

loading

type

Position and type of

influent distribution in

media-based systems

Surface inflow –

Subsurface inflow –

Basal inflow –

Vegetation

Sessility Location of the roots:

attached in the benthic

sediments or floating

Sessile (benthic bound) –

Floating –

Growth

form

Dominant growth form of

the vegetation in relation

to the water

Emergent Herbaceous

Woody

Submerged –

Floating leaved –

Free-floating –

Modified after Fonder & Headley (2011, 2013)

2.4 Nutrient attenuation pathways

A wide range of hydrological and biogeochemical interactions between water,

macrophytes, microbes, soils, filter media and ambient air within and around the CWs

combine to support water purification and/or nutrient attenuation (Figure 2. 2). CWs

are active bioreactors, governed by material and energy fluxes that lead to

characteristic chemical reactions. Nutrient attenuation may occur through destructive

or non-destructive pathways. Nutrients can be degraded or consumed during

destructive processes resulting in maximum attenuation, while non-destructive

processes convert nutrients from one form to another.

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Table 2. 2 A comparison of surface, subsurface, vertical flow and horizontal flow CWs.

SF SSF

Ad

van

tag

es Provide the maximum attenuation if constructed

for specific nutrient

Potential scope of air-water interaction

Support macrophyte growth

Provide alternating conditions for nutrient

processing

Better integration in landscape

Nutrient attenuation in full scale

Substrates encourage nutrient attenuation

Dis

adv

anta

ges

Problems with mosquitos

Dominant aerobic or anaerobic condition can

attenuate specific nutrients and generate others

Clogging problem can arise

Shut down of water flow to alternating

compartment if flow is low

May require additional water to keep full

system flowing

VF SSF HF SSF

Ad

van

tag

es Require relatively small area compared to HF

Potential scope of oxygen supply and mixing

Potential for nitrification process

Simple hydraulics

Higher attenuation from initial stage of operation

Long flow distances

Formation of humic acids for N and P

attenuation

Potential for denitrification process

Dis

adv

anta

ges

Short flow distances

Clogging problem can occur

Limited nitrate attenuation or denitrification

Need higher technical involvement

Lower P attenuation capabilities

Require a relatively high area compared to VF

Clogging problem can occur

Sulphur transformation can affect nitrification

sensitivity

Low ammonium oxidation

Less P attenuation

Preferential flow pathways emerge

Modified after Vymazal (2007); Malaviya & Singh (2012); Saeed & Sun (2012); Vymazal (2013b); Meng et al.

(2014)

In general, ammonia (NH3), nitrate (NO3), nitrite (NO2), total Kjeldahl

nitrogen (TKN), urea, dissolved inorganic nitrogen (DIN), dissolved organic nitrogen

(DON), particular nitrogen (PN) and total nitrogen (TN) are common N-based

nutrients in urban stormwater. Furthermore, filterable reactive phosphorus (FRP),

particulate phosphorus (PP), organic phosphorus and total phosphorus (TP) are the

main P-based nutrients. However, these names can slightly differ depending on

purposes of interpretation (Chapter 3 to 5).

2.4.1 Attenuation of nitrogen

The main routes of N attenuation in the CWs are sedimentation, plant uptake,

adsorption, nitrification, ammonification, ammonia volatilization, denitrification,

dissimilatory reduction of nitrate to ammonium (DNRA), N2 fixation and organic N

burial. Moreover, recently identified processes such as partial nitrification-

denitrification (PND), anaerobic ammonia oxidation (ANAMMOX) and completely

autotrophic nitrate removal over the nitrate (CANON) are also considered as N

processing pathways.

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Figure 2. 2 Cross section of a surface flow constructed wetland with groundwater

connectivity. Nutrients can enter the system through surface flow or runoff and groundwater

inputs. Aerobic and anaerobic biogeochemical reactions transform nutrients within

soils/sediments and water. Macrophytes and microbes can also uptake nutrients during growth

phases and release them during senescence. Nutrients can be exchanged across the sediment-

water column interface.

Both dissolved and particulate nutrients in the shallow water can be affected

by the presence of microbes, whether under aerobic or anaerobic conditions. Oxygen

for aerobic microbial degradation can be supplied via atmospheric oxygen diffusion,

photosynthesis, convection/wind effects or macrophytes root transfer into the

rhizosphere. Aerobic microbial degradation is dominant in the SF CWs, while the SSF

CWs prefer anaerobic microbial cycling of nutrients.

Ammonification converts organic N to NH3 and can occur when stormwater

contains high concentrations of organic N (Savant et al. 1982). Some of the generated

NH3 can be volatilized and released as gas (Reddy et al. 1984) (Table 2. 3).

Nitrification (Table 2. 3), microbial conversion of NH3 to NO3, is an important

pathway of NH3 attenuation and the process depends on microbial activity, DO level,

temperature and incoming NH3 concentrations. Sufficient oxygen in the water column

is essential for aerobic microbial processing. Initially microbial transformation of NH3

to NO2 occurs, and then NO2 converts to NO3. Chemolithotrophic bacteria like

Nitrosomonas, Nitrosococcus and Nitrosospira are active at the first stage. Facultative

chemolithotrophic bacteria such as Nitrospira and Nitrobacter, other bacteria such as

Arthrobacter globiformis, Mycobacterium phlei and Thiosphaera, or fungi such as

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Aspergillus flavus, Penicillium or Cephalosporium play a role at the later stage

(Reddy et al. 1984; US EPA 1993; Kadlec & Knight 1996; Paul & Clark 1996).

Microbial denitrification (Table 2. 3) is a major process of N attenuation in

CWs where NO3 transforms into nitrous oxide (N2O), nitric oxide or nitrogen

monoxide (NO) and ultimately to nitrogen gas (N2). Nitrate acts as the terminal

electron acceptor for this process and organic carbon sources act as electron donor

(Vymazal 1995). Denitrifying bacteria are usually chemoheterotrophs indicating that

they derive energy through chemical reactions. Bacillus, Micrococcus and

Pseudomonas are probably the most important genera in soils, while Pseudomonas,

Aeromonas and Vibrio are common in the aquatic environment (Bachand & Horne

1999; Vymazal 2007).

DNRA (Table 2. 3) reduces NO2 and NO3 to NH3 (Dong & Sun 2007; Kadlec

& Wallace 2009). This process takes place under low oxidation-reduction potential

(Eh) conditions and usually in C rich environments, particularly in the SSF CWs

where facultative or anaerobic microbial populations are dominant (Garcia et al.

2010). PND (Table 2. 3) is the microbiological conversion of ammonia into nitrite in

oxygen and carbon-limited environments (Jianlong & Ning 2004; Jianlong & Jing

2005). This process requires 25% less oxygen and 40% less organic matter than

nitrification and denitrification, respectively (Van Dongen et al. 2001; Jianlong & Jing

2005). Moreover, lower oxygen levels inside the CW can promote the growth of

ammonium oxidizers over nitrate oxidizers (Zhang et al. 2011). ANAMMOX directly

oxidizes ammonium and nitrite into nitrogen gas. NO3 is considered an electron

acceptor and the process is influenced by the Planctomycete bacteria group under

anaerobic conditions. Different intermediate products including hydrazine and

hydroxylamine can be formed. However, the growth of ANAMMOX bacteria is

usually slow, and higher concentrations of sulphide, NH3 and NO2 in water can slow

the growth of ANAMMOX bacteria even further (Third et al. 2001; Saeed & Sun

2012). Simultaneous PND and ANAMMOX occur in CANON. CANON also depends

on the mutual co-existence of aerobic ammonium oxidizers and anaerobic

ANAMMOX bacteria under oxygen limited conditions (Third et al. 2001; Saeed &

Sun 2012).

Biomass assimilation is the process of N uptake by macrophytes,

phytoplankton or microbial biomass that can reduce dissolved N concentrations in the

CWs (Sun et al. 2005). Macrophytes are natural purifiers within CWs (Malaviya &

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Singh 2012) as they: (a) provide suitable roots-shoots-leaves media for nutrient

attachment, uptake and storage during early to mature stages of growth (Brodrick et

al. 1988), (b) provide surfaces and oxygen in the below ground biomass or

root/rhizosphere zones for the growth and attachment of microorganisms or biofilms

for nutrient processing (Cui et al. 2010; Saeed & Sun 2012), (c) provide carbon from

root exudates (due to photosynthetically fixed carbon) for denitrification (Brix 1997;

Masi 2008; Wang et al. 2012), and (d) facilitate uniform flow distribution and flow

retardation and increase nutrient contact with plant surfaces for the effective removal

of finely graded particles and associated nutrients (Wong et al. 1999). However, the

total N attenuation in macrophytes can be limited as senescent macrophytes can

release nutrients back into the CW. Therefore, macrophytes require periodic

harvesting for permanent N removal.

Adsorption of NH3 from incoming waters by cation exchange (CE) processes

can also reduce TN concentrations (Bayley et al. 2003; Cui et al. 2010; Saeed & Sun

2011). This process is dominant in SSF system, where there is increased contact

between the substrate and nutrients. N2 fixation converts gaseous nitrogen into NH3

and can increase the N stored in the CWs. Symbiotic actinomycetes (associated with

nodulated host plants) and asymbiotic (free-living) heterotrophic bacteria and blue-

green algae (cyanobacteria) can fix N2 (Stewart 1973; Johnston 1991; Paul & Clark

1996).

Organic N burial takes place in the CWs when organic N from detritus,

senescent or refractory plant material gets buried and form litter and eventually peat.

The process may occur when emergent vegetation dominates SF CWs, where the litter

layer plays an important role in nutrient attenuation (Vymazal 2007). However, due to

sediment resuspension these particulate organic nutrients can be released to the water

column prior to the formation of the more stable peat.

2.4.2 Attenuation of phosphorus

P attenuation processes can be grouped into two broad categories: (a) long

term attenuation processes (sedimentation or physical settling, accretion,

accumulation, precipitation, adsorption, litter/peat ligand exchange) and (b) short term

attenuation processes (plant establishment, biofilm growth and microbial colonization

of litter) (Bavor & Adcock 1994; Kadlec & Knight 1996; Reddy et al. 1999).

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Sedimentation or physical settling processes filter course or particulate

material and this is of particular importance for P attenuation. P species can

accumulate in the soils/sediments or filter media and thus results a higher attenuation.

Chemical precipitation converts soluble P into insoluble P. Precipitation can also

incorporate phosphate ions into inorganic minerals, for example aluminium (Al),

calcium (Ca), iron (Fe) and magnesium (Mg) minerals, forming amorphous or poorly

crystalline solids (Vymazal 2007). P-containing mineral precipitates commonly found

in CWs include apatite as Ca5(Cl,F)(PO4)3, hydroxylapatite as Ca5(OH)(PO4)3,

variscite as Al(PO4)·2H2O, strengite as Fe(PO4)·2H2O, vivianite as Fe3(PO4)2·8H2O

and wavellite as Al3(OH)3(PO4)2·5H2O (Reddy & D'Angelo 1997). P can also co-

precipitate with other minerals, such as ferric oxyhydroxide and carbonate minerals,

such as CaCO3 (Vymazal 2007). At pH > 6, calcium phosphate can also be formed

and precipitate.

P adsorption by soil substrates is a long-term mechanism for P attenuation

(Richardson 1985; Kadlec & Knight 1996). The adsorption capacity of a substrate

depends on the clay content and mineral components (Rhue & Harris 1999) as clay

materials have higher adsorptive capacity. The concentrations of amorphous Al, Fe,

Ca and total organic carbon (TOC) also influence P adsorption (Reddy et al. 1995;

Reddy et al. 1999).

CE reactions can take place where negatively charged sediment/soil particles

attach to positively charged phosphate (Richardson 1985). Phosphate displaces water

or hydroxyls from the surface of Fe and Al hydrous oxides to form monodentate and

binuclear complexes within the coordination sphere of the hydrous oxide, through

ligand exchange reactions (Faulkner & Richardson 1989). Moreover, the transfer

between dissolved and particulate phases of P takes place via a two-step process: (a)

the rapid exchanges of phosphate between the soil porewater and soil particle or

mineral surfaces (adsorption) and (b) the slow penetration of phosphate into solid

phases (absorption) (Dunne & Reddy 2005). Since P sorption capacity is finite, once

soil sorption sites become saturated by prolonged nutrient loading, the CWs may

become a source of P, instead of a sink (Kadlec & Wallace 2009).

Macrophytes can uptake dissolved inorganic P from incoming water (Brix

1994; Vymazal 2001). Most of the uptake of P is performed by plant roots, followed

by absorption through leaves and shoots (Kadlec & Knight 1996; Vymazal 2007;

Vymazal 2013a). Macrophytes uptake P at higher rates during early to mature growth

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phases. However, senescent macrophytes can release dissolved P to the CWs

(Cheesman et al. 2010). Microbiota may have high growth rates due to high P

consumption rates in the CWs. Although P uptake by microbiota and biofilms in the

CWs is rapid, the total P microbial pool may not be significant. Moreover, the

majority of dissolved P taken up by microbial biomass will be rapidly returned to the

P cycle through bacterial decomposition (Reddy et al. 1995). Bacterial communities

also contribute to the long-term P burial in the system (Gächter & Meyer 1993). In

overall, stormwater nutrient can transfer from water column to groundwater,

atmosphere, sediments, microbes or macrophytes (Table 2. 3). Selected nutrient

attenuation efficiencies measured in different CWs are summarized in Table 2. 4.

2.5 Research needs and knowledge gaps

2.5.1 Performance variability due to CW design and type

CWs provide variable N and P attenuation across the world (Table 2. 4).

Attenuation of stormwater nutrient can go up to about 95%, however, this

performance of the CWs are not same. Major factors driving this differing

performance include CW treatment area, volume and flow path and

compartmentalization, all of which influence the biogeochemical and hydrological

processing of nutrients. CWs can be selective for particular nutrients depending on

such biogeochemical and hydrological variability. The SF and SSF systems usually

exhibit good attenuation for NH3 and NO3, respectively (Saeed & Sun 2012).

However, single-staged CW, either the SF or SSF, can also release nutrients to the

water column. Hybrid CWs have potential as an emerging beneficial approach that

nutrients generated in one compartment of these systems can be attenuated in

subsequent alternating compartments. Subsequent compartments ultimately provide

optimal environments for nutrient attenuation and polish the water. Benefits of

different approaches can be maximised by careful design, but uncertainty remains as

to what aspects of CW design promote attenuation. It is critical to show how the

different types of CWs perform under the highly variable flow and biogeochemical

conditions. Furthermore, water is generally unevenly distributed in the full scale CWs

because of channelization, microtopography, pattern of macrophytes, presence of any

woody log, filtering media (Fink & Mitsch 2007) and therefore optimization of CW

performance can be challenging.

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Table 2. 3 Nitrogen and phosphorus attenuation and transformation dynamics within and around constructed wetlands.

Nutrient

Transformation route within CW

Transformation

mode

Output of nutrients in different compartments in close vicinity of CW

Surface

water

Groundwater Atmosphere Soil and

sediments

Macrophytes

and microbes

NH3 Ammonia volatilization – forms gaseous NH3 (Vymazal 2007)

Plant assimilation or uptake (Sun et al. 2005)

Microbiota assimilation (Imfeld et al. 2009)

Adsorption in soil/sediment (Cui et al. 2010)

Nitrification (autotrophic) – forms NO2, N2O and NO3

Nitrification (heterotrophic) – forms NO2, N2O and NO3 (Reddy

et al. 1984)

Cation exchange (Cui et al. 2010)

Partial nitrification denitrification – forms NO2 (Jianlong &

Ning 2004; Jianlong & Jing 2005)

ANAMMOX – forms N2

CANON – forms N2 and NO3 (Third et al. 2001)

Dilution (Kim et al. 2005; Kim et al. 2007)

Leaching to groundwater (Harper 1988)

Physicochemical

Biological

Microbiological

Physicochemicalb

Microbiological

Microbiological

Microbiological

Physicochemicalb

Microbiological

Microbiological

Physical

Physical

Discharge

or transfer

to CW’s

water as

NH3, N2O,

NO3, NOx,

DON, N2,

TKN, TN

Transport

to/from

groundwater

through

porous media

of CW as

NH3, NO2,

NO3, NOx,

DON, TKN,

TN

Emission

through

diffusion,

transportation

via/by

macrophytes,

ebullition as

NH3, N2O, N2,

NO2

Adsorption,

cation

exchange by

CW’s soil

and sediment,

or store in

soil pore

space as

NH3, NO3,

N2O, DON,

TKN, TN

Adsorption

(or storage)

by plant

surface and

microbial

assemblage

and/or

forming

biofilm as

NH3, NO3,

TKN, TN

NO2,

NO3 or

NOx

Plant assimilation or uptake

Nitrification – forms NO3 and N2O

Denitrification – forms NO2, N2O and N2 (Bachand & Horne

1999)

Dissimilatory nitrate reduction – forms NH3 (Dong & Sun

2007)

ANAMMOX – forms N2 (Van Dongen et al. 2001)

Dilution (Kim et al. 2005; Kim et al. 2007)

Leaching to groundwater (Harper 1988)

Biologicala

Microbiological

Microbiological

Microbiological

Microbiological

Physical

Physical

DON

Ammonification – forms NH3 (Savant et al. 1982)

Oxidation – forms NO2 and N2O

Burial – buried in soil and forms peat (Vymazal 2007)

Dilution (Kim et al. 2005; Kim et al. 2007)

Leaching to groundwater (Harper 1988)

Microbiological

Microbiological

Physicochemical

Physical

Physical

TN, PN Adsorption in soil or sediment (Cui et al. 2010)

Dilution (Kim et al. 2005; Kim et al. 2007)

Physicochemicalb

Physical

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Nutrient

Transformation route within CW

Transformation

mode

Output of nutrients in different compartments in close vicinity of CW

Surface

water

Groundwater Atmosphere Soil and

sediments

Macrophytes

and microbes

DOP,

FRP ,

PP.

TP

Adsorption in soil or sediment (Cui et al. 2010)

Dilution (Kim et al. 2005; Kim et al. 2007)

Leaching to groundwater (Harper 1988)

Settlement and accretion (Richardson 1985).

Precipitation – forms amorphous solid

Soil adsorption (Reddy et al. 1999)

Plant uptake or assimilation (Vymazal 2013a)

Microbiota assimilation

Microbiota assimilation/biofilm growth (Gächter & Meyer

1993)

Volatilization – forms PH3 (Bavor & Adcock 1994)

Litter/peat accretion (Bavor & Adcock 1994)

Physicochemicalb

Physical

Physical

Physical

Chemical

Physical

Biologicala

Microbiological

Microbiological

Physicochemical

Physicochemical

Discharge

or transfer

to CW’s

water as

FRP, TP

Transport to

groundwater

through via

media of CW

as FRP, TP

Emission

through

diffusion,

volatilization

of decomposed

material as

PH3

Adsorption,

settling and

peat

formation as

FRP, TP

Adsorption

by plant

surface and

microbial

assemblage

and/or

biofilm as

FRP, TP

DOC,

DIC,

TDC

Aerobic degradation – form CO2, NH3

Anaerobic degradation (Vymazal & Kröpfelová 2009; Saeed &

Sun 2012)

Sorption and sedimentation

Phytoaccumulation and phytodegradation (Imfeld et al. 2009)

Microbial degradation (Imfeld et al. 2009)

Microbiological

Microbiological

Physical

Biological

Microbiological

Discharge

or transfer

to CW’s

water as

DOC, DIC,

TDC

Transport to

groundwater

as DOC,

DIC, TDC

Emission as

CO2, CH4

Settling and

peat

formation as

DOC, DIC

Uptake or

degradation

by microbes

as CO2, CH4,

Modified after Vymazal (2007); Saeed & Sun (2012); Jahangir et al. (2016) aPermanent removal bin presence of filter media

FFM: Floating macrophytes

HSSF: Horizontal subsurface flow

VSSF: Vertical subsurface flow

CH4: Methane

PH3: Phosphine gas

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Table 2. 4 Attenuation of nutrients and physicochemical parameters from urban stormwater runoff from some site-specific investigations.

Nutrients Location CW type Attenuation efficiency References

Urban stormwater

runoff

P, SS Tampa, Florida,

USA

SF 90% TP, 94% SS Rushton et al. (1995)

Urban stormwater

runoff

P Washington, USA SF 82% TP Reinelt & Horner (1995)

Residential

stormwater runoff

P, N, SS Manassas, Virginia,

USA

SF 54.7% NH3, 25.5% TKN, 39.4% NOx, 21.7% TN,

57.9% TSS, 35.8% DOP, 45.9% TP

Carleton et al. (2000)

Nursery runoff P, N New South Wales,

Australia

SF 84% TN, 65% TP Headley et al. (2001)

Urban stormwater

runoff

P Henely Brook

Perth, Western

Australia, Australia

SF 5% P in 1st year, 10% P in 2

nd year Lund et al. (2001)

Nursery runoff N Nimes, France SF 70% NOx Merlin et al. (2002)

Residential

stormwater runoff

P, N, SS Port Jackson,

Sydney, Australia

SF 12% TP, 16% TN, 9% TKN, 9-46% TSS Birch et al. (2004)

Urban stormwater

runoff

N, P Crum Woods,

Swarthmore

College,

Pennsylvania, USA

SF 26% NOx, 59% FRP Bangs (2007)

Urban stormwater

runoff

(gully pot, liquor)

N University of

Edinburgh,

Scotland

SF 78.7% NH3 in 1st year, 95.8% NH3 in 2

nd year, 93.7%

NO3 in 1st year, 95.5% NO3 in 2

nd year

Lee & Scholz (2007)

Combined

stormwater urban

& agricultural

runoff

N, P Putrajaya wetlands,

Malaysia

Hybrid 82.1% TN, 84.3% TP Sim et al. (2008)

Highway runoff SS, N, P Island of Crete,

Greece

Hybrid 89% TSS, 49% TN, 60% TP

Terzakis et al. (2008)

Combined

stormwater urban

(14%) agricultural

(40%), forested

land (33%)

N, P Seokmoon,

Choongnam, South

Korea

SF 51.5% and 31.7% TN during growing and winter

season, respectively 50.6% and 53.0% TP during

growing and winter season, respectively

Ham et al. (2010)

Combined

wastewater runoff

and urban

stormwater runoff

N, P Danshui River

Basin, Taipei,

Taiwan

SF 78% NH3, 49% TP Ko et al. (2010)

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Nutrients Location CW type Attenuation efficiency References

Simulated

stormwater runoff

N, P Clemson, USA SF 87.9% N in 1st year and 66.9% N in 2

nd year, 80.9% P

in 1st year and 58.6% P in 2

nd year

White & Cousins (2013)

Watershed

stormwater

P Atlantic Coastal

Ridge, FL, USA

Hybrid 27% P Cohen & Brown (2007)

Urban stormwater

runoff

NO3,

NH3,

FRP

Lake Jackson, FL,

USA

SF 67 % NO3, 87%, NH3, 62% FRP Johengen & LaRock (1993)

Wastewater

treatment

TSS,

NH3,

TN, FRP

The Universitat

Politècnica de

Catalunya-

Barcelona Tech,

Spain

SF 97% TSS, 94% NH3, 46% TN and 4% FRP Ávila et al. (2013)

Tertiary treated

urban wastewaters

P, NH3,

TN

Spain Hybrid 77.0% P, 95.0% NH3, 24.4% TN Martín et al. (2013)

Conservation of

the Ganga river

TSS,

TDS,

NO3,

FRP,

NH3,

Shantikunj,

Haridwar, India

SSF 65% TSS, 78% TDS, 84% NO3, 76% FRP and 86%

NH3

Rai et al. (2013)

Ameliorating

diffused nutrient

loadings

N, P Gundowring,

Wodonga, Victoria,

Australia

SF 10 kg N yr−1

(23 g N m−2

yr−1

) and 1.24 kg P yr−1

(2.80

g P m−2

yr−1

)

Raisin et al. (1997)

TDS: Total dissolved solid

TSS: Total suspended solid

SS: suspended solid

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2.5.2 Filter media as an effective nutrient sink

Different unconventional substrates, industrial by-products, as well as natural

and artificial materials can be used as CW filter media to enhance nutrient attenuation

by CE, adsorption, precipitation and complexation (Saeed & Sun 2012; Wu et al.

2015). Frequently used filter media include organic wood mulch, rice husks, gravel,

sand, clay, laterite, peat, alum sludge, calcite, marble, vermiculite, slag, fly ash,

bentonite, dolomite, limestone, shell, zeolite, wollastonite, activated carbon, light

weight aggregates, compost and (Van de Moortel et al. 2009; Malaviya & Singh 2012;

Saeed & Sun 2012). The presence of filter media in CWs is beneficial as it performs

multiple tasks such as (a) providing active sites for nutrient adsorption (Wood &

McAtamney 1996), (b) promote diffusion of oxygen into the substrate for nutrient

processing (if a porous substrate like compost is used) (Aslam et al. 2007), (c)

generate anaerobic conditions for denitrification (if a non-porous substrate used) )

(Gray et al. 2000), (d) provide suitable conditions for ion exchange (Cui et al. 2010),

(e) provide aeration in the filter bed (Białowiec et al. 2011), (f) support biofilm for

nutrient processing (Bourgues & Hart 2007) and (g) leach C (e.g., from organic wood

mulch) for denitrification (Saeed & Sun 2011). These filter media may have limited

interaction with solar radiation and the atmosphere, therefore encouraging anoxic

conditions. The performance of filter media in the field level CWs are subject to

further study. Furthermore, any release of nutrients from filter media can make

nutrient attenuation estimation challenging. The relative contribution of filter media in

the different compartments of a CW also needs to be assessed.

Some filter media can be dried out due to lack of stormevent during the

summer in semi-arid area where rainfall during summer is near zero. Therefore, filter

media can be dried out and microbial community can be stressed. It is therefore

necessary to estimate the function of such filter media in stormwater nutrient

attenuation after prolong dry periods. Furthermore, episodic pulses of storm events

can flood filter media and nutrient dynamics in such condition need to be understood.

2.5.3 Nutrient attenuation variability during flow dynamics

CWs designed for treating wastewater receive a relatively control rate of

inflowing water (Jahangir et al. 2016), However, CWs designed for stormwater

treatment typically experience highly variable inflow depending on hydro-

meteorology. Therefore, nutrient attenuation varies widely depending on the ratio of

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CW volume to inflow rate, inflow water volume, respective HRT and ADD.

Furthermore, CWs in semi-arid areas experience prolonged summer dry periods with

low to near zero flows, yet it is unclear how antecedent dry or wet conditions impact

on performance.

CWs frequently receive water from ungauged inflows including groundwater.

It is challenging to consider multiple and ungauged sources of water and nutrient

during CW efficiency estimation. HRT is usually higher during the dry periods

compared to the wet periods. Longer HRT increases the water contact time with

aquatic macrophytes and benthos, and subsequently facilitates nutrient attenuation

(Kadlec & Knight 1996). However, it is not clear how CW response to nutrient

processing under anoxic conditions is impacted by low flows and higher HRT. It is

also not clear how an open water or SF CW respond to such abrupt flow variability.

CWs can use recirculation system to keep a system functional over the dry season.

However, such recirculation can influence water balance and nutrient dynamics that

needed to be estimated.

The intense rainfall experienced in Mediterranean climates during the wet

winter can import high nutrient loads into CWs and therefore, event mean

concentration (EMC) changes with season. However, it is challenging to estimate how

CWs respond to these changing nutrient loads after and between storms. Episodic

storm events along with groundwater seepage can flood the riparian zones of CWs.

The riparian zones are CW ecotones where intense biogeochemical processing of

nutrients takes place. However, the response of CW riparian zones under seasonal

saturation and drying dynamics over is complex and requires further study.

Water levels in Mediterranean CWs can become very low (sometimes less

than 0.3 m) and therefore the water in the system can become stagnant. Ultimately, the

change in flow and associated water level convert the system into a lotic environment.

However, the same CW receives water from episodic stormwater early in the winter

and transitions back to a lotic environment. Sometimes groundwater inputs can also

contribute to the lotic state of the CWs. The significance of periodic lentic-lotic

transitions for nutrient dynamics remains unknown. The re-saturation of previously

exposed riparian soils during transitions to lotic conditions can also impact nutrient

attenuation or release to receiving waters, however, to date this scenario has not been

investigated within the context of stormwater treating CWs.

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2.5.4 Role of macrophyte growth and decay in wetland performance

Macrophytes can accumulate nutrients in their above ground biomass (AGB)

i.e., leaves and shoots and below ground biomass (BGB) i.e., roots and rhizospheres,

and therefore attention is higher in vegetated CWs than non-vegetated CWs (Vymazal

2011; Vymazal 2013a, b). However, nutrient uptake by macrophytes depends on the

type of macrophytes present (emergent, rooted and floating), species diversity (one

species or multiple), the planted form (individual or combined), growth stage (early or

mature stage) and stormwater flow conditions in the CWs. Different macrophyte

groups or species may interact and compete for nutrient uptake, nutrient uptake can

vary when species coverage or species type changes across the CW and therefore

optimization of macrophyte establishment needs to be considered. The time required

for CW macrophyte biomass to reach equilibrium conditions and how nutrient uptake

changes over this time, is still need further investigation. It is challenging to assess all

these aspects of macrophyte dynamics because of inter-specific completion of

macrophytes for nutrients, spatial heterogeneity in macrophytes biomass and its

seasonal dynamics.

Another challenge is macrophyte senescence on nutrient uptake dynamics

(Figure 2. 3). Macrophytes can exhibit seasonal senescence that can release stored

nutrients back to the CW (Brodrick et al. 1988; Kröger et al. 2007), and therefore,

mature macrophytes need periodic harvesting (Greenway 2005; Malaviya & Singh

2012; Vymazal 2013a). Furthermore, dead macrophytes can accumulate in the open

water during low flow conditions, hindering light penetration into the water column

and changing the DO dynamics. Therefore, the impact of seasonal macrophytes

senescence on the overall nutrient dynamics needs to be better understood.

2.5.5 Does the overall ‘metabolism’ of wetlands impact their attenuation ability

Wetland metabolism can be defined as the difference in the rate of C input and

output. If a wetland accumulates C (input > output, net autotrophic), then the

metabolism is characterised as positive. When a wetland releases more C than it is

retaining (i.e., net heterotrophic) then the metabolism is considered negative (Tuttle et

al. 2008; Coletti et al. 2013). Overall aquatic metabolism is the balance between

productivity or processes that produce oxygen (such as photosynthesis) and processes

that consume oxygen (such as respiration). The total metabolic balance of an

ecosystem is also known as the net ecosystem production (NEP), which is defined as

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the difference between gross primary production (GPP) and ecosystem respiration (R)

or community respiration (CR) (Lovett et al. 2006). NEP reflects the balance between

all anabolic and catabolic processes. When NEP is positive (net autotrophic), fixation

of inorganic C through photosynthesis exceeds oxidation of organic C. Alternatively,

when NEP is negative (net heterotrophic), the re-mineralisation of organic C exceeds

the fixation of inorganic C (Lovett et al. 2006; Dodds & Cole 2007; Staehr et al.

2012b). Researchers have used DO, CO2 and isotopes as key variables to determine

metabolism in aquatic environments including lake, estuary, river and ocean (Staehr et

al. 2010; Staehr et al. 2012a). DO variability in CWs under different flow regimes,

across both short and long time-scales, is still poorly understood. Usually DO levels in

a CW are monitored during the daytime and therefore, it is important to understand

how DO changes over the diurnal cycle. It is challenging to estimate metabolism in

stormwater CWs as these systems are dynamic and complex from both hydrological

and biogeochemical perspectives. A few studies have measured DO dynamics in

CWs, monitoring GPP and R (and therefore metabolism) as an indicator of wetland

function (Cronk & Mitsch 1994a; Tuttle et al. 2008; Reeder 2011). However, in these

studies DO was monitored over a relatively short timescale, from several days to a

week, and a lake metabolism definition was used. As discussed above, during the dry

summer CWs can transition to lentic systems (under these conditions the lake

metabolism definition is appropriate). However, early in the wet winter, storm event

pulses or frequent rainfall can shift the CW to a lotic system. These lentic-lotic

transitions make it complex to estimate metabolism in the CWs in Mediterranean

climates. Also, phytoplankton are typically the main primary producers in lakes, while

dense aquatic macrophytes are typically the main primary producers in CWs. The

different seasonal dynamics of these two types of primary producers have distinct

influences on metabolism. The summer macrophyte senescence experienced in

Mediterranean climates can input significant C loadings to the CWs at a time of very

long HRT and high temperatures leading to higher rates of oxygen consumption

indicating as biological oxygen demand (BOD), chemical oxygen demand (COD) and

sediment oxygen demand (SOD). Moreover, water levels can decrease during summer

lentic conditions, due to high evaporative demand. Thus the Mediterranean climate

imposes a strong signature on the wetland metabolism because the wetland carbon

budget is influenced by both vegetation mortality (Stephens 2005) and changes in

hydrology (Reddy & DeLaune 2008; Tuttle et al. 2008; Page & Dalal 2011). Changes

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29

in DO concentrations, taken over appropriate time and length scales, may be a simple

but useful indicator of wetland metabolism that can be used under both lentic and lotic

conditions, however further work is needed to investigate how this indicator impacts

on nutrient attenuation under different hydrological regimes.

Figure 2. 3 Schematic representation of the main phase of above ground biomass of

macrophytes including leaf expansion, maturity and senescence. Leaf maturity begins hen leaf

expansion is over and ends with the first senescence symptoms. During the maturity phase, the

leaf faces numerous sub-lethal events leading to many chronic senescence syndromes and

recovery events. Leaf-senescence no-return syndrome is characterized by a succession of

degradation process that will lead to death. The figure is modified after Guiboileau et al.

(2010).

2.5.6 Effectiveness of CW restoration to improve nutrient attenuation

CWs attenuate nutrients effectively in the first couple of years after the

construction; however this effectiveness can decrease over time due to periodic

accumulation of nutrients and organic matter in the sediments (Craft 1996; Hancock

2002), degradation of the riparian zones and alteration of water flow path (Harrison et

al. 2012), diffusion and resuspension of nutrients from the sediments (O'Brien et al.

2012), senescence of plant material that then releases nutrients to the system (Kröger

et al. 2007), development of anoxic environments and input of polluted groundwater

(Gabriele et al. 2013; Teufl et al. 2013). In the long term, CW can be a source of

nutrients, and therefore CW restoration is a key management intervention to maintain

nutrient attenuation (Jenkins & Greenway 2007). This restoration effort may include

modification of the CW main channel (Seitzinger et al. 2002), changes in water flow

paths (Craig et al. 2008), introduction of obstacles to influence flow direction

(Groffman et al. 2005), modifications to increases the water contact with hyporheic

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30

zone, benthos and macrophytes (Craig et al. 2008; Hester et al. 2009; Gordon et al.

2013), provision of environments with available carbon sources (Bernhardt & Likens

2002) and the creation of denitrification hotspots (Craig et al. 2008). However, how

these restoration efforts impact on the attenuation of different nutrient species is

poorly understood. There is also little clarity on how long such restoration features

continue to improve nutrient attenuation and whether they remain effective under

highly variable hydrological and biogeochemical conditions. An assessment of the

impact of CW restoration nutrient attenuation, and how that changes with time is

needed.

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Nutrient attenuation in a surface flow

constructed wetland experiencing summer low

flow and macrophyte senescence

This chapter is based on the manuscript published as: T. M. Adyel, M. R. Hipsey and

C. E. Oldham (2017) Temporal dynamics of stormwater nutrient attenuation of an

urban constructed wetland experiencing summer low flows and macrophytes

senescence. Ecological Engineering, 102, 641-661.

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Abstract

The attenuation of urban stormwater nutrient is essential for maintaining

ecological health of downstream waterways. Constructed wetlands (CWs) are widely

used for stormwater management due to the economic and environmental benefits

they create by attenuating nutrients. This research assessed stormwater nutrient

attenuation in a surface flow CW located in Western Australia, by assessing data

spanning decadal, seasonal and diurnal time-scales. The study site was built in 2004

and restored in 2010, and the significance of such restoration was also assessed in this

research. The CW designed to minimize nutrient loads to downstream sensitive

waterways despite experiencing Mediterranean climates with strong hydrological

seasonality including prolonged low or no flow conditions during the dry summer

periods and nutrient-rich pulses during the wet winter periods. Furthermore, seasonal

ungauged water inputs and macrophytes senescence made the system complex to

optimize nutrient attenuation. The annual average attenuation of nitrogen (N) and

phosphorus (P) based nutrients were 2–4 times higher during the post-restoration

periods than that observed during the pre-restoration periods. The attenuation of

inorganic, organic, dissolved and total N was higher during the dry periods of the

post-restoration regimes, while P species showed higher attenuation during the wet

periods of the post-restoration regimes. Inorganic N showed greater attenuation than

attenuation of inorganic P throughout the year. Baumea articulata and Schoenoplectus

validus were the dominant macrophyte species across the site; B. articulata was

estimated to store about 3 and 2 times higher N and P pools, respectively than that

stored in S. validus. Low dissolved oxygen (DO) occurred in the site and DO showed

a decreasing trend over the decade and a distinct diurnal signature of day-time peaks

and night-time anoxia. Diurnal pattern in aquatic metabolism, defined as the daily

fluctuation of DO levels within the water column of CW, was related to solar radiation

and nutrient concentrations, and could be considered as a proxy of CW function.

Keywords

Dissolved oxygen; Macrophytes senescence; Nutrient attenuation; Stormwater;

Water Sensitive Urban Design; Wetland restoration

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3.1 Introduction

Water quality is declining in many urban areas due to non-point source

nutrients, typically delivered via stormwater (Roy et al. 2008; Wong et al. 2012),

leading to nuisance algal blooms and eutrophication in downstream waterways

(Taylor et al. 2004; Hathaway et al. 2012). Stormwater and/or associated nutrient can

also lead to habitat fragmentation, biodiversity loss and changes in the morphological

and hydrological characteristics of the watercourses (Taylor et al. 2004; Walsh et al.

2005a; Francey et al. 2010; Zgheib et al. 2012). As a result, management of

stormwater quality has become an essential strategy to improve ecological integrity of

drainage systems, and as a means to improve urban sustainability and liveability (Hatt

et al. 2007; Wong et al. 2012; Deletic et al. 2013).

A paradigm shift in stormwater management has therefore been taking place in

many cities around the world based on Integrated Stormwater Management System

(ISWMS) and through adoption of Best Management Practices (BMPs). Such

initiatives have been referred as Low Impact Development (LID) in the USA (Hinman

2005), Sustainable Urban Drainage Systems (SUDS) in the UK (CIRIA 2000) and

Water Sensitive Urban Design (WSUD) in Australia (Lloyd 2001). In general, WSUD

are based on the idea that the management, protection and conservation of the urban

water cycle must take place to ensure that the urban water environment is sensitive to

natural hydrological, economic and ecological processes (Deletic et al. 2013), and that

the ecological services of urban waterways are maintained (Wong & Brown 2009).

There are different WSUD elements are in practice for stormwater nutrient

attenuation, and constructed wetland (CW) is one of them.

CWs have found widespread adoption over the past few decades due to their

ability to treat and transform stormwater nutrient by utilizing different hydrological

and biogeochemical processes. These processes take place within the water,

soils/sediments, aquatic macrophytes and microbial assemblages of CWs (Carleton et

al. 2000; Carleton et al. 2001; Kivaisi 2001; Mitsch & Gosselink 2007; Vymazal

2007). CWs vary widely in their performance ranging from 10 to 90% for nitrogen

(N) and phosphorus (P), and in some cases they may increase nutrient levels (Rushton

et al. 1995; Saeed & Sun 2012). The performance depends on numerous factors

including the area and land use of the catchment, nutrient loading rate, hydro-

climatological variability, macrophyte biomass, hydraulic retention time (HRT),

groundwater connectivity and specific sediment/soil properties (Hamilton et al. 1993;

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Carleton et al. 2001; Gasperi et al. 2011; Zgheib et al. 2011; Zgheib et al. 2012; Tang

et al. 2013). The degree of nutrient attenuation in CWs is controlled

biogeochemically and/or hydrologically (Fink & Mitsch 2007; Huang et al. 2011;

Chang et al. 2013; Jahangir et al. 2016). N and P of stormwater experience different

transformations depending on the CW’s biogeochemical conditions. These conditions

include oxygen concentrations, availability of a carbon (C) source, macrophytes and

microorganism abundance, soil/sediment properties and degree catchment-riparian-

hyporheic exchange (Kadlec & Knight 1996). For example, a lack of oxygen

suppresses nitrification, and triggers denitrification and dissimilatory reduction of

nitrate to ammonia (DNRA) (Harrison et al. 2012). The degree to which

biogeochemical processing of nutrients can occur, however, is highly dependent on

hydrological conditions within the water and groundwater regions of the CW. Higher

HRT increases the water contact with aquatic macrophytes and benthos, and usually

facilitates nutrient attenuation (Kadlec & Knight 1996). Furthermore, riparian zone

saturation exports nutrients to the overlying water column (Ranalli & Macalady 2010).

Increased flow velocities after the storm events flush senescent and floating biomass

from the system, thereby promoting aquatic productivity through the improved light

availability and higher temperature within the water column (Tuttle et al. 2008).

However, water is unevenly distributed in the CW because of channelization,

microtopography and spatial patterns within macrophyte beds (Kadlec & Knight

1996), and hence different parts of the CW can function differently (Fink & Mitsch

2007). These variabilities complicate the optimisation of the CW design and function;

in particular the function of CWs in the Mediterranean climates is less clear. The

effects of prolonged low flows and senescence of macrophytes during the summer

periods on the CW function in the Mediterranean climates are not well understood.

Furthermore, the performance of CW also varies over time that makes it complex for

system optimisation.

In the first few years after the construction, CWs function most effectively

predominantly due to available sites for absorbing nutrients (Omari et al. 2003;

Malaviya & Singh 2012), the settling of particulate nutrients within the system (Reddy

et al. 1999; Kadlec & Wallace 2009), higher nutrient accumulation by macrophytes in

their growth phase (Mustafa et al. 2009; Vymazal 2013a), intense hyporheic exchange

(Ranalli & Macalady 2010), and high photic depth and oxygen availability within the

water column (Stein & Paul 2005). The effectiveness of CWs can decrease with time

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due to senescence and accumulation of plant material that subsequently releases

nutrients back to the system (Kröger et al. 2007), accumulation of nutrients and

organic matter in the sediments (Craft 1996; Hancock 2002), degradation of the

riparian zones and development of preferential flow paths (Harrison et al. 2012),

diffusion and bioturbation of nutrients from the sediments (O'Brien et al. 2012),

development of anoxic environments and the input of polluted groundwater (Gabriele

et al. 2013; Teufl et al. 2013). Therefore, in the long term CWs can become a source

of nutrients and may require periodic restoration. However, predicting the optimum

time for CW restoration is challenging.

CWs restoration is undertaken to re-establish the ecological functions of both

biotic and abiotic components (Fernández & Novo 2007), thereby improving nutrient

attenuation (Bukaveckas 2007; Craig et al. 2008; Gabriele et al. 2013). Physical

restoration can involve the modification of stream channels (Seitzinger et al. 2002),

changes in water flow paths (Craig et al. 2008), earthworks in the riparian zones

(Craig et al. 2008), introduction of artificial woody debris or dams to influence flow

direction (Groffman et al. 2005) and incorporation of permeable layer of engineered

materials or substrates (Saeed & Sun 2012). Restoration can also include the re-

establishment of macrophytes and routine harvesting of mature macrophytes (Brown

2000; Vymazal 2013a), modifications to increase the water contact between hyporheic

zone, benthos and macrophytes (Craig et al. 2008; Hester et al. 2009; Gordon et al.

2013), provision of environments with available C sources (Bernhardt & Likens 2002)

and the creation of denitrification hotspots (Craig et al. 2008). However, in the

Mediterranean climate, CWs experience prolonged periods of no or low surface flows

during the summer, episodic high flows after storm events and possible groundwater

input during the winter. Moreover, senescent macrophytes can release organic matter

during the period when temperatures are high and CWs dry out that ultimately leads to

anoxic conditions. Therefore, major feedbacks between hydrological and/or

biogeochemical processes need to be identified for optimal restoration and subsequent

nutrient attenuation.

In the present study, we assessed the nutrient attenuation in a surface flow CW

situated on the Swan Coastal Plain (SCP) of Western Australia (WA). The studied

CW experiences Mediterranean climates with prolonged periods of no to low flows

and macrophytes senescence, particularly during the summer periods. In dry periods

local groundwater can contribute flow within the CW. During the wet periods,

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stormwater runoff from residential, commercial and industrial sites is collected by

surface and subsurface drainage system and discharged to the CW. We explored

dynamics of nutrient attenuation over diurnal, seasonal and decadal time-scales

through synthesis of historical meteorological data, water quality and quantity data,

sediment and macrophyte quality data, and high frequency dissolved oxygen (DO)

data. Our analysis adopted a whole-system approach to investigate the influence of

restoration, seasonal prolonged low flows, episodic flows and macrophyte senescence

on the overall nutrient dynamics. The results also highlighted the variability in CW

function, and demonstrate the importance of changes in CW metabolism regarding

nutrient dynamics.

3.2 Materials and methods

3.2.1 Site background and restoration works

The study focused on the Anvil Way Compensation Basin (AWCB), situated

in the Mills Street Main Drain (MSMD) sub-catchment of WA (Figure 3. 1). MSMD

drains stormwater from a 120 ha residential and light industrial area with high density

traffic ways. The AWCB was initially built in 2004 as a drainage compensating basin

to retain small amount of stormwater and reduce the export of stormwater pollutant to

the Canning River. The basin was restored to a “living stream” in November 2010.

The restoration efforts included the removal of approximately 1400 m3 metal- and

hydrocarbon-containing sediments, the introduction of a sedimentation pond close to

the main inlet to trap particulate material and the creation of a meander through the

basin to increase water contact with the wetland macrophytes and benthos during low

flow conditions. Macrophytes were also planted at benches or riparian zones to

encourage sedimentation and nutrient removal and three low sand bars were

introduced to reduce risk of short-circuiting of the flow between the inlet and outlet.

The AWCB is now roughly triangular shaped and 0.9 ha in area.

3.2.2 Data collection

3.2.2.1 Meteorology

Solar radiation data (August 2014 to August 2015) was obtained from the

weather station of the Department of Agriculture and Food (DAFWA), South Perth,

located approximately 5 km north-west of the AWCB. Daily rainfall data (January

2011 to August 2015) was obtained from the Welshpool depot of the Department of

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Water (DoW) and the Perth Airport Station of the Bureau of Meteorology (BoM).

These stations are approximately 0.8 km north-west and 5 km north-south of the

AWCB, respectively.

3.2.2.2 Water quantity

5-min intervals water discharge and level data at the AWCB inflow and

outflow stations were obtained from DoW. A Starflow ultrasonic instrument

(UnidataTM, Australia) at the inflow and a float well sensor at the outflow were used.

Inflow and outflow data were only available since 2009 and 2012, respectively. The

water levels of four groundwater bores (G1, G2, G3 and G4) were also logged by

DoW. Bores G1to G3 and G4 began operation in April 2010 and January 2012,

respectively. Bore covers were trafficable and flush with the ground surface.

Groundwater levels were monitored on a monthly basis and depth from top of the

casing was converted to Australian Height Datum (AHD).

3.2.2.3 Water quality

Historical unfiltered and filtered water samples at fortnightly or monthly

(September 2004 to May 2015) intervals were collected from the main inlet (W1),

Mars Street Drain or MSD (W2) and main outlet (W3) by DoW. We also collected

opportunistic (November 2013 to May 2015) and pre-storm event (12 to 13 March

2015) water samples at three sites i.e., W1, W2 and W3 (Table 3. 1). Pre-storm event

samples were collected at about 2-h intervals spanning day and night regimes. Water

samples were filtered on-site using 0.45 μm membrane filter, stored on ice until the

returning to the laboratory, and then frozen until analysis. Historical water samples

were analysed for filtered ammonia (NH3), filtered total oxidised nitrogen (NOx), total

Kjeldahl nitrogen (TKN), unfiltered total nitrogen (TN), filtered reactive phosphorus

(FRP) and unfiltered total phosphorus (TP) using standard method (APHA 1998).

Historical quarterly water samples were also collected and analysed for dissolved

organic nitrogen (DON). Opportunistic and pre-storm event samples were analysed

for NH3, filtered nitrite (NO2), filtered urea nitrogen (UreaN), filtered total nitrogen

(FTN), TN, FRP, filtered total phosphorus (FTP), TP, dissolved organic carbon

(DOC) and dissolved inorganic carbon (DIC) using Lachat Quick Chem procedure

(APHA 2012). We calculated other nutrient parameters based on analysis results of

opportunistic and pre-storm event samples (Table 3. 1).

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Figure 3. 1 Map of the Anvil Way Compensation Basin showing monitoring and sampling

points. Sampling points include surface water (W1, W2 and W3), groundwater (G1, G2, G3

and G4), sediment (S1, S2, S3 and S4) and macrophyte (M1, M2, M3 and M4). Stormwater

enters to the system at the main inlet (W1) and Mars Street Drain (W2), and exits at the main

outlet (W3) into the Canning River. The AWCB is mainly dominated by B. articulata and S.

validus. P1, P2 and P3 indicate the porewater monitoring points at a transect within riparian

zone.

Canning River

DO logger

P3

P2

P1

Transect

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During the historical water sampling, in situ DO concentrations were also

recorded at three sites by DoW. During opportunistic and pre-storm sampling, we also

measured DO concentrations in the main stream water at 10-min intervals using a

miniDOT DO logger (PMA, USA) from July 2014 to May 2015. An additional DO

logger (D-opto, New Zealand) was also installed at W3 to capture DO signals at 10-

min intervals during the pre-storm event.

DoW collected and analysed groundwater samples for NH3, NOx, TKN, TN,

FRP and TP using standard method (APHA 1998). Groundwater samples were also

monitored for DO concentrations using in situ logger (Table 3. 1).

3.2.2.4 Sediment quality

DoW collected sediment samples from November 2011 to May 2015 on about

half yearly at in-stream sites i.e., at inlet (S1) and outlet (S4), and two bench sites i.e.,

S2 and S3 (Figure 3. 1) Average sediment sampling depth was about 10–15 cm.

Sediments were analysed for TKN, TP and total organic carbon (TOC). Details

sampling and analysis procedure are described elsewhere (GHD 2008).

Soil/sediment oxidation-reduction potential (Eh) and porewater nutrient

concentrations were monitored at three points (P1, P2 and P3) over a 2 m transect

extending from the water's edge to the riparian zone (Table 3. 1). P1, P2 and P3 were

approximately 60, 40 and 20 cm below the soil surface and each point was

horizontally separated by 50 cm. Three Eh sensors (Sensorex, USA) were inserted

vertically into these points and connected to a data logger (DaqPro, USA) recording at

30-min intervals. One suction cup (UTM, Germany) was also placed at each

porewater monitoring point (same depth of Eh sensors) with the other end attached to

sampling bottle of 500 mL capacity. The suction cups periodically collected water

samples from soil porewater and stored them in the sampling bottles for later analysis

(Table 3. 1).

A perforated PVC pipe was inserted up to 30 cm from soil surface in the

transect. A CTD (conductivity, temperature and depth) diver (Schlumberger,

Germany) was placed at the bottom of the pipe to measure water level/pressure. The

CTD pressure changes were compared with an on-site atmospheric baro diver (Onset

HOBO, USA). Electric conductivity (EC) and temperature were monitored at 10-min

intervals.

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Table 3. 1 Summary table of spatial and temporal dynamics of studied nutrient parameters,

data type, sampling frequency and data source for the Anvil Way Compensation Basin

assessment.

Component Unit Nutrient Data type Sampling

sites

Duration Sampling

frequency

Analytical

method

Data

source

Surface

water quality

mg/L NH3, NOx,

TKN, TN,

FRP, TP

Historical W1, W2,

W3

September

2004 to

May 2015

Fortnightly

to monthly

APHA

(1998)

DoW

DON Quarterly

NH3, NOx,

NO2, NO3,

FTN, TN,

UreaN,

DIN, PN,

DON,

NUON,

FRP, FTP,

TP, PP,

DOP, DIC,

DOC, TDC

Opportunistic W1, W2,

W3

November

2013 to

May 2015

Fortnightly

to monthly

APHA

(2012)

This

study

NH3, NOx,

FNO2, NO3,

FTN, TN,

UreaN,

DIN, PN,

DON,

NUON,

FRP, FTP,

TP, PP,

DOP, DIC,

DOC, TDC

Pre-storm

event

W1, W2,

W3

12 to 13

March

2015

2–3-h

intervals

APHA

(2012)

This

study

Groundwater

quality

mg/L NH3, NOx,

TKN, TN,

FRP, TP

Historical G1, G2,

G3, G4

April

2010 to

May 2015

Monthly APHA

(1998)

DoW

Soil

porewater

quality

mg/L NH3, NOx,

NO2, NO3,

FTN, DIN,

DON,

NUON,

FRP, FTP,

DOP, DIC,

DOC,TDC

Opportunistic P1, P2, P3 11 to 17

March

2015

2–3-h

intervals

APHA

(2012)

This

study

Sediment

quality

mg/kg TKN or TN,

TP, TOC

Historical S1, S2,

S3, S4

November

2011 to

May 2015

Variable,

mainly half

yearly

GHD

(2008)

DoW

Macrophyte

quality

mg/kg TKN or TN,

TP

Historical M1, M2,

M3, M4

October

2012 to

October

2013

Variable,

mainly half

yearly

GHD

(2008)

DoW

Analysed nutrient species: NH3: Filtered ammonia; NOx: Filtered total oxidised nitrogen; NO2: Filtered nitrite; UreaN: Filtered urea nitrogen; FTN: Filtered total nitrogen; FRP: Filtered reactive phosphorus; FTP: Filtered total phosphorus; TN: Unfiltered

total nitrogen; TP: Unfiltered total phosphorus; DIC: Dissolved inorganic carbon; DOC: Dissolved organic carbon.

Calculated nutrient species: NO3: Filtered nitrate = NOx – NO2; DIN: Filtered inorganic nitrogen = NOx + NH3; PN: Particulate

nitrogen = TN – FTN; DON: Dissolved organic nitrogen = FTN – NH3 – NOx; NUON: Filtered non-urea organic

nitrogen = DON – UreaN; PP: Particulate phosphorus = TP – FTP; DOP: Filtered organic phosphorus = FTP – FRP; TDC: Total dissolved carbon = DIC + DOC.

3.2.2.5 Macrophyte properties

A natural resource management group, the South East Regional Centre for

Urban Landcare (SERCUL), WA planted the AWCB with Schoenoplectus validus,

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Baumea articulata, B. juncea, Juncus pallidus and J. kraussii after the restoration.

Recent (June 2012) ground-truthing of species coverage found S. validus and B.

articulata as dominant species. Macrophyte samples at four points (M1, M2, M3 and

M4) were collected using 0.0625 m2 quadrat on about half yearly from October 2012

to October 2013. Macrophyte samples were analysed for TKN and TP concentrations

in the above ground biomass (AGB) such as shoots and leaves, and below ground

biomass (BGB) such as roots and rhizosphere (GHD 2008).

Floating macrophytes, weeds, algal mats, debris or a combination of all

accumulated periodically in the AWCB main stream. Images of main stream coverage

by these floating materials between 1 August 2014 and 28 June 2015 were obtained

from the NearMap (Link: http:au.nearmap.com).

3.2.3 Data analysis

3.2.3.1 Nutrient attenuation

CW efficiency is typically calculated as the difference between the influent

and effluent nutrient loads. Nutrient concentrations and water flows need to be

monitored simultaneously at the inflow and outflow of CW to calculate the load.

Quantification of nutrient attenuation within the AWCB, however, was complicated

due to presence of ungauged inputs such as MSD (W2) and possible groundwater.

Furthermore, simultaneous flow data was available at the main inflow and outflow

from October 2012, and hence the calculation of nutrient load attenuation, and how it

changed over time, was not always possible. Therefore, an alternative approach, the

standardised delta concentration, SDC (%), was adopted for assessing nutrient

attenuation over time. The overall estimation of nutrient attenuation was performed in

two ways where scenario 1 considered SDC as standardised difference in nutrient

concentrations between the inlet and outlet (Adyel et al. 2016):

𝑆𝐷𝐶 =𝐶𝑖𝑛𝑙𝑒𝑡−𝐶𝑜𝑢𝑡𝑙𝑒𝑡

𝐶𝑖𝑛𝑙𝑒𝑡 × 100 (3.1)

where 𝐶𝑖𝑛𝑙𝑒𝑡 is nutrient concentration at the inlet (mg/L) and 𝐶𝑜𝑢𝑡𝑙𝑒𝑡 is nutrient

concentration at the outlet (mg/L).

From the water balance analysis, we expected that MSD and groundwater

inputs would contribute about 20–70% water depending on the time of the year and

available rainfall (Adyel et al. 2015a; Ruibal-Conti et al. 2015). Consequently,

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scenario 2 was used to estimate averaged SDC, SDC_ave (%) where inlet nutrient

concentration was the average concentration of W1 and W2:

𝑆𝐷𝐶_𝑎𝑣𝑒 =𝐶∗

𝑖𝑛𝑙𝑒𝑡−𝐶𝑜𝑢𝑡𝑙𝑒𝑡

𝐶∗𝑖𝑛𝑙𝑒𝑡

× 100 (3.2)

where 𝐶∗𝑖𝑛𝑙𝑒𝑡 is the average nutrient concentration of the main inlet (W1) and MSD

(W2) (mg/L) and 𝐶𝑜𝑢𝑡𝑙𝑒𝑡 is the nutrient concentration at the main outlet (W3) (mg/L).

Although this approach was not able to provide an exact value of CW

efficiency, it was able to: (a) provide a range of performance values for different

compounds of interest, (b) highlight the importance of the impact that ungauged

sources have on the assessment, and (c) demonstrate the relative differences in

performance over time. When simultaneous flow and nutrient data are available at

main inlet and outlet, we calculated incoming and outgoing nutrient load and

subsequently load attenuation, as:

𝐿 = 𝑄𝑖 × 𝐶𝑖 (3.3)

𝐿𝐴 =∑ 𝐿𝑖−∑ 𝐿𝑜

∑ 𝐿𝑖 × 100 (3.4)

where L is the nutrient load (mg/s), Qi is the flow rate at ith timestep (m3/s), Ci is the

nutrient concentration at ith timestep (mg/L), LA is nutrient load attenuation (%), Li is

the load at the inlet (mg/s) and Lo is the load at the outlet (mg/s).

3.2.3.2 Sediment nutrient mass and porewater properties

The mass of sediment nutrient (TKN or TN, TP and TOC) was calculated for the

bench and in-stream sites assuming that each of the sampling site was representative

of a specified area of the AWCB:

𝑁𝑀𝑠 = 𝑁𝐶𝑠 × 𝐵𝑠 × 𝐴𝑠 × 𝐷𝑠 (3.5)

where NMs is the sediment nutrient mass (kg), NCs is the sediment nutrient

concentration (mg/kg), Bs is the sediment bulk density (kg/m3), As is sediment area

(m2) and Ds is sediment depth (m).

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In addition, nutrient concentrations of riparian soil/sediment porewater were

analysed to assess nutrient variability due to riparian zones saturation (Table 3. 1).

3.2.3.3 Macrophytes nutrient mass and main stream coverage

S. validus was sampled at four macrophyte sampling sites on three sampling

regimes (October 2012, May 2013 and October 2013) while B. articulata was only

sampled at M1 and M2 on October 2012 and May 2013 due to minimal coverage at

M3 and M4. S. validus was opportunistic and quickly grew into any gaps, especially

in the areas where B. articulata was sampled, while B. articulata was long lived. TKN

and TP pools in AGB and BGB at four sampling points were estimated assuming each

of the sampling site was representative of a specified area of the AWCB:

𝑁𝑀𝑏 = 𝑁𝐶𝑏 × 𝐷𝑊𝑏 × 𝐴𝑏 × 𝑄𝑏 (3.6)

where NMb is the biomass nutrient mass (kg), NCb is biomass nutrient concentration,

DWb is dry weight of the biomass (kg), Ab is the biomass area (m2) and Qb is quadrat

area as 0.0625 m2.

NearMap images of the AWCB were digitized to estimate the main stream

coverage by floating material.

3.2.3.4 Hydrological assessment

Beside the main inflow, stormwater entered to the AWCB through MSD and

probably groundwater, particularly during the storm events and wet periods. The

water input from local sources and ungauged areas into the AWCB was calculated

considering rainfall pattern from June 2012 to December 2013. The volumetric

contribution for ungauged areas (VCUA) was computed by numerical integration of

the discharge hydrograph over the specified duration of the event (Chow et al. 1999).

Selected small rainfall events of short duration (e.g. pulses) were used to highlight the

contribution of local catchment areas to the AWCB. Large rainfall events (> 25 mm)

of long duration (∼24 h) or event hydrographs presenting peak discharges above the

0.6 m3/s value, were used to highlight the potential maximum volumetric contribution

and peak discharge values from ungauged areas (Ruibal-Conti et al. 2015).

The volume of the AWCB was calculated using a Digital Elevation Model

(DEM). Height and volume ratio relationship was obtained from site construction

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plan. HRT of the AWCB was established using the volume of the system and the

outflow rate:

𝐻𝑅𝑇 =𝑉𝑎

𝑄𝑜𝑢𝑡𝑙𝑒𝑡 (3.7)

where 𝑉a is volume of the AWCB (m3) and Qoutlet is the discharge rate at the outlet

(m3/s).

3.2.3.5 DO as a function of solar radiation

The DO logger at the mid-channel water recorded DO concentrations and

saturation at 10-min intervals. Based on available data, the delta DO saturation,

ΔDOsat (%) was calculated as a proxy of CW metabolism for each day according to:

∆𝐷𝑂𝑠𝑎𝑡 = 𝐷𝑂𝑚𝑎𝑥 − 𝐷𝑂𝑚𝑖𝑛 (3.8)

where DOmax is the maximum DO saturation at the afternoon (%) and DOmin is the

minimum DO saturation at the morning (%).

At the same time, daily total exposure of solar radiation over the period

between DOmin and DOmax was computed. Average monthly ΔDOsat and solar

exposure were then considered to examine the change of DO saturation over months

and seasons.

3.3 Results

3.3.1 Long term changes in wetland properties

Nutrient concentrations at the two inlets (W1 and W2) and the outlet (W3)

were averaged over periods defined as ‘dry’ (December to May) and ‘wet’ (June to

November) under both pre- and post-restoration regimes (Table 3. 2). Mean NH3,

NOx, TN, FRP and TP concentrations at W2 were higher than that measured at W1,

irrespective of the periods or restoration regimes. DON concentrations were higher at

W1 compared to that observed at W2 during the dry periods and vice-versa during the

wet periods under both pre- and post-restoration regimes. NH3 concentrations at W3

during the wet periods of pre-restoration periods were almost double than those

measured during the wet periods of post-restoration periods. NOx concentrations at

W3 during the wet periods were higher than that observed during the dry periods

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under both pre- and post-restoration regimes. TKN and DON concentrations were

variable at W3. TN concentrations at W3 were lower during the dry periods than that

of the wet periods, while TP concentrations showed the reverse. Since 2014,

additional nutrient species were measured in the surface water (Table 3. 2). FTN, PN

and DIN concentrations at W3 during the dry periods were less than the combined

mean concentrations measured at W1 and W2. The opposite scenario was found for

NO2, FTN, UreaN, DIN, NO3 and FTP concentrations. W3 showed average higher

DIC and DOC concentrations than that measured at W1, while both species showed

the highest concentrations at W3 during the wet periods.

Annual average nutrient attenuation as SDC was assessed from 2004 to 2015

(Figure 3. 2 and Figure 3. 3). Inorganic and dissolved N fractions like NOx and NH3

showed higher attenuation than the total and organic fractions like TN and DON

(Table 3. 3). Moreover, NH3, TKN and TN attenuation increased after the restoration.

Annual mean NOx attenuation was always positive (Figure 3. 2d) with slight decrease

immediately after the restoration; however NOx showed an increasing attenuation

trend three years later (Figure 3. 2c, d). DON attenuation also increased slightly after

the restoration, however, was negative thereafter (Figure 3. 2g,h). FRP and TP showed

periodic release and attenuation during the pre-restoration, while attenuation increased

after the restoration (Figure 3. 3). Annual average FRP and TP attenuation was

negative for the first six years of monitoring. TP attenuation then increased and

reached at the maximum immediately after the restoration (Figure 3. 3b, d). However,

TP and FRP started to be released from the AWCB four years after the restoration.

Overall, the attenuation of inorganic N was greater than inorganic P. Inorganic N and

TP attenuated more effectively during the dry and wet periods, respectively (Table 3.

3). DIN showed higher attenuation than DON, while DIC and DOC released (Table 3.

3). Restoration features improved attenuation of NH3, TKN, TN, FRP and TP in the

AWCB. Using student’s t-test for independent samples, Mann-Whitney’s normalized

test and normalized Wilcoxon’s T test against the normal distribution of data, we

found that attenuation during post-restoration periods were statistically significant for

NH3 (p < 0.010), TKN (p < 0.002), TN (p < 0.001) and TP (p < 0.041).

Using student's t tests for independent samples, Mann-Whitney's normalized

test and normalized Wilcoxon's T test against the normal distribution of data, it was

found that attenuation during the post-restoration periods were statistically significant

for NH3 (p < 0.010), TKN (p < 0.002), TN (p < 0.001) and TP (p < 0.041). As the

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AWCB received water and nutrients from multiple sources, there were some

uncertainties of nutrient attenuation. SDC estimation didn’t consider the influence of

the MSD and therefore SDC_ave was applied since it combined mean concentrations

at W1 and W2 as input concentrations (Figure 3. 4 and Figure 3. 5). Nutrient

attenuation as SDC_ave increased compared to SDC for all nutrients species

irrespective of periods or restoration regimes. Moreover, SDC_ave was positive for all

species, except DIC (Table 3. 3).

Load attenuation indicated the performance of the AWCB when (a)

simultaneous flow and nutrient concentration were available at the inlet and outlet,

and (b) influence of MSD was relatively small in respect of water flow and nutrient.

However, these condition were available is some occasion since end of 2012. NH3

showed higher load attenuation among N based nutrients with the efficiency being

above 50%. This was equivalent to a mass removal between 0.1 and 11 kg/day. TKN,

TN and NOx were subsequently removed with less efficiency. Although there was

limited DON data, it suggested that this fraction was hardly removed. This was

consistent with the observation of low SDC for DON (Figure 3. 2g,h). FRP showed

higher load attenuation (up to 70%) compared to TP, however both nutrients showed

periodic release and attenuation. Furthermore, P load released during high flow

conditions caused by sudden pulse after prolonged dry or low flow conditions.

3.3.2 Nutrient accumulation or uptake in the sediment and macrophytes

The bench sites (S2 and S3) had a greater sedimentation area and therefore,

accumulated more nutrient mass than that stored in the in-stream sites (S1 and S4)

(Figure 3. 6). S4 had 3–4 times more nutrient mass than that of at S1. Nutrient mass

increased sharply at the bench sites from November 2011 to May 2013. No data was

obtained after May 2014 at the bench sites. Net assimilation of TN and TOC varied

consistently with time, while P assimilation was less clear (where t is the days since

11 November 2011):

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Table 3. 2 Spatial and temporal variability of nutrient concentrations in the Anvil Way Compensation Basin. The dry and wet periods represent

December to May and June to November, respectively.

aThe Australian and New Zealand Environment and Conservation Council (ANZECC) guideline values

bHalthy River Action plan (HRAP) target values

n/a not applicable

Nutrient

species

Dry periods Wet periods

Pre-restoration Post-restoration Pre-restoration Post-restoration

Main inlet

(W1)

(mg/L)

Mars

Street

Drain

(W2)

(mg/L)

Man

outlet

(W3)

(mg/L)

Outlet

conc.

within

target

values

(%)

Main inlet

(W1)

(mg/L)

Mars

Street

Drain

(W2)

(mg/L)

Man outlet

(W3)

(mg/L)

Outlet

conc.

within

target

values

(%)

Main inlet

(W1)

(mg/L)

Mars

Street

Drain

(W2)

(mg/L)

Man

outlet

(W3)

(mg/L)

Outlet

conc.

within

target

values

(%)

Main inlet

(W1)

(mg/L)

Mars

Street

Drain

(W2)

(mg/L)

Man outlet

(W3)

(mg/L)

Outlet

conc.

within

target

values

(%)

NH3 0.15±0.16 0.41±0.28 0.10±0.14 73.53a 0.39±0.37 0.42±0.11 0.11±0.12 42.86

a 0.15±0.16 0.42±0.24 0.15±0.21 54.28

a 0.16±0.16 0.18±0.17 0.07±0.06 60.71

a

NOx 0.16±0.18 0.16±0.18 0.05±0.06 94.12a 0.14±0.19 0.44±0.36 0.03±0.04 100

a 0.40±0.24 0.49±0.48 0.27±0.23 40

a 0.52±0.31 0.54±0.44 0.41±0.32 23.3

a

TKN 1.13±0.47 1.34±0.46 1.26±0.46 n/a 1.27±0.46 1.24±0.36 1.01±0.28 n/a 0.97±0.37 1.11±0.53 1.03±0.37 n/a 0.88±0.26 0.99±0.63 0.73±0.20 n/a

DON 0.75±0.25 0.72±0.27 0.81±0.24 n/a 0.70±0.14 0.51±0.18 0.73±0.15 n/a 0.63±0.26 0.69±0.46 0.63±0.25 n/a 0.46±0.17 0.58±0.49 0.48±0.17 n/a

TN 1.25±0.47 1.52±0.51 1.33±0.42 44.18a

23.53b

1.33±0.45 1.68±0.74 0.99±0.29 79.31a

62.07b

1.34±0.48 1.58±0.74 1.36±0.71 5143a

28.57b

1.28±0.59 1.28±0.74 1.01±0.49 46.45a

66.67a

FRP 0.07±0.06 0.17±0.19 0.08±0.05 26.47a 0.15±0.14 0.51±0.78 0.11±0.11 26.93

a 0.05±0.02 0.09±0.13 0.04±0.02 57.14

a 0.05±0.02 0.09±0.06 0.04±0.02 48.38

a

TP 0.17±0.10 0.37±0.33 0.21±0.10 0a

2.94b

0.22±0.13 0.64±0.82 0.22±0.13 17.24a

24.14b

0.14±0.05 0.20±0.19 0.18±0.20 0a

2.86b

0.12±0.05 0.17±0.15 0.10±0.04 50a

56.26b

NO2 n/a n/a n/a n/a 0.02±0.00 0.02 0.01±0.01 n/a n/a n/a n/a n/a 0.01±0.00 0.06±0.07 0.01±0.00 n/a

FTN n/a n/a n/a n/a 0.79±0.04 0.95 0.72±0.14 n/a n/a n/a n/a n/a 0.71±0.48 0.54±0.12 0.49±0.26 n/a

UreaN n/a n/a n/a n/a 0.00±0.01 0 0.00±0.00 n/a n/a n/a n/a n/a 0.04±0.03 0.02±0.01 0.02±0.02 n/a

PN n/a n/a n/a n/a 0.22±0.28 0.59 0.09±0.23 n/a n/a n/a n/a n/a 0.02±0.14 0.02±0.03 0.07±0.05 n/a

DIN n/a n/a n/a n/a 0.27±0.07 0.66 0.16±0.08 n/a n/a n/a n/a n/a 0.32±0.20 0.31±0.07 0.15±0.06 n/a

NO3 n/a n/a n/a n/a 0.17±0.05 0.15 0.05±0.07 n/a n/a n/a n/a n/a 0.28±0.21 0.23±0.04 0.12±0.07 n/a

DON n/a n/a n/a n/a 0.53±0.11 0.29 0.57±0.06 n/a n/a n/a n/a n/a 0.39±0.28 0.24±0.11 0.34±0.24 n/a

NUON n/a n/a n/a n/a 0.52±0.10 0.29 0.57±0.06 n/a n/a n/a n/a n/a 0.17±0.20 0.22±0.12 0.24±0.20 n/a

FTP n/a n/a n/a n/a 0.07±0.03 1.65 0.18±0.06 n/a n/a n/a n/a n/a 0.05±0.01 0.06±0.01 0.05±0.01 n/a

PP n/a n/a n/a n/a 0.08±0.03 0.05 0.05±0.02 n/a n/a n/a n/a n/a 0.02±0.01 0.02±0.01 0.02±0.03 n/a

DOP n/a n/a n/a n/a 0.01±0.00 0.05 0.02±0.01 n/a n/a n/a n/a n/a 0.01±0.01 0.01±0.00 0.01±0.01 n/a

DIC n/a n/a n/a n/a 10.51±2.88 2.4 15.51±3.15 n/a n/a n/a n/a n/a 10.42±8.41 5.03±2.12 10.81±8.14 n/a

DOC n/a n/a n/a n/a 10.55±1.74 7.75 12.60±0.52 n/a n/a n/a n/a n/a 6.46±3.11 4.82±0.25 6.38±2.99 n/a

TDC n/a n/a n/a n/a 21.06±1.14 10.15 28.11±2.63 n/a n/a n/a n/a n/a 16.89±10.84 9.85±1.93 17.19±10.37 n/a

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Figure 3. 2 Nutrient attenuation (as SDC) in the Anvil Way Compensation Basin over pre- and

post-restoration regimes. Bar plots (a, c, e, g and i) show attenuation over individual sampling

periods, while box plots (b, d, f, h and j) show annual average attenuation. Solid thick vertical

lines in bar and box plots represent the time (November 2010) when the Anvil Way

Compensation Basin was restored. Horizontal lines and open squares in each box plot

represent the annual median and mean SDC, respectively. Data of pre-restoration and post-

restoration periods include September 2004 to November 2010 and December 2010 to April

2015, respectively.

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Figure 3. 3 Nutrient attenuation (as SDC) in the Anvil Way Compensation Basin over pre- and

post-restoration regimes. Bar plots (a and c) show attenuation over individual sampling

periods, while box plots (b and d) show annual average attenuation. Solid thick vertical lines

in bar and box plots represent the time (November 2010) when the Anvil Way Compensation

Basin was restored. Horizontal lines and open squares in each box plot represent the annual

median and mean SDC, respectively. Data of pre-restoration and post-restoration periods

include September 2004 to November 2010 and December 2010 to April 2015, respectively.

TN = 18.64t + 62.67; R2

= 0.84 (3.9)

TOC = 240.7t + 9163; R2

= 0.92 (3.10)

TP = 1.866t + 122.6; R2

= 0.55 (3.11)

The most recent i.e., June 2012 assessment of species coverage showed that B.

articulata (jointed twig-rush) and S. validus (lake club rush) were the most widely

dispersed macrophytes across the AWCB. B. articulata and S. validus were rooted on

riparian and saturated soil, and had extensive root and rhizome systems. TKN

concentrations in the AGB and BGB of S. validus were approximately the same, while

B. articulata showed higher TKN and TP concentrations in the BGB. Nutrient uptake

efficiency of the common reed was found higher in AGB than in BGB in Malaysia

(Sim et al. 2008).

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Table 3. 3 Nutrient attenuation as SDC and SDC_ave during the dry and wet periods over pre- and post-restoration regimes of the Anvil Way

Compensation Basin. The dry and wet periods represent December to May and June to November, respectively.

Dry periods Wet periods

Pre-restoration Post-restoration Pre-restoration Post-restoration

SDC (%) SDC_ave (%) SDC (%) SDC_ave (%) SDC (%) SDC_ave (%) SDC (%) SDC_ave (%)

NH3 -24.24±247.62 67.83±69.44 60.58±41.86 71.88±38.40 -30.07±161.26 69.83±36.91 29.77±71.38 68.85±20.83

NOx 44.14±56.34 80.20±24.76 43.31±47.05 83.71±22.37 38.59±33.39 70.59±15.41 10.33±54.07 61.26±20.28

TKN -20.25±53.35 48.08±15.58 13.93±33.32 44.66±23.69 -10.89±30.71 48.08±16.43 13.57±20.68 48.25±21.75

DON -9.47±27.06 44.27±15.01 -4.24±13.61 13.65±26.59 -5.15±25.29 48.86±13.55 -9.22±39.25 12.24±21.67

TN -14.66±50.48 50.88±15.48 20.62±30.35 56.39±20.21 -3.46±42.76 55.06±11.16 19.53±18.02 57.69±15.90

FRP -29.79±79.04 56.63±39.18 1.91±79.70 28.99±80.52 1.97±58.50 59.27±22.51 16.33±28.74 61.58±29.30

TP -42.26±81.55 54.24±21.70 -16.81±65.52 49.59±35.15 -21.64±68.89 50.10±16.87 15.81±19.84 57.82±25.37

NO2 n/a n/a 45.29±38.96 55.63 n/a n/a 13.81±30.92 80.28±9.34

FTN n/a n/a 7.96±22.261 52.11 n/a n/a 20.00±21.58 63.86±4.69

UreaN n/a n/a 64.346 n/a n/a n/a 30.75±21.17 50.83±8.97

PN n/a n/a 40.623 75.24 n/a n/a 68.15±56.23 66.61±17.99

DIN n/a n/a 42.85±14.16 78.49 n/a n/a 35.63±38.26 67.47±4.17

NO3 n/a n/a 72.88±35.45 70.09 n/a n/a 29.732±51.06 63.17±0.80

DON n/a n/a -11.44±34.73 17.33 n/a n/a 7.50±15.39 59.34±3.58

NUON n/a n/a -11.77±34.26 17.33 n/a n/a -4.96±28.37 62.69±5.36

FTP n/a n/a -147.86±32.42 87.42 n/a n/a -1.50±12.93 56.53±0.44

PP n/a n/a 39.92±1.60 61.51 n/a n/a 3.75±81.09 67.79±10.83

DOP n/a n/a -18.59±43.23 65.69 n/a n/a 10.83±10.15 61.28±3.34

DIC n/a n/a -49.09±10.85 -22.13 n/a n/a -7.03±14.38 49.65±9.04

DOC n/a n/a -20.69±14.97 33.57 n/a n/a -0.24±15.39 52.66±14.32

TDC n/a n/a -33.36±5.28 13.65 n/a n/a -5.43±12.67 48.29±4.89

n/a not applicable

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Figure 3. 4 Change of attenuation (as SDC_ave) of N species by the Anvil Way Compensation

Basin over the pre- and post-restoration regimes. Bar plots show attenuation over individual

sampling periods, while box plots show annual average attenuation. 100% SDC_ave indicates

compete attenuation while negative SDC_ave indicates nutrient release. Solid thick vertical

lines in bar and box plots represent the time when the Anvil Way Compensation Basin was

restored (November 2010). Horizontal lines and open squares in each box plot represent the

annual median and mean SDC_ave, respectively. Data of the pre-restoration periods include

September 2004 to November 2010, whilst the post-restoration periods include December

2010 to April 2015.

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Figure 3. 5 Change of attenuation (as SDC_ave) of P species by the Anvil Way Compensation

Basin over the pre- and post-restoration regimes. 100% SDC_ave indicates compete

attenuation while negative SDC_ave indicates nutrient release. Bar plots show attenuation

over individual sampling periods, while box plots show annual average attenuation. Solid

thick vertical lines in bar and box plots represent the time when the CW was restored

(November 2010). Horizontal lines and open squares in each box plot represent the annual

median and mean SDC_ave, respectively. Data of the pre-restoration periods include

September 2004 to November 2010, whilst the post-restoration periods include December

2010 to April 2015.

However, the significantly higher BGB of S. validus and B. articulata in the

AWCB confirmed TKN and TP mass per unit area were also higher in the BGB. The

macrophytes showed maximum nutrient storage in the ABG and BGB at the age of

two and half years. The storage of nutrient mass started to decline in the following few

months (Figure 3. 7). Importantly, the macrophytes experienced seasonal senescence,

and seasonal biomass decline in the two year old B. articulata at M1 was three times

higher than that observed at M2 (Table 3. 4).

Overall S. validus senescence was 2–3 times higher than senescence of B.

articulata and after 2.5 years of plantation, new stem and leaves of S. validus started

to grow, percentage of mature plants increased and percentage of dead plants

decreased.

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Figure 3. 6 Nutrient pools of (a) TN, (b) TP and (c) TOC at the in-stream (S1 and S4) and

bench (S2 and S3) sediments of the Anvil Way Compensation Basin from November 2011 to

May 2015. Data are not available since May 2014 at the bench sites.

3.3.3 Hydrological variability on nutrients dynamics

Although there was very low flow during the dry summer periods in WA,

seasonal variability in hydrology was expected to drive variability in attenuation. The

maximum rainfall around the AWCB occurred during the winter between July and

September, followed by a sharp reduction over spring and summer between

September and January (Figure 3. 8a). A seasonal pattern of flow rate and discharge

was observed at the outflow, with high flow rate and discharge during the wet months

(Figure 3. 8b). Total outflow discharge was sometimes higher than the total input,

particularly during the wet periods. The water balance indicated approximately 20–

70% of the water came from unaccounted sources, such as MSD and possible

groundwater inputs (Ruibal-Conti et al. 2015) depending on the rainfall characteristics

(amount and duration of rainfall). VCUA between June and December in 2012 and

2013 was estimated for selected rainfall events. VCUA was generally small (13–27%)

for mid to large size rainfall events (> 25 mm) and large (40–80%) for small and

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frequent rainfall events, particularly between the late wet and early dry periods

(Figure 3. 9). VCUA and runoff generating areas varied over the season in accordance

with the antecedent wetness conditions (Ruibal-Conti et al. 2015).

Figure 3. 7 Nutrient pools in AGB and BGB of the Anvil Way Compensation Basin from

October 2012 to October 2013. (a) TKN in AGB, (b) TKN in BGB, (e) TP in AGB, and (f) TP

in BGB of S. validus; (c) TKN in AGB, (d) TKN in BGB, (g) TP in AGB, and (h) TP in BGB

of B. articulata. B. articulata are collected only in October 2012 and May 2013 at site M1 and

M2. AGB and BGB denote above ground biomass and below ground biomass, respectively.

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Table 3. 4 Spatial and temporal changes of physical properties of above ground biomass of aquatic macrophytes per quadrate in the Anvil Way

Compensation Basin.

Sampling

date

Site

name

Species No of Stems No of

Inflorescences

Stem height (m) Leaf stage (%)

Min. Max. Average New Mature Senescent

10/10/2012 M1 BA 77.33±27.12 3.00±1.54 0.267±0.17 2.47±0.26 1.5±0.21 2.33±1.33 78.00±4.16 19.67±4.67

M2 BA 57.67±8.97 3.67±2.18 0.14±0.05 2.19±0.04 1.38±0.12 2.33±0.33 91.00± 2.00 6.67±1.67

M1 SV 47.67±10.39 6.00±1.53 0.08±0.04 1.59±0.09 0.82±0.09 4.33±1.86 44.00±23.43 51.67±21.6

M2 SV 71.67±9.28 10.00±2.08 0.17±2.08 2.17±0.05 1.47±0.06 1.33±0.33 79.33±5.84 19.33±5.67

M3 SV 57.00±11.14 6.67±2.73 0.04±0.01 1.47±0.04 0.89±0.05 7.33±3.93 51.00±4.58 41.67±8.33

M4 SV 54.33±3.48 9.00±1.00 0.07±0.01 1.78±0.22 1.68±0.38 3.00±1.00 52.67±6.22 44.33±5.67

13/05/2013 M1 BA 78.33±6.98 3.00±1.53 0.23±0.14 2.31±0.15 1.56±0.14 5.00±2.88 65.00±10.41 30.00±10.00

M2 BA 114.00±19.69 16.67±6.23 0.21±0.09 2.45±0.08 1.52±0.10 2.00±0.58 58.00±5.19 40.00±5.77

M1 SV 85.00±4.16 11.00±2.52 0.09±0.04 1.73±0.24 1.19±0.19 4.00±3.00 44.67±5.17 51.33±4.67

M2 SV 108.33±24.04 16.67±7.67 0.05±0.01 1.87±0.33 1.27±0.35 7.30±2.67 39.33±0.67 53.33±3.33

M3 SV 90.33±13.29 22.67±1.67 0.07±0.05 1.75±0.01 1.26±0.06 5.33±2.66 48.00±3.00 46.67±1.67

M4 SV 66.00±20.52 20.00±4.36 0.05±0.03 1.85±0.12 1.31±0.15 11.00±4.93 52.33±3.71 36.67±6.01

15/10/2013 M1 SV 84.67±7.68 21.33±4.84 0.13±0.08 1.65±0.08 0.94±0.03 3.00±2.00 86.00±3.00 11.00±1.00

M2 SV 80.33±14.62 15.00±3.78 0.04±0.01 1.58±0.14 0.77±0.08 4.67±0.88 84.33±5.78 11.00±4.93

M3 SV 115.00±21.50 21.00±8.08 0.08±0.01 1.73±0.09 0.79±0.22 3.33±0.88 53.33±9.53 43.33±8.82

M4 SV 123.67±38.58 16.67±3.99 0.09±0.03 2.14±0.06 1.01±0.21 1.17±13.20 52.17±13.20 46.67±13.64

BA: B. articulata

SV: S. validus

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Figure 3. 8 (a) Monthly total rainfall recorded at Perth Airport Station, located 5 km north-

south of the Anvil Way Compensation Basin, from 2012 to 2015, and (b) monthly total

discharge and monthly average flow rate at main outflow station of the Anvil Way

Compensation Basin from 2012 to 2014.

Figure 3. 9 Selected rainfall amount and rainfall duration at Welshpool Weather Station,

located 0.8 km north-west of the Anvil Way Compensation Basin, along with flow discharge

in 2012 and 2013. (a) Rainfall amount and duration in 2012, (b) inflow and outflow water

volume, and VCUA in 2012, (c) rainfall amount and duration in 2013, and (d) inflow and

outflow water volume and VCUA in 2013. VCUA denotes volumetric contribution from

ungauged areas.

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The possible contribution of this ungauged water may bring with additional

nutrient inputs from MSD and/or groundwater. Nutrient concentrations at MSD are

given in Table 3. 5, while groundwater nutrients since April 2010 are shown in Table

3. 5. NH3 concentrations were higher during the wet periods across all the four bores

while NOx, TKN and TN concentrations were higher during the wet periods, except at

G1. FRP and TP concentrations were 3–10 times higher at G2 than that measured at

other bores and concentrations were relatively close during at the dry and wet periods

(Table 3. 5). NH3 concentrations at W3 were higher than that measured at

groundwater bores during the wet periods and vice-versa during the dry periods. NOx

concentrations were higher at W3 than that observed at G2 but lower than at G4. TN

concentrations during the wet periods in bores, except G2, were higher than

concentrations at W3. FRP and TP concentrations at W3 were lower than

concentration at G2, however higher than other bores. As the AWCB received water

and nutrients from multiple sources, there were some uncertainties of nutrient

attenuation. SDC estimation didn't consider the influence of W2 and therefore

SDC_ave was applied since it combined mean concentrations at W1 and W2 as input

concentrations (Figure 3. 4 and 3. 5). SDC_ave increased compared to SDC for all

nutrients irrespective of periods or restoration regimes. Moreover, SDC_ave was

positive for all species, except DIC. The relationship between SDC and HRT was not

clear as nutrients showed both attenuation and release at the same HRT. For example,

during the wet periods, we observed maximum attenuation and release of NOx and

TN when HRT was 0.3–0.5 day. We observed limited correlation between SDC and

HRT when outflow water levels were low due to limited rainfall and associated flows.

Under such conditions, up to 70% attenuation and 10% release of NOx were observed

at 1–2 days HRT.

Table 3. 5 Spatial and temporal variation of groundwater nutrient concentrations at four bores

in the Anvil Way Compensation Basin from 2010 to April 2015. The dry and wet periods

represent December to May and June to November, respectively.

Nutrient

(mg/L)

Bore

G1 G2 G3 G4

Dry Wet Dry Wet Dry Wet Dry Wet

NH3 0.19±0.06 0.26±0.05 0.18±0.02 0.22±0.04 0.25±0.05 0.33±0.12 0.39±0.08 0.48±0.14

NOx 2.49±2.10 2.26±1.57 0.013±0.00 0.244±0.69 0.097±0.12 1.44±2.95 0.11±0.17 3.14±4.24

TKN 0.79±0.25 0.78±0.31 0.48±0.15 0.55±0.12 0.50±0.09 0.86±0.63 0.90±0.25 0.94±0.26

TN 3.29±2.06 3.26±1.67 0.49±0.15 0.78±0.75 0.59±0.18 2.25±3.30 1.00±0.31 4.06±4.08

FRP 0.06±0.01 0.05±0.01 0.22±0.07 0.22±0.07 0.02±0.00 0.02±0.00 0.07±0.03 0.08±0.03

TP 0.07±0.02 0.07±0.02 0.26±0.07 0.23±0.08 0.03±0.00 0.03±0.01 0.08±0.03 0.09±0.03 Bores G1, G2 and G3 were installed in April 2010 and G4 was installed in January 2012

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Hydrological variability including rainfall, groundwater input or seepage can

influence the properties of riparian zones of CW. Eh of riparian soil and nutrient

concentrations in soil porewater influenced by soil saturation after rainfall or seasonal

groundwater seepage in the AWCB. P1, the deepest point of the riparian transect, was

saturated throughout the sampling periods and showed highly reduced Eh (Figure 3.

10). P3 situated at the top of the transect (in the sand bar), and was saturated

periodically and displayed a relatively oxidised state. NH3 concentrations increased at

the three sites after soil saturation, and interestingly P3 showed the highest NH3

concentrations. Average NH3 concentrations in porewater were higher than that found

in groundwater bores and outlet. NOx concentrations at P1 and P2 changed slightly

after soil saturation while P3 showed the highest NOx concentrations. FRP

concentrations were also maximum at P3, where P1 and P2 experienced with FRP

increase slightly. Soil porewater samples were rich with DOC and DIC and porewater

DIC concentrations were lower at P1 and P2 compared to that at P3 after the first

rainfall event on 13 March 2015. DIC and DOC concentrations increased at all sites

following the second round soil saturation (Figure 3. 10). Average porewater DIC and

DOC concentrations were higher than that measured at the surface water inlet and

outlet.

3.3.4 Diurnal changes in wetland function

DO is considered as an important parameter for nutrient dynamics within

CWs. However, we had only spot DO readings at W1, W2 and W3 during the day

time on fortnightly or monthly intervals from 2004 to 2015. DO concentrations

showed a clear seasonal trend, with the maxima and minima during the wet and dry

periods, respectively. A long term decrease in the average DO levels was observed at

W1 and W3. DO concentrations dropped to around zero, and anoxic water has been

recently observed at W1 and W3 for several months over the dry periods. DO maxima

also decreased during the wet periods to around 7 mg/L in 2014 (Figure 3. 11a).

Groundwater DO concentrations were consistently low, ranging from 0 to 2 mg/L,

with few exception and no obvious seasonal trend (Figure 3. 11b). High resolution DO

data of the AWCB from 2014 to 2015 indicated a strong diurnal DO signal where

nigh-time anoxia (< 1 mg/L) was observed for most of the dry months (Figure 3. 11c)

and the maximum DO concentrations were recorded during the sunny days. DO levels

of the AWCB responded to the exposure of solar radiation (Figure 3. 12a, b). Higher

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DO concentrations and saturation fluctuation were found during the dry months.

Furthermore, ΔDO saturation over time, particularly during the dry periods, was

correlated with solar radiation exposure (R2 = 0.82) (Figure 3. 12a). Almost flat or

zero DO concentration and saturation were also observed during the sunny days.

There might be several causes behind the occurrence of low DO, and one of

the assumptions was formation of weeds, algal mats, floating macrophytes, debris or

combination of all on water surface and edge of the main stream. Although controlled

floating macrophyes or bed attenuated nutrient in other studies (Chua et al. 2012;

Chang et al. 2013), floating material in the AWCB formed a thick layer in the main

stream. Such floating material of the AWCB provided shade to the stream water that

suppress light penetration and photosynthesis, and consequently reduced DO levels.

We observed different scenarios of the coverage of the main stream by floating

material using the digitized NearMap images from 1 August 2014. These scenarios

included: (a) 1 August 2014: water was flowing and little scattered material started to

grow on the main stream, (b) 27 October 2014: slight accumulation of floating

material on the edge of the main stream, (c) 7 December 2014: accumulation of

floating material progressed towards the edge and part of the main stream, (d) 7

February 2015: occurrence of dense floating material over the main inlet,

sedimentation pond and main stream, (e) 7 March 2015: dense floating material over

main inlet, sedimentation pond and main stream, (f) 24 April 2015: clearance of all

debris and floating material from main stream, and (g) 28 June 2015: main stream

without any floating material. Attempts were taken to compare the relative coverage

or shade of the main channel with DO saturation fluctuation. The maximum stream

coverage (about 70%) and occurrences of flat DO were observed in February and

March 2015. The minimum ΔDO saturation was recorded at the time of maximum

shade while ΔDO saturation increased in April 2015 after the manual removal of

floating material (Figure 3. 12c).

The diurnal pattern of nutrient concentrations of the surface water was

monitored along with DO levels and solar exposure for 2 days (12 and 13 March

2015) before a storm event (Figure 3. 13). The 12 March was sunny and had hypoxic

water (DO∼ 0.2–0.7 mg/L) at the main stream, while DO concentrations were almost

zero at night. The following day was cloudy (Figure 3. 13a) and DO concentrations

remained unchanged with only a slight increase of DO levels for a few hours after a

rainfall pulse (Figure 3. 13b).

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Figure 3. 10 Spatial and temporal trend of (a) water level and porewater oxidation-reduction

potential within a riparian zone transect, and (b–e) nutrients from 11 to 17 March 2015. Water

level and porewater oxidation-reduction potential data are collected at 10 and 30-min

intervals, respectively. P1, P2 and P3 sites are at saturated zone, transitional zone between

saturation and unsaturation zone, and unsaturated sand bar, respectively.

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Figure 3. 11 Changes of delta DO saturation in response of solar exposure and stream

coverage with floating macrophytes in the Anvil Way Compensation Basin. (a) Change of

delta DO saturation (difference between the highest DO saturation during the afternoon and

the lowest DO saturation during the morning) as a function of solar exposure (sum of solar

radiation exposed over time to achieve delta DO saturation) during the wet and dry periods.

The wet and dry periods include June to November and December to May, respectively. (b)

Standard deviation of delta DO saturation as a function of solar exposure at the wet and dry

periods. (c) Coverage of main stream by senescent macrophytes along with floating material

and respective mean delta DO saturation over time. NearMap provides main stream coverage

images.

Nutrient species (Figure 3. 13c-f) followed a diurnal trend with DO

concentrations and sunlight. NH3 concentrations at W1 and W2 decreased as

progressed towards the day-time and relatively higher DO levels, and vice-versa at

night. DON also followed diurnal trend with the maximum concentrations at W3 was

measured at the mid-day. FRP at W1 and W3 showed a diurnal pattern with increased

concentrations from the afternoon to next day early morning due to lack of DO.

However, as sunlight appeared and DO concentrations increased, FRP concentrations

decreased at W1 and W3. DIC concentrations were lower at W3 compared to that

found at W1, while DOC released from the system, particularly from evening to

morning.

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Figure 3. 12 (a) Changes of delta DO saturation in response of solar exposure and stream

coverage with floating macrophytes in the Anvil Way Compensation Basin. (a) Change of

delta DO saturation (difference between the highest DO saturation during the afternoon and

the lowest DO saturation during the morning) as a function of solar exposure (sum of solar

radiation exposed over time to achieve delta DO saturation) during the wet and dry periods.

The wet and dry periods include June to November and December to May, respectively. (b)

Standard deviation of delta DO saturation as a function of solar exposure at the wet and dry

periods. (c) Coverage of main stream by senescent macrophytes along with floating material

and respective mean delta DO saturation over time. NearMap provides main stream coverage

images.

3.4. Discussion

3.4.1 Restoration improves attenuation of specific nutrient species

Nutrient attenuation after CW restoration depends on the effectiveness of the

biogeochemical and hydrological controls included or modified during the restoration.

The AWCB restoration aimed to improve nutrient attenuation and transformation by

inclusion of (a) a sedimentation pond close to the main inlet, (b) a meandering low

flow path, (c) densely vegetated stream banks and riparian zones, (d) multiple sand

bars, (e) a low flow diversion from MSD to the sedimentation pond, and (f) an

adjustable outlet weir. The possible consequences of these restoration initiatives on

nutrient dynamics in the AWCB are summarized in Table 3. 6.

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Figure 3. 13 Diurnal pattern of meteorology and water quality in the Anvil Way

Compensation Basin from 12 to 13 March 2015. (a) Rainfall, solar radiation and outflow rate,

(b) main stream water temperature, and DO concentrations at main stream and outlet (W3),

and (c–f) nutrient concentrations at inlet (W1) and outlet (W3). Rainfall, solar radiation, water

temperature and DO data are recorded at 10-min intervals, while outflow rate is recorded at 5-

min intervals.

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Table 3. 6 Conceptual consequences of the Anvil Way Compensation Basin restoration initiatives on nutrient attenuation and transformation

pathways.

Nutrient attenuation pathway enhancement

Restoration initiatives

Enhance

water

travel

time and

contact

with

system

Increase

surface

area-to-

volume

ratio

Increase

favourable

conditions for

denitrification

Provide

suitable

conditions

for

nitrification

Enhance

groundwater

-surface

water

interaction

Increase

interaction

with

macrophytes

Promote

opportunities

to interact

with soil or

sediment

Enhance

particle

settling

Promote

condition

for

nutrient

sorption

Removal of sludgy sediments √ √

Creation of sedimentation pond

close to main inlet √ √ √

Introduction of multiple sand bars √

Low flow diversion from MSD √

Creation of meandering stream or

channel √ √ √ √ √ √

Modification of flow path

through the basin √ √ √ √ √ √ √ √ √

Densely vegetated shallow

benches or riparian zone √ √ √ √ √ √

Modification of riparian soil zone √ √ √ √ √

Modification of outlet structure √

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Studies of other CWs have found that restoration encouraged nutrient

processing by increasing contact and interaction between stream water, vegetated

riparian zones and biogeochemical active sites (Verhoeven et al. 2006).. Additionally,

nutrient uptake and transformation within the CWs usually increased due to higher

surface transient storage (Baker et al. 2012). Before restoration, our study site was a

compensating basin where stormwater passed through the system via the outlet

quickly (approximately 1–2 h HRT). HRT of the AWCB increased after the

restoration due to inclusion of the meandering flow path, sand bars and dense

macrophytes. Although the relationship of HRT and SDC was not strong enough,

overall attenuation of the nutrients increased after the restoration (Figure 3. 2 and

Figure 3. 3). Other factors therefore contributed in overall attenuation of the system,

for example, modification of riparian zones and plantation of macrophytes

significantly contributed nutrient uptake (Figure 3. 6 and Figure 3. 7).

Interestingly, we found NOx attenuation in the AWCB decreased for the first

three years after the restoration (Figure 3. 2b, d). An available C source and low

oxygen levels are important for NOx attenuation or denitrification (Saeed & Sun

2012). Removal of organic-rich sediments during the AWCB restoration reduced the

C availability and suitable conditions for the denitrifying bacteria to process NOx.

Oxygen levels in the water column of the restored AWCB increased which can trigger

NH3 attenuation and NOx generation. Moreover, NOx attenuation is higher in fine

grained sediments than coarse sediments and therefore, replacement of sludgy

sediments with coarse grained soils/sediments within the AWCB during restoration

can also reduce NOx attenuation. Since restoration, organic matter from the inflowing

water and decay of plant material has slowly accumulated in the AWCB and oxygen

levels have declined; hence the NOx attenuation has subsequently increased (Figure 3.

2b, d).

We found that although FRP and TP attenuation increased immediately after

the restoration, P release began again two years later (Figure 3. 3). In CWs, sorption is

one of the leading mechanisms for P attenuation and essentially follows first order

reactions with removal of P to the new soils being proportional to the concentration of

P in the surface water (Kadlec & Knight 1996). During the restoration, earth works

incorporated new soil into the AWCB that have initially improved P attenuation,

however by two years had become a P source. P sorption for any soil sites is finite,

and once soil sorption sites become saturated due to nutrient loading, the system

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becomes a P source rather than a sink (Bridgham et al. 2001). Moreover,

accumulation of P from incoming water and senescent plant material and their

subsequent release or resuspension can convert the system as P source rather sink.

3.4.2 Hydrological and biogeochemical controls on nutrient attenuation

Hydrological variability is reported to influence physical and chemical

processing of nutrients within the CW (Mitsch & Gosselink 2000). Water is unevenly

distributed in the AWCB due to presence of microtopography (including benches and

sand bars), meander flow path, multiple water inputs, possible groundwater seepage

and dense macrophytes. The AWCB experienced prolonged low flows over the

summer and episodic water pulses with possible groundwater inputs during the winter

(Figure 3. 9). These entire variables shaped nutrient attenuation within the AWCB. In

general, the AWCB showed a reduced capacity to attenuate N during high flows of the

wet periods, compared to that of the dry periods. The wet time groundwater

concentrations of NH3 (all bores), NOx (all bores), TKN (bore G1, G3 and G4), TN

(bore G1, G3 and G4), FRP (bore G2) and TP (bore G2) were sometimes higher than

nutrient concentrations observed at W3. Therefore, anoxic nutrient-rich groundwater

can contribute additional nutrient concentrations to the AWCB. Furthermore, MSD

delivered stormwater and passed quickly at the outlet providing high concentrations at

the outlet indicating overall nutrient enrichment.

Nutrient attenuation depends on available ambient conditions that prevail

within CW. N attenuation in the AWCB was temperature dependent, for example,

NH3 and NOx were attenuated about 2 and 4 times higher, respectively during the dry

periods compared to that of the wet periods (Table 3. 3). During post-restoration,

overall NOx removal was 7 times higher during the dry periods than that measured

during the wet periods. NOx attenuation possibly increases during the dry periods

because warmer water increased microbial activities to break down organic carbon,

subsequently reduces DO levels and provides available C for denitrification (Rousseau

et al. 2008). Sediments of the AWCB were rich with organic matter (Figure 3. 6) and

DOC concentrations were higher at the main outlet than that observed at the main inlet

(Table 3. 3) supports the conditions for NOx attenuation. Organic carbon for NOx

attenuation in the AWCB can be delivered from inflow water, decaying of senescent

macrophytes and sediment resuspension. DON, NUON and DOP released from the

AWCB during the dry periods while DOP attenuation occurred during the wet

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periods. FRP and TP were attenuated more during the wet periods than that measured

during the dry periods, and dilution was considered as important reason for

attenuation. Dissolved N and P species showed higher attenuation than the particulate

species. Diurnal nutrient pattern (Figure 3. 13) showed that NH3 attenuation decreased

during the day-time likely due to available solar radiation and high oxygen levels.

After hydrological variability, sediments and macrophytes are important

contributor of nutrient attenuation in the AWCB. Soils/sediments and macrophytes in

riparian and in-stream areas of CWs act as buffering filters for nutrients, where

diverse ecological, hydrological and biological processes take place (Hayashi &

Rosenberry 2002; Ranalli & Macalady 2010). In the AWCB, bench sites contained 2–

3 times higher nutrient mass than that at in-stream sites (Figure 3. 6). However, bench

sites are subject to saturation by inflow water during moderate to high flows

(particularly during the wet periods) and senescence of macrophytes, and limited

wash-off of stored nutrients during the dry periods. Inflow nutrients and senescent

plant material can settled down in the bench sites, while nutrient at in-stream sites

were subject to continuous wash-off. However, sediment nutrient pools in the AWCB

also periodically decreased indicating some release of accumulated nutrients (Figure

3. 6). P precipitates with different metallic cations, like aluminium (Al), calcium (Ca),

iron (Fe) and manganese (Mn) that form amorphous or poorly crystalline solids and

co-precipitate with other minerals, such as ferric oxyhydroxide and calcite (Vymazal

2007). Al and Fe levels in water and sediments decreased in the line with P

concentrations in the AWCB after the restoration (Adyel et al. 2015a; Ruibal-Conti et

al. 2015) suggesting that P was precipitated with these metals. The top sediment layer

of the AWCB was rich with organic matter (Figure 3. 6) and therefore, NOx

processing might be triggered in the sediments. However, organic-rich bench and in-

stream sediment sites can release NH3 and NOx from their porewater to the water

column. Gabreiele et al. (2013) found that low DO concentrations in the CW

sediments indicated as NH3 supply due to microbial mineralization of organic matter

and DNRA. Soils/sediments release P through (a) diffusion due to P concentration

gradient between soils/sediments and overlying water column and (b) advection due to

microbial activities, bioturbation and vertical movement of porewater (Reddy et al.

1999). When riparian zones of the AWCB saturated after prolonged dry periods,

nutrients release occurred (Figure 3. 13). Soil saturation after dry periods usually

causes osmotic shock and microbial cell lysis to mobilize and release P (Turner &

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Haygarth 2001; Dupas et al. 2015). Furthermore, soil saturation and associated anoxic

conditions create reductive dissolution of Fe (hydr)oxides that also contribute to P

release from soil to the porewater (Dupas et al. 2015). FRP peak was observed after

riparian zone saturation, while the maximum P was found at the top most soil layer

(P3) of the AWCB riparian transect. Similar results were also observed in the AWCB

during a big storm event in March 2015 that flooded riparian zones. Therefore,

solubilisation-mobilization-transport can be the mechanism of P to be released after

saturation of the soils within the AWCB.

Seasonal groundwater level fluctuation and seepage can modify Eh of riparian

soils to release already adsorbed nutrients (Hoffmann et al. 2009). A decrease in Eh at

P2 and P3 of the AWCB riparian transect would be related to increase organic matter

and subsequent oxygen consumption. DO levels in the flooded riparian zones of the

AWCB during storm event were near zero. G2 is situated close to the main outlet of

the AWCB and contained very high FRP and TP concentrations (Table 3. 4). The

AWCB also acts C source over last couple of years. DOC entering at W1 of the

AWCB can be degraded as it travelled towards W3, however, replaced with new DOC

produced within the system and ultimately net export of the species occurred.

Groundwater seepage can contribute some nutrients export to the AWCB; however,

the magnitude of this potential export can't be projected without continuous

monitoring of groundwater quality.

After sediments, aquatic macrophytes are also responsible for nutrient

dynamics with in a CW. During the AWCB restoration, aquatic macrophytes were

planted across the AWCB and these macrophytes demonstrated nutrient uptake and

storage during early to mature growth stage (Figure 3. 7). Macrophytes of the AWCB

formed a horizontal ecotone between riparian zone and open water, and vertical

ecotone between groundwater-connected sediments and overlying water. Macrophytes

in a CW can (a) provide suitable root-shoot-leaf zones for nutrient transformation

including attachment, uptake and storage during early and mature stage, (b) provide

surfaces for the growth of microbial communities and biofilm, and (c) release oxygen

to support nitrification and supply C from root exudates (due to photosynthetically

fixed C) for denitrification (Brix 1994; Brix 1997; Cui et al. 2010; Saeed & Sun

2012). The nutrient pools within the AWCB were higher in BGB i.e., the roots and

rhizospheres than that measured in AGB i.e., shoots and leaves. The ratio of N and P

pools in AGB and BGB in the AWCB was 1:4.6 and 1:6.8, respectively.

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Macrophytes species coverage and biomass change can happen significantly

not only during the macrophyte establishment period but also on a seasonal basis. The

lack of ground-truthed of macrophytes species coverage data during the biomass

sampling prevents meaningful estimation of nutrient pools across the AWCB. We,

therefore, tested two different scenarios to estimate relative nutrient pools in

macrophytes: if the AWCB was 100% dominated by (a) S. validus or (b) B. articulata.

If the AWCB was 100% dominant by S. validus, then the total vegetation nutrient

pools would be 665 kg TKN and 141 kg TP. Similarly, if the AWCB was 100%

covered by B. articulata, then the total vegetation nutrient pools would be 1605 kg

TKN and 256 kg TP. The only ground-truthing (in 2012) indicated that the AWCB

was indeed dominated by S. validus, thus the TKN value assuming 100% S. validus

should be considered a conservative estimate of the vegetation N pools. These TKN

pools are similar in magnitude to the sediments/soils TKN pools in 2011, although

almost an order of magnitude lower than sediments/soils TKN pool in 2013. Nutrient

storage per unit area was significantly greater for B. articulata than S. validus,

suggesting that promoting the establishment and growth of B. articulata could

improve nutrient retention across the AWCB. A distinct seasonal pattern of

macrophytes senescence was observed in the AWCB (Table 3. 4). The seasonal

dynamics of S. validus also suggested that nutrients would be transferred to other

pools within the AWCB during the summer, including possible release to the

soils/sediments and CW water through leaching that can increase nutrient

concentrations at the outlet. However, litter or decay matter on the top of the sediment

is likely to have limited oxygen diffusion capacity to the lower sediment layer that

eventually create anoxic conditions and turn the environment suitable for

denitrification (Bastviken et al. 2005). All these results indicated some inter- and

intra-specific completion of macrophytes to store stormwater nutrient.

Overall differences in TN and TP attenuation can be attributed to several

reasons: (a) the AWCB inflow had proportionally more organic N than organic P, (b)

uptake of N species was 4–7 times higher than P species in macrophytes, (c) sediment

N pools were about 100 times greater than sediment P pools, (d) periodic anoxic and

C rich conditions favour NOx attenuation, while oxic conditions are favourable for

NH3 and FRP attenuation, and (e) internal release of P species was dominant than N

release. Nutrient species can be attenuated and transported into different media such

as surface water, soils/sediments, groundwater, macrophytes, microbes and overlying

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air column through different processes in the CW as summarized in Chapter 2 (Table

2. 3).

3.4.3 DO as a proxy indicator of wetland metabolism

Aquatic metabolism can be defined as the balance of gross productivity and

respiration within the water column of CWs (Tuttle et al. 2008) and we used delta DO

as a proxy indicator of CW metabolism (Adyel et al. 2016). DO levels within the CWs

indicate the balance between biogeochemical processes that consume oxygen such as

respiration, and processes that deliver oxygen to the water column such as

photosynthesis and reaeration or exchange from the atmosphere. The AWCB was

characterized by low surface water DO levels, particularly during the dry periods and

also displayed a distinct diel DO signal with almost zero DO concentration at night.

Different studies found possible reasons for low DO levels or DO depletion in the

CWs as: (a) oxygen demand as indicated by biochemical oxygen demand (BOD) and

chemical oxygen demand (COD) (Carpenter & Lodge 1986), (b) DO consumption

during breakdown of senescent macrophytes, (c) DO consumption by sediments as

indicated by sediment oxygen demand (SOD) (Chimney et al. 2006), (d) floating

macrophytes and debris via shading that inhibits photosynthesis and DO exchange

between atmosphere and water (Caraco et al. 2006; Nahlik & Mitsch 2006), (e)

reduction of wind action in standing macrophytes that limit atmospheric reaeration of

the water column (Kirk 1994), and (f) possible seasonal mixing of surface water with

hypoxic groundwater.

We also monitored how metabolism changed with meteorological conditions.

The dry periods showed 2–3 times higher ΔDO (R2 = 0.82) compared to that observed

during the wet periods in the AWCB. Anoxic conditions were frequently observed

during the dry periods with almost no ΔDO when the main water channel was covered

with floating material. The floating material usually provides shade to the water

column, inhibits light penetration to water and inhibits oxygen exchange between

atmosphere and water. Therefore, low DO levels of the AWCB water column can

limit photosynthesis and increase oxygen demanding substances. Anoxic conditions

below dense macrophytes and near sediments have reported in other aquatic system

(Carpenter & Lodge 1986). DO levels in a CW beneath floating macrophytes were

consistently below 4.0 mg/L throughout the day (Reeder 2011). Low DO

concentrations were also reported under floating mats of Lemna and Pithophora

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(Lewis & Bender 1961) and thicker mats of Lemna and Wolffia (Morris & Barker

1977). Although floating macrophytes generate oxygen, much of which mainly

emitted to the atmosphere with very limited diffusion to the water column (Morris &

Barker 1977). When senescent floating macrophytes were manually removed from the

AWCB, DO levels increased due to light availability and higher temperature, both

promoted photosynthesis. Removal of dense plant material was previously found to be

effective for improving DO levels (Kaenel et al. 2000). Higher DO levels in the water

column were also reported in area with less macrophytes and high water turbulence

(Bunch et al. 2010). Diurnal cycles in the AWCB indicated that DO levels also

increased after a rain event pulse. This has been observed in other CWs that episodic

pulses and associated increased flow rates flush senescence cells and toxic pigments

out of the CW, trigger nutrients uptake, increase reproduction rates of aquatic

producers and promote photosynthesis and respiration (Stevenson 1996; Tuttle et al.

2008). Low DO levels were also observed in the AWCB for several days, particularly

during the dry periods, even when there was limited plant cover in the main stream.

The cause of these low DO levels can be the intense SOD and consumption of DO to

break down senescent plant material. The outlet of the AWCB displayed higher DOC

concentrations than at the inlet, particularly during the dry periods and these

additional DOC were likely generated within the system through sediment flux and

decay of senescent macrophytes. High SOD and decomposition of DOC were also

reported as a source of low DO levels in other CW (Chimney et al. 2006).

3.5 Conclusions

Stormwater nutrient attenuation in a surface flow CW was assessed in this

study over diurnal to decadal time-scales. The CW was restored after five years of

operation, and consequences of such restoration were also explored in this research.

The main findings of the research included:

1) The CW showed variable nutrient attenuation indicating the influence of

hydrological and biogeochemical processes. The analysis therefore can be considered

as an important empirical evidence on CW function and how this change at temporal

scale. Analysis results can also serve as a benchmark of CW performance in diverse

hydrological regimes like low or near zero flow to pulse flow conditions. This

research indicated that restoration can improve attenuation of specific nutrients over

time, and CW can switch between nutrient source and sink.

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2) A distinct diurnal DO signature was observed in the CW with anoxia at

night, indicating how CW shifted from oxic to anoxic conditions in a 24-h cycle. The

research also indicated how nutrients responded over diurnal cycle i.e., to solar

radiation and DO concentrations. The findings highlighted the importance of sampling

time targeting particular nutrient for the assessment of CW function at diel scale.

3) The study also investigated the importance of sediments and aquatic

macrophytes as sink of incoming nutrients. The sediments were a significantly greater

sink of nutrients than that observed in two dominant macrophytes i.e., B. articulata

and S. validus. First macrophyte species stored about 3 and 2 times higher TKN and

TP pools, respectively than that stored in second species, indicating inter-specific

competition of nutrient among macrophytes at different growth phases. Seasonal

macrophytes senescence indicated stored nutrient can be released to the system or

transmitted to other pools and converted the system as nutrient source. Moreover,

senescent macrophytes along with other debris covered the main stream and provided

shad to the water that reduced DO concentrations.

4) The research explored wetland metabolism based on diurnal change of high

frequency DO data, as a proxy of CW function. The study untimely showed that

metabolism was linked with solar radiation exposure, and able to correlate with degree

of nutrient attenuation. This investigation, therefore, created the opportunity for using

in situ sensors for indicating real-time function of stormwater treating CW. The

intense diel metabolism can lead to large variability in nutrient attenuation and should

be considered in assessing wetland performance rather than solely relying on long-

term monthly snapshots. Mature and senescent macrophytes need periodic harvest to

minimize leaching of nutrients.

5) Initiatives need to take to improve DO levels within the CW and this could

be achieved through removal of floating debris, re-circulation of effluents during the

dry periods and supply artificial aeration pumping air to the system.

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Chapter 4

Stormwater nutrient attenuation in a multi-

compartment constructed wetland

This chapter is based on the manuscript published as: T. M. Adyel, C. E. Oldham and

M. R. Hipsey (2016) Stormwater nutrient attenuation in a constructed wetland with

alternating surface and subsurface flow pathways: event to annual dynamics. Water

Research, 107, 66-82.

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Abstract

Among different Water Sensitive Urban Design (WSUD) options, constructed

wetlands (CWs) are widely used to protect and support downstream urban waterways

from stormwater nutrients. This analysis assessed the nutrient attenuation ability of a

novel CW in Western Australia that combined multiple alternating surface flow (SF)

and laterite-based subsurface flow (SSF) compartments within a parkland context to

improve the urban landscape and amenity. The CW was designed to maximise

nutrient reduction despite experiencing a large range of hydrologic conditions, from

low transit time nutrient-rich pulses during the wet periods to prolonged low to zero

flow conditions during the dry periods. The CW design was further complicated by

the possibility of ungauged water inputs after wet antecedent conditions, seasonal

macrophyte senescence and a recirculation system to maintain flow during the dry

periods. From analysis of data over a range of time scales, we determined that overall

the CW attenuated up to 62% total nitrogen (TN) and 99% total phosphorus (TP)

loads during dry weather conditions, and 54–76% TN and 27–68% TP during episodic

flow pulses. N species attenuation was dominant in the SF compartments, while P

species were attenuated mostly within the SSF compartments. Nutrient accumulation

in the sediments, and above and below ground biomass of the macrophytes were

found to increase during the early stages of operation, suggesting the system reached

equilibrium within four years. Further, by comparing trends in nutrient attenuation

within the context of diel changes in high frequency oxygen data from different

compartments, it was demonstrated that changes in dissolved oxygen were related to

changes in nutrient concentration across the CW, although interpretation of this was

complicated by changing hydro-climatological conditions. The implementation of this

CW concept in a highly seasonal Mediterranean climate demonstrates that urban

liveability and environmental health can both be improved through careful design.

Keywords

Dissolved oxygen; Ecosystem service; Laterite; Multi-compartment; Wetland

metabolism

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4.1 Introduction

Stormwater runoff is an important source of nutrients in urban environments,

mobilising and redistributing both organic and inorganic forms from point and non-

point sources within the catchment (Hatt et al. 2009; Gasperi et al. 2011; Burns et al.

2012; Zgheib et al. 2012). Due to the rapid expansion of impervious areas in cities

around the globe, the magnitude of nutrient loads associated with untreated

stormwater are increasing, and subsequently creating significant challenges for

downstream receiving water environments (Walsh et al. 2005b; Brown et al. 2009;

Burns et al. 2012; Fletcher et al. 2013). These challenges include issues associated

with water quality impairment due to eutrophication such as the growth of algal

blooms, the generation of anoxia or hypoxia, and, in extreme cases, the large-scale

mortality of fish and aquatic biodiversity, all of which reduce the recreational amenity

of waterways within the urban landscape (Taylor et al. 2004; Miller & Boulton 2005;

Kaushal et al. 2008; Cuffney et al. 2010; Hathaway et al. 2012). There are, therefore,

increasing efforts to monitor and actively manage stormwater quality to safeguard and

restore urban waterways.

A number of approaches are currently using to reduce stormwater nutrient

loads from urban areas. These approaches have collectively been referred as Water

Sensitive Urban Design (WSUD) in Australia, Sustainable Urban Drainage Systems

(SUDS) in the UK and Low Impact Design (LID) in the USA and New Zealand

(Fletcher et al. 2014). A commonly used practice within such approaches is the

implementation of a constructed wetland (CW) for stormwater retention and nutrient

attenuation prior to discharge into a sensitive downstream watercourse (Hatt et al.

2006; Burns et al. 2012; Fletcher et al. 2013). CWs are engineered green bioreactors

(Mitsch & Jorgensen 2003), that attenuate nutrient loads via a range of

biogeochemical and hydrological processes occur within the water, soils/sediments,

aquatic macrophytes and associated microbial communities (Fink & Mitsch 2007;

Huang et al. 2011; Chang et al. 2013; Wu et al. 2014; Vymazal & Kröpfelová 2015).

Biogeochemical processes depend on the availability of oxygen and carbon sources,

abundance of macrophytes and microorganisms, soil/sediment properties, formation of

biofilms and the presence of artificial filter media (Huang et al. 2011; Malaviya &

Singh 2012; Saeed & Sun 2012). Hydrological processes, such as dilution and riparian

and/or hyporheic exchanges, can control the extent of biogeochemical transformations

within the CWs (Fink & Mitsch 2007). In particular, higher hydraulic retention time

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(HRT) increases the contact of water with different elements of the CW, which is

thought to promote nutrient attenuation.

Individual CW can be classified according to the predominant direction of

flow, the position of the water surface relative to soil or substrate, the presence or

absence of macrophytes, and the degree of saturation of the underlying soil (Fonder &

Headley 2013). Open water or surface flow (SF) and subsurface flow (SSF) CWs are

the two most common types for treating urban stormwater. In isolation, a SF or SSF

CW would usually attenuate certain nutrient species more than other species. For

example, CWs with continuous flow and ample oxygen exhibit efficient ammonia

(NH3) attenuation by promoting nitrification, whereas CWs with low oxygen

concentrations show greater nitrate (NO3) attenuation by promoting denitrification.

CWs with both SF and SSF systems (i.e., a ‘multi-compartment’ wetland) can

combine the advantages of single stage SF and SSF CWs and provide better overall

nutrient attenuation (Ávila et al. 2014; Ayaz et al. 2015; Vymazal & Kröpfelová

2015). Since the hydrological and biogeochemical conditions differ within

compartments of such CWs, some parts of the system can experience an aerobic

environment, while other parts are anaerobic, and some may be net autotrophic whilst

others are net heterotrophic, leading to different attenuation efficiencies for nitrogen

(N), phosphorus (P) and inorganic and organic species of each. Whilst multi-

compartment systems are promising, the optimal design of such systems for nutrient

attenuation remains uncertain. Furthermore, it is even less clear how to optimise

design of a multi-compartment CW system that experiences a Mediterranean climate,

where the flow rates become very low during the dry summer and some compartments

may dry out. In this case, additional water supply and/or recirculation may be required

to keep the CW active and maintain amenity of the system. Episodic water pulses

during the wet winter periods make nutrient attenuation more difficult due to low

HRT that limit the extent of biogeochemical reactions. Therefore, large flow

variability throughout the year makes the optimization for nutrient attenuation within

multi-compartment systems challenging. Although some studies have investigated the

long-term performance of single stage CW (Gu et al. 2006; Mustafa et al. 2009), to

the best of our knowledge there are no published data on the long-term performance of

a multi-compartment CW in an urban landscape for stormwater nutrient attenuation.

In order to optimise the design of multi-compartment CW, a better

understanding of their long-term nutrient attenuation dynamics and responses to flow

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variability is therefore necessary. In the present study, we assessed the performance of

a multi-compartment CW on the Swan Coastal Plain (SCP) in Western Australia

(WA), implemented to support the restoration of the nearby Canning River. The CW

was designed to include three SF and two laterite-based SSF compartments, and a

summer recirculation scheme. We explored the dynamics of nutrient attenuation over

event, seasonal and annual scales over a 7-year periods (2009–2015) through a

synthesis of historical meteorological data, water quality and quantity data, high-

frequency oxygen data, and sediment and macrophyte quality data. We aimed to

explore the following questions: (a) What is the comparative contribution of different

compartments of the study site to nutrient attenuation? (b) How do flow conditions

(low flow/base flow, high flow) influence the nutrient attenuation of the system? (c)

What is the particular contribution of sediments and macrophytes to nutrient

reduction? (d) How do dissolved oxygen (DO) concentrations vary between the

compartments and can daily oxygen fluctuations be used as a proxy of wetland

process dominance? The research findings highlight the relative difference between

the SF and SSF compartments, and the large seasonal variability in performance based

on changes in oxygen dynamics and retention time. The results were used to estimate

the overall nutrient reduction that occurred since wetland construction and aspects of

the design that enhance performance were discussed. Finally, we also demonstrated

that the multi-compartment design offers additional eco-recreational amenity,

providing other ecological services important for biodiversity protection and

increasing urban liveability.

4.2 Materials and methods

4.2.1 Site background

The study site, the Wharf Street Constructed Wetland (WSCW), is situated in

Canning, WA (Figure 4. 1). The climate of the site is Mediterranean with most of the

rain occurs from June to September (long term annual average 770 mm) and dry hot

summers with temperatures reaching an average maximum of 32 °C in January and

February. The catchment is characterised by a shallow groundwater table (often 2–3 m

below ground) and highly transmissive Bassendean sands. During the summer dry

months, groundwater top-up, recirculated water and drained irrigation water are the

principal water sources to the CW. During the wet season, stormwater runoff from

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78

residential, commercial and industrial areas is captured by surface and subsurface

drainage systems and discharged into the CW.

The WSCW has a total area of approximately 1ha and receives stormwater

from approximately 129ha of urban area drained by the Wharf Street Main Drain

(WSMD), before discharging into the Canning River. The WSCW started operation in

2009, while laterite-based SSF compartments were only incorporated in October 2012

and the system has been hydraulically connected since then. The SSF compartments

were initially built (in 2009) with recycled concrete materials (RCM), however, the

RCM were heavily abraded during installation and degraded further in situ providing

elevated alkalinity in the SSF components; several attempts were made to reduce the

alkalinity without success. In June 2012, approximately 1500 m³ of RCM were

removed (all of the SSF1 and roughly half of the SSF2) and replaced by 25–40 mm

screened and washed laterite aggregates. After incorporation of the laterite-based SSF

compartments, a continuous flow through the WSCW was finally established. The

WSCW is lined by in situ clays that restrict groundwater exchange with the system.

For our current research, we divided the WSCW into four different

compartments (Figure 4. 1): (a) compartment 1: SF1 with inlet (W1) and outlet (W2),

(b) compartment 2: laterite-based SSF1 with inlet (W3) and outlet (W4), (c)

compartment 3: laterite-based SSF2 with inlet (W5) and outlet (W6), and (d)

compartment 4: SF2 with inlet (W7) and outlet (W8). The first two open water bodies

of the WSCW are connected through a narrow vegetated channel and considered as

the SF1 compartment. Some portion of water can be by-passed the SSF1 compartment

during the high flow conditions of the wet periods. The minimum water level in the

WSCW was maintained during the dry summer by a pump-back system that

recirculated water from W8 to W1 (Figure 4. 1). It was estimated that the recirculation

system operated for 157.5 h per week (at night-time) at a flow rate of 4500 L/hr

during the dry periods and delivered about 300 m3 water during 2011 and about

2245 m3 from October 2013. Local groundwater was also used intermittently to top-up

the WSCW, keep the system active and maintain the aesthetic landscape during the

hot summer when natural water flows were nearly zero. Additional ungauged water,

especially during the stormwater pulses, entered the system through the ornamental

lake (OL) and Bebington Court Drain (BCD). The BCD catchment contains mainly

residential area with semi to high traffic way, and enters approximately 50 m upstream

of the main outlet of the WSCW.

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Figure 4. 1 (a) Map of the Wharf Street Constructed Wetland indicating sampling locations of surface water, flow, sediment and macrophyte and DO.

The ornamental lake (L) and Bebington Court Drain (W7) deliver ungauged water during episodic storm events. Flow rates were measured at inflow

(1) station from 2010 to 2013 and inflow since 2013. (b) Cross-section of the flow path through alternating SF and SSF compartments. Additional

pipes allow SSF1 to be by-passed under high flow conditions and half of SSF2 is covered by grass. Elevation from inlet to outlet is about 0.3 m.

a)

b)

W1 W8

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4.2.2 Data collection

4.2.2.1 Meteorology

Solar radiation data was obtained from the Department of Agriculture and

Food (DAFWA) weather station located approximately 3.8 km north-west of the

WSCW. Daily rainfall data was obtained from the Department of Water (DoW) and

the Bureau of Meteorology (BoM) stations that were approximately 0.3 km north-west

and 7 km north-south of the WSCW, respectively.

4.2.2.2 Water quantity

5-min intervals water discharge and level data were collected at the WSCW

inflow and outflow stations. The main inflow was measured via a structure comprising

a rock riffle (primary flow control) with a set of three by-pass pipes (under the riffle)

and a hydrostatic water level probe to provide water stage information. The outflow

was measured at the concrete V-notch weir using a water level transducer in a float

well system. A detailed water balance of the WSCW was previously provided by

(Adyel et al. 2015b).

4.2.2.3 Water quality

Fortnightly or monthly unfiltered and filtered water samples (July 2009 to August

2015) were collected from the inlet and outlet of the various compartments as

indicated above. Additional opportunistic water samples were also collected from

2013 to 2015. Water samples were filtered on-site using 0.45 μm membrane filters,

stored on ice until returning to the laboratory, and then frozen until analysis (Table

4.1). Historical water samples were analysed for filtered ammonia (NH3), filtered total

oxidised nitrogen (NOx), total Kjeldahl nitrogen (TKN), dissolved organic nitrogen

(DON), unfiltered total nitrogen (TN), filtered reactive phosphorus (FRP) and

unfiltered total phosphorus (TP). Opportunistic samples were analysed for NH3,

filtered nitrite (NO2), filtered urea nitrogen (UreaN), filtered total nitrogen (FTN), TN,

FRP, filtered total phosphorus (FTP), TP, dissolved organic carbon (DOC) and

dissolved inorganic carbon (DIC) using Lachat Quick Chem procedure (APHA 2012).

We calculated other nutrient parameters i.e., NOx, filtered nitrate (NO3), particulate

nitrogen (PN), dissolved inorganic nitrogen (DIN), DON, filtered non-urea organic

nitrogen (NUON), particulate phosphorus (PP) and dissolved organic phosphorus

(DOP) and total dissolved carbon (TDC) based on the analysis results of opportunistic

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samples (Table 4. 1). During the historical water sampling, in situ DO concentrations

were recorded. We also measured 10-min intervals DO concentrations and saturation

at the middle of SF1 and SSF1 compartments from July 2014 to July 2015 using a

miniDOT DO logger (PMA, USA).

Table 4. 1 Summary table of spatial and temporal dynamics of studied parameters, data type,

sampling frequency and data source for the Wharf Street Constructed Wetland assessment.

Component Parameter Data type Sites Duration Sampling

frequency

Analytical

method

Data

source

Surface

water quality

NH3, NOx,

TKN,

DON, TN,

FRP, TP

Historical W1, W2,

W3, W4,

W5, W6,

W7, W8

July 2009

to May

2015

Baseflow

sampling

(fortnightly

to monthly)

APHA

(1998)

DoW

TN, TP W1, W8 Event

sampling (2

to 3-hr

intervals)

APHA

(1998)

DoW

NH3, NOx,

NO2, NO3,

FTN, TN,

UreaN,

DIN, PN,

DON,

NUON,

FRP, FTP,

TP, PP,

DOP, DIC,

DOC, TDC

Opportunistic W1, W2,

W3, W4,

W5, W6,

W7, W8

November

2013 to

May 2015

Baseflow

sampling

(fortnightly

to monthly)

APHA

(2012)

This

study

DO Historical W1, W2,

W3, W4,

W5, W6,

W7, W8

July 2009

to May

2015

Baseflow

sampling

(fortnightly

to monthly)

Logger DoW

Continuous Within

SF1 and

SSF1

July 2014

to July

2015

10-min

intervals

miniDOT

DO logger

This

study

Sediment

quality

TKN or

TN, TP,

TOC

Historical S1, S2,

S3

June 2010

to May

2014

Mainly half

yearly

GHD

(2008)

DoW

Macrophyte

quality

TN, TP Historical M1, M2,

M3

November

2010 to

May 2012

Mainly half

yearly

GHD

(2008)

DoW

Analysed nutrient species: NH3: Filtered ammonia; NOx: Filtered total oxidised nitrogen; NO2: Filtered nitrite; UreaN: Filtered

urea nitrogen; FTN: Filtered total nitrogen; FRP: Filtered reactive phosphorus; FTP: Filtered total phosphorus; TN: Unfiltered

total nitrogen; TP: Unfiltered total phosphorus; DIC: Dissolved inorganic carbon; DOC: Dissolved organic carbon.

Calculated nutrient species: NO3: Filtered nitrate = NOx - NO2; DIN: Filtered inorganic nitrogen = NOx + NH3; PN: Particulate

nitrogen = TN – FTN; DON: Dissolved organic nitrogen = FTN – NH3 – NOx; NUON: Filtered non-urea organic

nitrogen = DON – UreaN; PP = Particulate phosphorus = TP – FTP; DOP: Filtered organic phosphorus = FTP – FRP; TDC: Total dissolved carbon = DIC + DOC.

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4.2.2.4. Sediment and macrophyte properties

Sediments were sampled at three locations such as S1, S2 and S3 (Figure 4. 1),

on average every six months from June 2010 to May 2014. Total number of samples

in each point was 17. S1, S2 and S3 were located at the first open water pond of SF1

compartment, the end of SF1 compartment and the open pond after SSF1

compartment, respectively. Average sediment sampling depth was around 10–15 cm.

The sediment sampling methodology is described in detailed by (GHD 2008).

Sediments were analysed for TKN or TN, TP and total organic carbon (TOC).

The WSCW was planted with aquatic macrophytes, including Baumea

articulata, B. rubiginosa, B. preissii, Carex appressa, Juncus kraussii, Schoenoplectus

validus and Typha domingensis by the South East Regional Centre for Urban

Landcare (SERCUL). Macrophyte samples (n = 51) were collected using quadrats

(0.065 m2) at three locations (M1, M2 and M3) (Figure 4. 1), at four to seven month-

intervals from November 2010 to May 2012. Macrophyte samples were analysed for

TKN or TN and TP in the above ground biomass (AGB) such as shoots and leaves and

below ground biomass (BGB) such as roots and rhizospheres (GHD 2008).

4.2.3 Data analysis

4.2.3.1 Hydrological assessment and its contribution on nutrient attenuation

A water balance was estimated for the WSCW using 5-min intervals flow data

from the main inflow and outflow. When the total incoming water volume (Vinfow) was

higher than the outgoing water volume (Voutfow), the water balance was considered

negative and the WSCW gained water (Voutflow < Vinfow). The water balance was

considered positive when volume of outgoing water was higher than volume of

incoming water (Voutflow > Vinfow); under these conditions the WSCW lost water.

Hydrograph studies were performed considering the inflow and outflow rate

under different rainfall patterns and antecedent conditions (dry and wet). We

partitioned the flows into two regimes: (a) high flow, when the flow rate was >

0.005 m3/s and (b) base flow, when the flow rate was < 0.005 m

3/s. For base flows, the

yearly mean nutrient concentrations at the inlet and outlet were derived from the

historical and opportunistic data in order to define typical dry weather concentration

(DWC). Event mean concentration (EMC) as mg/L was estimated based on the

detailed event analyses where intra-event data were used to estimate load reductions:

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𝐸𝑀𝐶 = ∑ 𝑉𝑖 ×𝑛𝑖 𝐶𝑖/𝑉𝐸 (4.1)

where Vi is the volume proportional to the flow rate at ith timestep (m3), Ci is the

nutrient concentration at ith timestep (mg/L), n is the total number of samples and

VEVE is the total runoff volume across an event (m3).

Since the effectiveness of event nutrient attenuation depends on the size of the

event, the relationship between HRT and attenuation was factored into and applied to

each event that occurred. Load reduction was calculated on the occasions when

simultaneous nutrient concentration and flow data at the main inlet and outlet were

available. In this case, the total volume of water that passed through the inlet and

outlet, total nutrient load, and EMC of nutrient at W1 and W8 were calculated as:

𝐿 = 𝑄𝑖 × 𝐶𝑖 (4.2)

𝐿𝐴 =∑ 𝐿𝑖−∑ 𝐿𝑜

∑ 𝐿𝑖 × 100 (4.3)

where L is the load (mg/s), Qi is the flow rate at ith timestep (m3/s), Ci is the nutrient

concentration at ith timestep (mg/L), LA is the load attenuation (%), Li is the load at

the inlet (mg/s) and Lo is the load at the outlet (mg/s).

4.3.2.2 Nutrient attenuation within compartments

Load estimation and reduction through each compartment was not possible due

to lack of flow data in each compartment. Therefore, nutrient attenuation was

estimated by computing the standardised delta concentration (SDC) as %, defined for

each compartment as:

𝑆𝐷𝐶 =𝐶𝑖𝑛𝑙𝑒𝑡−𝐶𝑜𝑢𝑡𝑙𝑒𝑡

𝐶𝑖𝑛𝑙𝑒𝑡 × 100 (4.4)

where Cinlet is the nutrient concentration at the inlet (mg/L) and Coutlet is the nutrient

concentration at the outlet (mg/L) of the compartment. Details of the SDC approach

were provided elsewhere (Adyel et al. 2015a; Adyel et al. 2015b). Moreover, multiple

sources W6 and W7 delivered ungauged water and nutrients to the SF2 compartment.

Therefore, SDC_ave, a modified version of SDC, was applied that considered average

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nutrient concentration of W6 and W7 as the inflow concentration for the SF2

compartment.

4.3.2.3 Nutrient pool estimation in sediments and macrophytes

The sediment TKN or TN and TP pools were estimated for three sampling

locations assuming that each sampling location was representative of a specified area

as:

𝑁𝑀𝑠 = 𝑁𝐶𝑠 × 𝐵𝑠 × 𝐴𝑠 × 𝐷𝑠 (4.5)

where NMs is the sediment nutrient mass (kg), NCs is the sediment nutrient

concentration (mg/kg), Bs is the sediment bulk density (kg/m3), As is the sediment area

(m2) and Ds is the sediment depth (m).

TKN or TN and TP pools in AGB and BGB were estimated, assuming that each of the

sampling site was representative of a specified area of the WSCW, as:

𝑁𝑀𝑏 = 𝑁𝐶𝑏 × 𝐷𝑊𝑏 × 𝐴𝑏 × 𝑄𝑏 (4.6)

where NMb is the biomass nutrient pool (kg), NCb is the biomass nutrient

concentration (mg/kg), DWb is dry weight of the biomass (kg), Ab is the biomass area

(m2) and Qb is the quadrat area (0.0625 m

2).

4.3.2.4 Oxygen variability

Nutrient attenuation was correlated to changes in DO concentrations or delta

DO (ΔDO) as mg/L or DO saturation (ΔDOsat) as %, defined as:

ΔDO = DOmax - DOmin (4.7)

where DOmax is the maximum DO concentration (mg/L) or saturation (%) during the

afternoon and DOmin is the minimum DO concentration (mg/L) or saturation (%)

during the morning.

Total daily exposure of solar radiation over the period achieving DOmin and

DOmax was computed from available meteorology data. The average monthly ΔDOsat

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and solar exposure were then calculated to investigate the change in DO saturation

over months and seasons.

4.3 Results

4.3.1 Long term dynamics of nutrient quality

Nutrient concentrations changed along the multiple compartments, with higher

concentrations at the main inlet and BCD (W7) (Figure 4. 2). There was a sharp

reduction in the average concentrations of NH3, FRP and TP at the outlet of the SF1

compartment, while NOx and TN concentrations slightly reduced and DON

concentrations increased. The SSF1 compartments received nutrients at lower

concentrations as they had been treated in the SF1 compartment, and further

processing within the SSF1 decreased nutrient concentrations (Figure 4. 2). However,

in the SSF2 compartment, the average outlet (W6) concentrations of NH3, FRP and

TP were slightly higher compared to that at W4. In addition to W6, W7 delivered

nutrients to the SF2 compartments and therefore influenced the nutrient dynamics of

the compartment and overall system. At the main outlet (W8), TN concentrations were

within the Australian and New Zealand Environment and Conservation Council

(ANZECC) guideline (1.2 mg/L) and Healthy River Action Plan (HRAP) (1.0 mg/L)

target for 89 and 81% of the sampling events, respectively. TP concentrations at W8

were within the ANZECC guideline (0.065 mg/L) and HRAP target (0.1 mg/L) for 95

and 86%, respectively of the sampling events.

Nutrient concentrations at the inlets and outlets of the different compartments

were averaged over the periods defined as ‘dry’ (December to May) and ‘wet’ (June to

November) (Table 4. 2). NH3, TKN and DON concentrations at W8 compared to at

W1 were higher during the dry periods, while NOx and TN concentrations were

higher during the wet periods. FRP and TP showed relatively similar concentrations at

W1 and W8 irrespective of the periods. Since 2013, additional nutrient species were

measured in the surface water samples (Table 4. 2). The wet periods showed marginal

higher FTN, DIN, NUON and PP and concentrations at W8 than that measured during

the dry periods, while the dry periods showed two to three times higher concentrations

than the wet periods concentrations particularly for FTP and DOP. NO3 concentrations

at W8 during the wet periods were 20 times higher than that measured during the dry

periods. DOC concentrations were three to four times higher during the wet periods

than the dry periods (Table 4. 2).

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Figure 4. 2 Trends of (a) NH3, (b) NOx, (c) TKN, (d) DON, (e) TN, (f) FRP and (g) TP

nutrient concentrations along the Wharf Street Constructed Wetland from 2009 to 2015.

Horizontal lines and open squares in each box plot represent the annual median and mean

concentration, respectively. W1, W2, W4, W6, W7 and W8 represent the inlet of the

SF1/main inlet, outlet of the SF1, outlet of the SSF, outlet of the SSF2, Bebington Court Drain

and outlet of the SF2/main outlet, respectively. Horizontal solid and dotted lines of each box

represent the ANZECC guideline and HRAP target, respectively.

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Table 4. 2 Spatial and temporal variability of nutrient concentration (mg/L) in the WSCW. The dry and wet period represents six months of December

to May and June to November, respectively.

SF1 SSF1 SSF2 SF2

Inlet (W1) Outlet (W2) Inlet (W3) Outlet (W4) Inlet (W5) Outlet (W6) Inlet (W7) Outlet (W8)

Dry Wet Dry Wet Dry Wet Dry Wet Dry Wet Dry Wet Dry Wet Dry Wet

2009-2015

NH3 0.13±0.02 0.07±0.01 0.30±0.19 0.03±0.00 0.03±0.01 0.06±0.02 0.04±0.02 0.01±0.00 0.01±0.00 0.02±0.00 0.04±0.01 0.02±0.00 0.08±0.02 0.03±0.00 0.03±0.01 0.02±0.00

NOx 0.08±0.02 0.33±0.05 0.09±0.04 0.25±0.05 0.04±0.01 0.20±0.06 0.06±0.01 0.18±0.04 0.04±0.02 0.22±0.08 0.11±0.04 0.21±0.06 1.08±0.14 1.91±0.28 0.07±0.02 0.30±0.06

TKN 0.78±0.09 0.94±0.12 0.94±0.18 0.64±0.03 0.75±0.05 0.61±0.04 0.48±0.14 0.32±0.03 0.79±0.13 0.60±0.09 0.41±0.08 0.29±0.04 0.48±0.05 0.51±0.05 0.66±0.04 0.59±0.03

DON 0.31±0.07 0.52±0.04 0.56±0.07 0.47±0.04 0.42±0.07 0.47±0.08 0.36±0.06 0.31±0.05 0.39±0.04 0.52±0.11 0.30±0.05 0.28±0.05 0.30±0.05 0.36±0.06 0.46±0.04 0.45±0.04

TN 0.82±0.08 1.37±0.12 0.84±0.09 0.83±0.05 0.76±0.05 0.81±0.07 0.49±0.10 0.56±0.05 0.88±0.14 0.89±0.12 0.48±0.08 0.59±0.08 1.65±0.19 2.26±0.26 0.67±0.04 0.90±0.08

FRP 0.05±0.01 0.03±0.00 0.02±0.01 0.02±0.00 0.02±0.01 0.02±0.00 0.01±0.01 0.01±0.00 0.03±0.02 0.02±0.00 0.01±0.00 0.01±0.00 0.04±0.01 0.02±0.00 0.02±0.00 0.02±0.00

TP 0.19±0.04 0.15±0.03 0.07±0.01 0.05±0.00 0.08±0.01 0.04±0.00 0.03±0.02 0.01±0.00 0.08±0.02 0.04±0.01 0.02±0.01 0.02±0.00 0.15±0.08 0.04±0.00 0.04±0.01 0.04±0.01

2013-2015

NO2 0.01±0.00 0.01±0.00 0.01±0.00 0.01±0.00 0.00 0.01±0.00 0.01 0.00±0.00 n/a 0.73±0.07 n/a 0.01±0.00 n/a n/a 0.01±0.00 0.01±0.00

FTN 0.55±0.05 0.95±0.10 0.45±0.06 0.69±0.04 0.38 0.77±0.06 0.48 0.66±0.09 n/a 0.02±0.00 n/a 0.55±0.09 n/a n/a 0.56±0.10 0.72±0.07

UreaN n/a 0.02±0.01 0.00 0.02±0.00 0.05±0.03 n/a 0.02±0.01 n/a 0.25±0.43 n/a 0.01±0.00 n/a n/a n/a 0.03±0.01

PN 0.42±0.19 0.58±0.42 0.35±0.16 0.19±0.06 0.40 0.03±0.04 0.09 0.07±0.11 n/a 0.22±0.09 n/a 0.09±0.07 n/a n/a 0.18±0.07 0.01±0.03

DIN 0.14±0.10 0.39±0.11 0.07±0.06 0.22±0.07 0.01 0.19±0.06 0.14 0.27±0.09 n/a 0.20±0.08 n/a 0.22±0.05 n/a n/a 0.11±0.08 0.25±0.08

NO3 0.08±0.06 0.33±0.10 0.05±0.04 0.20±0.07 0.01 0.16±0.06 0.12 0.26±0.09 n/a 0.51±0.08 n/a 0.20±0.05 n/a n/a 0.08±0.08 0.23±0.07

NUON 0.40±0.11 0.55±0.05 0.38±0.11 0.46±0.05 0.36 0.53±0.07 0.34 0.38±0.03 n/a 0.02±0.01 n/a 0.32±0.13 n/a n/a 0.46 0.49±0.04

FTP 0.05±0.01 0.05±0.01 0.05±0.02 0.03±0.01 0.02 0.02±0.00 0.00 0.01±0.00 n/a 0.04±0.02 n/a 0.01±0.00 n/a n/a 0.06±0.04 0.03±0.01

PP 0.14±0.02 0.19±0.10 0.09±0.04 0.04±0.01 0.09 0.02±0.00 0.01 0.00±0.00 n/a 0.01±0.00 n/a 0.01±0.01 n/a n/a 0.01±0.04 0.02±0.00

DOP 0.01±0.00 0.01±0.00 0.01±0.00 0.01±0.00 0.01 0.00±0.00 0.00 0.00±0.00 n/a 8.92±1.96 n/a 0.00±0.00 n/a n/a 0.04±0.03 0.01±0.00

DIC 31.08±7.81 16.38±4.05 26.01±7.70 13.23±3.52 27.81 13.10±3.10 28.50 15.85±4.87 n/a 45.73±6.93 n/a 6.39±3.47 n/a n/a 26.34±5.09 12.17±2.89

DOC 8.61±1.64 32.68±8.43 9.44±2.51 30.31±7.61 9.64 35.70±8.95 8.95 34.96±8.27 n/a 54.65±5.45 n/a 44.97±6.39 n/a n/a 8.63±2.65 27.70±7.04

TDC 39.68±9.14 49.06±6.08 35.45±10.15 43.54±5.87 37.45 48.80±6.12 37.45 50.81±3.91 n/a 0.73±0.07 n/a 51.35±5.46 n/a n/a 34.97±7.52 39.88±6.08 aANZECC guideline values bHRAP target values

n/a not applicable

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4.3.2 Nutrient attenuation across compartments

The overall nutrient attenuation as SDC in the WSCW was estimated by

considering nutrient concentrations at W1 and W8. The annual average attenuation of

NH3 (62.7%; p < 0.0001), FRP (57.6%; p < 0.0001) and TP (65.8%; p < 0.0001) were

always positive, while TKN, NOx, DON and TN showed periodic attenuation and

release (Figure 4. 3). The average attenuation of NOx and TN was around 15%, while

DON showed negative attenuation (−58.23%). The SF1 compartment showed mostly

NOx attenuation with a few NOx releases, while the SSF1 showed NOx releases at the

beginning of operation followed by alternating release and attenuation (Figure 4. 4).

The SF1 showed alternating annual attenuation and release of TN, while annual

average TN attenuation at the SSF1 was always positive.

Based on the mean SDC, the different compartments of the WSCW showed

variable attenuation and release of nutrients (Figure 4. 5, Table 4. 3 and Table 4. 4).

Total attenuation of DIN during the dry periods was almost 1.5 times higher than that

during the wet periods, while DON and DOP were released from the system during

the dry periods. DOC attenuation during the dry periods was three times higher than

that measured during the wet periods, while DIC released from the WSCW during the

wet periods. DOC also released from the SF1 compartment.

4.3.3 Impact of hydrological variability on nutrient attenuation

The water balance and nutrient dynamics of the WSCW were influenced by

hydrological variability including rainfall, flow pattern, water volume input, water

recirculation and antecedent conditions. A negative water balance (Voutflow < Vinfow)

was observed during rainfall events after antecedent dry conditions (Figure 4. 6). Only

50% of the total inflow volume reached the outflow, with the remaining water either

stored in the different compartments or lost from the system via evapotranspiration. A

positive water balance (Voutflow > Vinfow) was observed when recirculation pumping

coincided with rainfall after wet antecedent periods (Figure 4. 6). The volumetric

contribution from ungauged areas (VCUA) to the WSCW decreased over time with

average values of 56% (2011), 39% (2012) and 27% (2013). This may have been

impacted by the decrease in mean annual rainfall and the increase in dry antecedent

conditions.

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Figure 4. 3 Nutrient attenuation in the Wharf Street Constructed Wetland from 2009 to 2015.

Bar plots (a, c, e, g, i, k and m) show attenuation over individual sampling periods, where box

plots (b, d, f, h, j, l and n) show annual average attenuation. 100% SDC indicates compete

attenuation while negative SDC indicates nutrient release. Horizontal lines and open squares

in each box plot represent the annual median and mean SDC, respectively.

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Figure 4. 4 Nutrient attenuation in the SF1 (a, b, e, f, i and j) and SSF1 (c, d, g, h, k and l)

compartment of the Wharf Street Constructed Wetland from 2009 to 2015. Bar plots (a, c, e,

g, i and k) show attenuation over individual sampling periods, where box plots (b, d, f, h, j and

l) show annual average attenuation. 100% SDC indicates compete attenuation while negative

SDC indicates nutrient release. Horizontal lines and open squares in each box plot represent

the annual median and mean SDC, respectively.

Based on the simultaneous flow and nutrient monitoring data captured over six

storm events, we assessed the EMCs and loads of TN and TP at the inlet and outlet. A

typical flow pattern during a storm event (17–20 November 2009) and subsequent

nutrient concentrations are presented in Figure 4. 7. The event was accompanied with

30 mm of rainfall and about 65% of the incoming water reached the outlet. The

WSCW attenuated 35 and 62% of the incoming TN and TP loads, respectively.

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Figure 4. 5 Nutrient attenuation within different compartments of the Wharf Street Constructed Wetland: (a) SF1, (b) SSF1, (c) SSF2, (d) SF2 and (e)

overall system. 100% SDC indicates compete attenuation while negative SDC indicates nutrient release. Horizontal lines and open squares in each

box plot represent the median and mean SDC, respectively.

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Table 4. 3 Nutrient attenuation (%) during the dry and wet period in the Wharf Street Constructed Wetland. The dry and wet period represents six

months of December to May and June to November, respectively.

SF1 SSF1 SSF2 SF2

Dry Wet Dry Wet Dry Wet Dry Wet

NH3 39.53±46.64 57.45±6.80 -101.02±86.78 69.17±5.78 -102.62±60.99 14.47±9.61 40.87±24.95 12.25±13.08

NOx 21.63±27.08 49.23±5.96 -273.82±136.12 -238.58±89.08 -532.12±168.95 -271.48±98.65 91.17±2.93 82.21±5.84

TKN -48.67±23.68 14.54±4.44 38.30±13.92 47.02±3.77 47.10±6.71 49.09±4.50 -62.79±16.74 -38.05±11.68

DON -181.85±118.97 0.24±3.10 42.57±5.06 42.63±4.88 23.55±12.39 44.85±6.60 -68.71±27.01 -45.86±17.45

TN -6.77±13.53 27.65±5.07 37.23±10.01 30.35±4.03 39.44±6.56 31.20±7.22 46.14±6.55 43.18±9.08

FRP 54.47±7.84 34.07±12.20 -19.39±69.55 57.48±5.72 57.38±21.70 3.91±41.27 50.71±9.14 44.47±6.77

TP 54.38±6.44 54.78±4.51 63.59±16.84 81.97±1.45 74.32±1.64 56.65±8.14 19.83±11.65 0.58±12.50

Table 4. 4 Nutrient attenuation (%) during the dry and wet period in the Wharf Street Constructed Wetland. The dry and wet period represents six

months of December to May and June to November, respectively.

SF1 SSF1 SSF2 Overall

Dry Wet Dry Wet Wet Dry Wet

NO2 38.58±12.81 15.12±8.04 -26.35 42.97±6.22 15.97±21.30 34.41±15.41 21.35±9.74

FTN 16.79±9.39 24.83±4.82 n/a 20.34±6.43 25.18±9.78 -1.67±12.66 22.57±5.70

UreaN n/a 21.24±9.54 78.54 54.29±13.81 26.62±17.66 n/a -46.09±60.43

PN -41.79±109.29 80.79±13.49 -838.84 252.22±92.77 83.81±28.79 40.30±34.65 139.87±36.43

DIN 67.02±11.00 37.96±7.73 -1529.95 -47.02±34.97 -50.68±54.11 32.69±13.07 19.80±17.31

NO3 67.30±15.07 37.58±9.84 7.02 -96.54±50.74 -62.93±63.96 44.46±29.62 -9.53±27.48

DON 7.36±6.54 16.93±3.14 7.02 24.76±5.33 42.75±22.99 -4.66±13.96 16.82±4.37

NUON 7.45±6.52 17.32±3.47 82.51 22.61±5.43 43.65±23.61 -11.40 17.11±5.98

FTP 14.62±13.49 38.26±7.62 90.55 74.69±3.00 56.65±15.53 -6.50±42.23 49.11±7.87

PP 41.04±24.60 79.91±20.09 92.77 89.60±4.80 78.48±15.52 93.90±23.36 87.84±12.77

DOP -71.69±98.35 307.24±271.61 -2.47 128.67±7.44 106.82±24.99 -1008.98±1039.86 586.02±539.0

DIC 18.49±10.04 18.64±9.38 7.14 -21.38±12.68 34.64±28.84 12.99±5.69 -15.68±49.16

DOC -5.74±10.96 6.98±4.19 0.00 1.18±7.35 -4.26±18.11 5.66±15.78 15.25±2.74

TDC 13.49±9.74 11.66±4.44 n/a -8.05±5.33 2.80±14.81 11.44±5.73 19.39±5.43

n/a not applicable

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Figure 4. 6 Hydrograph at the inlet and outlet of the Wharf Street Constructed Wetland during

different hydro-climatological conditions: (a) a small rainfall under the wet antecedent

condition, (b) a small rainfall under the dry antecedent condition, (c) a large rainfall under the

dry antecedent condition and (d) frequent rainfall events under the wet antecedent condition.

TN and TP attenuation during the storm events were linked to HRT; the longer

the HRT, the greater nutrient attenuation. We calculated nutrient loads during base

flows or DWC (Table 4. 5). The WSCW attenuated up to 62% TN and 99% TP loads

during the DWC. The WSCW also attenuated about 46% TN and 48% TP loads

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during the high flows. Throughout the operation the system attenuated about 45 and

65% incoming TN and TP loads, respectively from being discharged to the

downstream Canning River.

There were uncertainties in nutrient attenuation estimation when the WSCW

received ungauged water from BCD and/or OL overflow. Under these conditions,

SDC_ave was used, and the average and median of SDC_ave were lower than that of

SDC for all nutrients in the SF2 compartment.

Figure 4. 7 Nutrient concentration and flow patterns at the main inlet (W1) and main outlet

(W8) of the Wharf Street Constructed Wetland during a storm event (17–21 November 2009).

(a) Flow and TN concentration at W1, (b) flow and TP concentration at W1, (c) flow and TP

concentration at W8 and (d) flow and TP concentration at W8. Dotted lines in each box

represent the respective EMC of the nutrients. Tables summarise total water discharge, total

nutrient load and EMC at W1 and W8 during the storm event.

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Table 4. 5 Estimation of nutrient load attenuation in the Wharf Street Constructed Wetland

during the base and high flow conditions.

TN TP

Year Flow

type

Inlet

load

(kg)

Outlet

load

(kg)

Δ Load

(kg)

Load

removal

(%)

Inlet

load

(kg)

Outlet

load (kg)

Δ Load

(kg)

Load

removal

(%)

2010 Base 162.09 83.27 78.82 49 14.492 5.11 9.37 65

High 991.90 242.95 748.94 76 99.71 65.79 33.91 34

2011 Base 18.89 14.02 4.86 26 1.8102 0.49 1.32 73

High 290.17 129.31 160.85 55 29.17 20.60 8.56 29

2012 Base 4.696 1.80 2.89 62 0.939 0.59 0.34 36

High 166.07 67.66 98.41 59 16.69 10.76 5.92 36

2013 Base 25.71 24.95 0.75 3 3.84 0.04 3.79 99

High 324.30 150.57 173.73 54 32.60 23.79 8.81 27

2014 Base 52.25 52.86 -0.60 -1 3.96 3.583 0.37 10

High 490.21 100.66 389.55 79 83.10 26.73 56.36 68

4.3.4 Nutrients storage within sediments and macrophytes

Sediments of the WSCW were potential long-term sink of nutrients. TN or

TKN and TP concentrations were highest at S1 and increased with time. Sediments

were rich with TOC, with concentrations higher at S1 than at S2 between June 2010

and May 2012, while a reverse scenario was observed between October 2012 and

October 2013. The maximum and minimum sediment nutrient pools were observed at

S2 and S3, respectively (Figure 4. 8). There was a sharp increase in nutrient pools at

all sites from October 2013 to May 2014. TN and TOC pools were 8–15 and 100–

8000 times higher, respectively than TP pools. TN and TP pools increased during the

early stage of operation (June 2010 to April 2011), had reduced by October 2011 and

increased thereafter. The net accumulation of sediment nutrients with time, where t is

days since 29 June 2010 or the first sampling date:

TN=0.0027t2–3.2448t+2397; R

2= 0.39 (4.8)

TP=0.0005t2–0.8548t+478.59; R

2= 0.56 (4.9)

TOC=0.0314t2 –40.446t+24649; R

2= 0.55 (4.10)

Aquatic macrophytes such as B. articulata, B. rubiginosa, B. preissii and

S. validus accumulated nutrients (TKN and TP) in AGB and BGB (Figure 4. 9).

B. articulata and S. validus contained higher TKN and TP nutrient pools than other

species, while BGB accumulated more nutrients than that measured in AGB.

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However, macrophytes showed seasonal senescence (Table 4. 6) that can contribute

internal nutrient release.

Figure 4. 8 Nutrient pools of (a) TN, (b) TP and (c) TOC from June 2010 to May 2014 at three

sediment sampling sites of the Wharf Street Constructed Wetland. Error bars indicate standard

error.

Figure 4. 9 Dry biomass and nutrient pools in AGB and BGB of B. articulata from November

2010 to May 2012 at three sampling sites of the Wharf Street Constructed Wetland. (a) Dry

biomass in AGB, (b) dry biomass in BGB, (c) TN pools in AGB, (d) TN pools in BGB, (e) TP

pools in AGB and (f) TP pools in BGB. Error bars indicate standard error. AGB and BGB

indicate above ground biomass and below ground biomass, respectively.

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Table 4. 6 Spatial and temporal variability of physical properties of above ground biomass of

B. articulata per quadrate in the Wharf Street Constructed Wetland.

Time Site No of

Inflores-

cences

Leaf Stage (%) Stem height (m) No of

Stem Mature New Senescent Mean Max. Min.

22/11/2010 M1 3.00±

1.73

79.00±

8.08

5.33±

2.33

15.67±

6.17

1.38±

0.19

2.31±

0.12

0.15±

0.14

108.67±

26.82

22/11/2010 M2 10.00±

0.88

99.00±

11.55

1.00±

0.33

40.00±

11.26

1.66±

0.20

2.48±

0.23

0.64±

0.14

88.00±

2.60

22/11/2010 M3 9.00±

5.57

80.00±

5.13

4.67±

2.73

15.33±

2.40

1.65±

0.16

2.86±

0.15

0.35±

0.18

88.33±

11.20

02/06/2011 M1 6.67±

3.38

65.00±

7.64

6.67±

1.67

28.33±

6.01

1.48±

0.13

2.51±

0.23

0.11±

0.03

90.33±

15.17

02/06/2011 M3 0.33±

0.33

64.33±

19.80

3.00±

1.00

32.67±

20.22

1.92±

0.08

2.38±

0.23

0.17±

0.05

50.67±

3.33

06/10/2011 M1 12.33±

4.41

86.67±

1.20

3.33±

1.20

10.00±

0.00

1.72±

0.08

2.47±

0.19

0.25±

0.16

109.67±

4.84

06/10/2011 M3 6.67±

2.33

91.67±

1.67

4.00±

1.00

4.33±

0.67

1.72±

0.08

2.76±

0.22

0.13±

0.05

93.00±

9.81

03/05/2012 M1 10.67±

2.40

68.00±

9.17

3.67±

1.33

28.33±

8.82

1.69±

0.18

2.59±

0.09

0.20±

0.06

101.00±

7.77

03/05/2012 M3 3.33±

1.20

64.33±

17.70

2.33±

1.33

33.33±

18.33

1.79±

0.34

2.81±

0.35

0.15±

0.08

90.33±

16.15

4.3.5 DO variability

DO levels were higher at the outlet than that at the inlet of the SF

compartments during 65% of sampling times (p < 0.0001). However, DO

concentrations decreased at the outlet of the SSF compartments compared to that

measured at the inlet (Figure 4. 10). Near zero DO levels were observed at the outlet

of the SSF compartments, specifically during the dry periods. A diurnal DO signal

was observed in the SF1 compartment, particularly during the dry periods, with the

maxima and minima DO levels during day and night-time, respectively. DO levels

within the SSF1 increased during the wet periods, after rainfall and flow pulses.

Night-time anoxia (DO < 1 mg/L) was observed during most of the dry months in the

SSF compartments. The trend between DO concentrations and nutrient concentrations

(Figure 4. 11) and ΔDO and SDC (Figure 4. 10) at different compartments was

investigated. NH3 concentrations at the outlet of the SF compartments reduced when

DO concentrations and ΔDO. However, NH3 processing usually generates NOx in

CW, and higher DO levels suppress NOx attenuation. In the presence of ample DO,

FRP attenuated while higher FRP concentrations prevailed at lower DO

concentrations. NOx attenuation in the SF compartments was dominant (R2 = 0.52;

p < 0.0001) at very low ΔDO, probably due to denitrification. NH3 attenuation

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increased (R2 = 0.51; p < 0.0001) and NOx attenuation suppressed in the SF

compartments during the wet periods when higher ΔDO was experienced. FRP

attenuation also responded to ΔDO in the SF1 compartment, however, not as intensely

as NH3. The SSF compartments showed variable nutrient attenuation in response to

ΔDO. Although DO levels reduced in the SSF compartments, attenuation of NH3 and

FRP, and a release of NOx were observed. Moreover, the SSF compartments received

nutrients at low concentrations and therefore, a slight increase/release in

concentrations at the outlet would show large SDC (Figure 4. 10).

4.4 Discussion

4.4.1 Variability in performance within the system and over time

Variability in hydrology, CW design and effective surface area of the CW

influenced nutrient attenuation in the WSCW over time. The WSCW experiences

prolonged low flows and low water levels during the dry summer, and therefore the

recirculation system is needed to maintain a minimum flow rate. Water can be stored

in the open water bodies or SF compartments and the SSF compartments during the

dryer periods and therefore a negative water balance was frequently observed; this

extended the HRT and led to higher nutrient load attenuation (up to 62% TN and 99%

TP).

Incoming water during the storm events contributed to the outflow with a

positive water balance and water discharged for up to 2 days (Figure 4. 6); this was

likely sourced from ungauged inputs such as BCD, direct precipitation and/or

overflow of the OL. The ungauged inputs delivered 27–56% of incoming water

depending on rainfall pattern, season and antecedent dry or wet conditions. The first

few hours of the storm events delivered nutrient in higher concentrations (Figure 4. 7)

due to the first flush effect. Some portion of water travelled from the outlet of SF1 to

the inlet of SFF2 by-passing SSF1 compartment during the high flow conditions that

can reduce overall attenuation capacity. However, during such high flow conditions,

dilution and particle settling are probably important processes of nutrient attenuation.

The presence of macrophytes and tree logs in the SF compartments and laterite in the

SSF compartments facilitate the settling of particulate nutrients by providing

roughness.

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Figure 4. 10 Spatial and temporal trend of DO concentrations in water samples of (a) SF1, (b)

SSF1, (c) SF2 and (d) SSF2 compartment of the Wharf Street Constructed Wetland from 2009

to 2015. Diurnal DO signature at the mid zone of the (e) SF1 and (f) SSF1 compartment

during rainy (6–9 September 2014) and sunny (1–4 March 2015) conditions. Relationship of

ΔDO and SDC NH3 at the (g) SF and (h) SSF compartments, SDC NOx at the (i) SF and (j)

SSF compartments, and SDC FRP at the (k) SF and (l) SSF compartments.

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Figure 4. 11 Relationship between DO and nutrient concentrations in different compartments

of the Wharf Street Constructed Wetland. DO and NH3 concentrations at the (a) SF1, (b)

SSF1, (c) SSF2, and (d) SF2; DO and NOx concentrations at the (e) SF1, (f) SSF1, (g) SSF2,

and (h) SF2; DO and FRP concentrations at the (i) SF1, (j) SSF1, (k) SSF2 and (l) SF2.

The variable redox conditions across the different compartments, and the

variable exposure to solar radiation also impacted nutrient attenuation. The SF and

SSF compartments show higher attenuation of N and P based nutrients, respectively.

The SF compartments are open to air and light those provide the aerobic environment

essential for nitrification and ensure the stability of P absorption. The SF

compartments also provide large area of sediment surfaces and macrophytes that

contribute significantly to the attenuation of incoming nutrients. The SSF

compartments provide increased surface area and anaerobic environments suitable for

the growth of biofilms. The SSF compartments in other CWs have been shown to

support nutrient attenuation by promoting plant root growth and increasing upward,

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downward and sideways mixing of incoming water (Headley et al. 2005; Konnerup et

al. 2009). Nutrient attenuation also depends on inlet concentrations in the different

compartments (Figure 4. 12 and Figure 4. 13).

Figure 4. 12 Relationship between DO and nutrient concentrations in different compartments

of the Wharf Street Constructed Wetland. DO and NH3 concentrations at the (a) SF1, (b)

SSF1, (c) SSF2, and (d) SF2; DO and NOx concentrations at the (e) SF1, (f) SSF1, (g) SSF2,

and (h) SF2; DO and FRP concentrations at the (i) SF1, (j) SSF1, (k) SSF2 and (l) SF2.

Interestingly, DON and NOx periodically released from the SF and SSF

compartments, respectively. The decay of macrophyes and organic matter, and

sediment resuspension can generate DON in the SF systems (Kröger et al. 2007).

Negatively charged ions have a low affinity to laterite, and this may have impacted

NOx attenuation in the SSF compartments. Furthermore, NH3 attenuation generates

NOx that would then increase overall NOx concentrations at the outlet. However, both

DON and NOx were attenuated in the subsequent alternating compartments,

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highlighting the benefits of multi-compartment CW. The WSCW attenuated up to

99% of TP loads, and the sediments, macrophytes and laterite were important sinks of

P. In particular, laterite has previously been shown to adsorb P via ligand exchange

reaction, where phosphate displaces water or hydroxyls from the surface of hydrous

oxides of iron (Fe) and aluminium (Al) (Wood & McAtamney 1996). Cerezo et al.

(2001) found that the addition of Fe improved P retention significantly from 55 to

66% in a CW under semi-arid conditions. We similarly observed correlations between

improved P retention and Al or Fe attenuation in the WSCW, with co-precipitation

likely facilitating attenuation. The SSF compartments were also planted with Carex

that are expected to uptake P.

The alternating SF and SSF compartments utilised in the WSCW exhibited

improved nutrient attenuation than previously found in a single stage CW within 4 km

of the current field site (Ruibal-Conti et al. 2015; Adyel et al. 2016). Furthermore, the

WSCW exhibited higher nutrient attenuation than that found in other multi-chamber

CWs for stormwater nutrient attenuation (Malaviya & Singh 2012). This is

particularly impressive given that most of the previously investigated multi-

compartment CWs were laboratory scale or relatively small with controlled flow rate

and inflow loading, while the WSCW is a full-scale system setting in an urban

catchment, and exposed to prolonged low flows during the dry summer and episodic

pulses during the wet winter.

Different reactions and processes take place simultaneously in multi-

compartment CWs to control nutrient attenuation. Although direct nutrient attenuation

processes were not measured in the WSCW, four distinct patterns (Figure 4. 14) of

NH3 and NOx dynamics across the different compartments were observed. These

patterns included (a) pattern 1: attenuation of both species, (b) pattern 2: NH3 release

and NOx attenuation, (c) pattern 3: NH3 attenuation and NOx release, and (d) pattern

4: release of both species. These patterns can be explained in relation to prevailing

conditions in each compartment, which provides some insight into likely dominant

processes. Pattern 1 was dominant in both SF1 and SF2 compartments probably due to

plant uptake, biomass assimilation and adsorption onto soils, sediments and substrates.

Furthermore, NH3 can also be attenuated via nitrification, partial nitrification and

denitrification (PND) and anaerobic ammonium oxidation (ANAMMOX). The end

product of NH3 attenuation can be further attenuated via denitrification, dissimilatory

nitrate reduction (DNRA) and PND. Connolly et al. (2004) suggested that NH3

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removal in a vertical flow SSF system occurred firstly by adsorption onto the media,

followed by nitrification and then denitrification. These steps are likely to be similar

in the SSF compartments of the WSCW. Pattern 2 occurred occasionally when

nitrification was dominant and denitrification was suppressed. However, NOx release

and NH3 attenuation (pattern 3) was observed more frequently throughout the year in

the SSF compartments. N can also be released (pattern 4) due to desorption, and the

decay of macrophytes and organic matter. While we can suggest the controlling

processes based on ambient conditions, further investigations of the processes

occurring in the different compartments are needed.

Figure 4. 13 Relationship between inlet nutrient concentrations and nutrient attenuation in

different compartments of the Wharf Street Constructed Wetland. NH3 concentrations and

NH3 attenuation at the (a) SF1, (b) SSF1 (c), SSF2, (d) SF2; NOx concentrations and NOx

attenuation at the (e) SF1, (f) SSF1 (g), SSF2, (h) SF2, TN concentrations and TN attenuation

at the (i) SF1, (j) SSF1 (k), SSF2 (l) SF2. Positive SDC and negative SDC indicate nutrient

attenuation and nutrient release, respectively.

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Figure 4. 14 (a) Conceptual relationships between different attenuation pathways of NH3 and

NOX. Measured relationships between NH3 and NOx attenuation in the (b) SF and (c) SSF

compartments of the Wharf Street Constructed Wetland.

Over time, the sediments of the WSCW accumulated one-third of the incoming

nutrient loads. The larger the sedimentation area, the larger the sediment nutrient

pools. For example, S2 was situated in the largest sedimentation area and contained 3–

4 times higher N pools and 2–3 times higher P pools than that found in S1 and S3

(Figure 4. 8). Al and Fe levels increased in the WSCW sediments along with P pools

(Ruibal-Conti et al. 2015; Adyel et al. 2016) supported our previous suggestion that P

co-precipitated with Al/Fe minerals. Other possible routes of nutrient accumulation in

the sediments of CWs include sedimentation, precipitation, chemical reaction,

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adsorption, peat formation and burial (Reddy et al. 1999; Malaviya & Singh 2012).

Occasionally, the sediments nutrient pools of the WSCW decreased over time,

indicating that the sediments acted as a source, possibly due to sediment resuspension,

and nutrient releases driven by the periodic drying and wetting of the riparian zones.

Detailed investigation of the triggers for nutrient release from sediments is needed for

optimization of the system.

After the sediments, aquatic macrophytes in CWs are also important

facilitators of nutrient uptake and assimilation via suitable root-shoot-leaf zones.

Macrophytes of the WSCW accumulated about one-fifth of the incoming nutrient

loads, indicating higher storage than that previously found in temperate climates

(Vymazal 2013b). Macrophytes accumulated more nutrients during the early to

growth stage, particularly for the first two to three years of operation. BGB showed 2

to 3 times higher nutrient pools than that stored in AGB. AGB also demonstrated

seasonal senescence contributing to internal loading of nutrients. B. articulata and

S. validus showed the greatest capacity to assimilate nutrients and therefore the

establishment and growth of these two species could improve nutrient retention across

the system. However, the presence of unsampled macrophytes and the absence of up-

to-date species mapping made macrophyte nutrient pools estimation challenging.

Periodic species coverage count is therefore essential for better estimation of

macrophyte nutrient pools, while the harvest of mature macrophytes prior to summer

senescence is required to ensure the permanent removal of plant-stored nutrients.

Moreover, modelling approach can be incorporated to determine effectiveness of the

system over times.

Some urban water models are capable of predicting the performance of single

stage CWs; however prediction of the performance of multi-compartment CW is

challenging due to variable flow conditions. Typical computational approach such as

MUSIC - Model for Urban Stormwater Improvement Conceptualisation (MDT 2005)

conceptualises the performance of a single stage CW as a 1st order decay reaction

rate, without considering complexities such as different inlet concentrations, ungauged

water inputs, flow patterns, sediment or macrophyte uptake within the context of a

multi-compartment CW. This model underestimated nutrient attenuation during storm

events and overestimated during low flows in the WSCW using default parameters.

Alternative approaches therefore need to be considered for better prediction of

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nutrient attenuation in multi-compartment systems and ultimately the optimization of

their design.

4.4.2 ΔDO as an indicator of wetland metabolism

DO fluctuations (ΔDO) can be used as an indicator of wetland metabolism,

representing the balance between oxygen-consuming heterotrophic processes and

oxygen-delivering autotrophic processes. The strong seasonal drivers in hydrology

and productivity of the CW influence large changes in oxygen metabolism. ΔDO in

the SF1 compartment responded positively to solar radiation with statistical

significance (R2 = 0.76; p < 0.0001) during the dry periods (Figure 4. 15).

Biological, chemical and sediment oxygen demand remain intense in the

warmer and lentic water (Tuttle et al. 2008); all of these contribute to lower the DO

level. Interestingly, we also found periods of low DO and ΔDO during the summer

periods even when the exposure to solar radiation was high (Figure 4. 15a). Likely

causes of this scenario were the thick algal mats, scum, the aquatic fern (Azolla) and

other debris that accumulated as a floating mass in the SF1 compartment during the

summer when water levels dropped to less than 0.3 m. Such floating materials shade

the open water, and inhibit both photosynthesis and atmospheric DO exchange

(Nahlik & Mitsch 2006; Adyel et al. 2017a). At the same time, oxygen consumption

promoted by the respiration of the living floating material and its summer senescence,

settling and decay can increase both water column and sediment oxygen demand

(Chimney et al. 2006). Like many wetlands in Mediterranean environments, the

WSCW alternated between a lentic and lotic phase over the year with subsequent

impact on DO dynamics. DO saturation increased in the lotic phase of the WSCW

compared to lentic phase, most likely due to re-aeration and the flushing or settling of

oxygen demanding substances. Positive ΔDO as a proxy of wetland metabolism was

linked with nutrient attenuation, particularly in the SF compartments. Increased DO

levels in the SF compartments due to reaeration promoted attenuation of NH3 and

FRP. DO levels reduce in the SSF system more likely due to DO consumption by

biofilms, heterotrophic processes and limited interactions with solar radiation and air

(Rajabzadeh et al. 2015).

A ΔDO ∼1–6 mg/L was correlated with up to 90% NH3 and 80% FRP

attenuation in the SF1 compartment indicating autotrophic process. NH3 and FRP

attenuation also occurred in the SSF compartment under negative ΔDO, therefore

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other process including adsorption were probably dominant (Reddy et al. 1999;

Connolly et al. 2004); this needs further investigation. The interpretation of CW

metabolism under different hydro-climatological conditions is complicated and

therefore, requires further exploration.

Figure 4. 15 (a) Monthly ΔDO saturation as a function of solar exposure during the wet and

dry periods in the Wharf Street Constructed Wetland. R2 value is 0.76 during the dry periods.

The wet and dry periods consist of June to November and December to May, respectively.

Horizontal and vertical error bar represent standard error. (b) Standard deviation of ΔDO

saturation during same solar exposure.

4.4.3 Benefits of multi-functional system

In addition to nutrient attenuation, the WSCW can provide non-market

ecosystem services. The site integrates residential areas, a nature park and

downstream sensitive waterways, providing a passive eco-recreation and educational

asset consolidated by safety, amenity and accessibility (Figure 4. 16). The site

enhances the local habitat by returning endemic species and habitat types for flora and

fauna (Synnix 2007). This site experienced mosquito problems (Russell 1999) before

establishment and the CW design ensured a water velocity sufficient to discourage

mosquito larvae. Vegetated wetlands also contain natural predators that control

mosquito population (Greenway et al. 2003).

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Figure 4. 16 Some multi-functional aspects of the Wharf Street Constructed Wetland: (a)

cycling and walking path, (b) the SF1 compartment as a habitat of waterfowl, (c–d) amenity

facilities as (c) barbeque and (d) fishing platform.

The WSCW also has economic significance, and economic value can be

placed on its ecological services as described for other CWs (Moore & Hunt 2012). A

CW designed to treat high nutrient inflows was estimated to be worth USD 3.3 million

over 20 years (Yang et al. 2008). A careful quantification of the value of the

ecological services provided by the WSCW is required to compare it with other man-

made ecosystems. Interestingly, a study in a nearby catchment of WSMD found that

house values increased with decreasing distance to a wetland (Tapsuwan et al. 2009).

The WSCW is located close to a residential area and we would expect it has influence

on the market value of nearby properties. The WSCW multi-compartment landscape

and green infrastructure design concept can be implemented in other areas to enhance

urban livability and ecological sustainability.

a

)

b

)

c

)

d

)

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4.5 Conclusions

The monitoring, management and treatment of urban stormwater nutrients are

essential to safeguard and restore downstream waterways. In this study, we assessed

nutrient attenuation in the hybrid WSCW. Major outcomes of this research included:

1) The research demonstrated the variability in nutrient attenuation from the

event-scale with high frequency data to the annual-scale, and therefore, analysis

provided important empirical evidence justifying how the system changed over time.

Results can serve as an important benchmark for future CW design in the area

experiencing hydrologically diverse conditions i.e., near zero flow to pulse flow

conditions.

2) The study used a novel wetland design and demonstrated the benefit of

alternating SF and laterite-based SSF compartments on the overall nutrient dynamics

in a Mediterranean climate, highlighting that each compartment has its own

characteristic hydrological and biogeochemical variability. The SF and laterite-based

SSF compartments of the WSCW showed higher attenuation of N and P, respectively.

3) The research indicated relative contribution of sediments and aquatic

macrophytes for capturing incoming nutrient loads. The sediments were a larger pool

of nutrients than the dominant macrophytes such as B. articulata and S. validus.

However, seasonal macrophyte senescence and sediments resuspension appeared to

deliver nutrients back to the system.

4) The research explored “wetland metabolism” based on a diurnal changes in

high-frequency oxygen data, as a proxy for CW function and performance. This was

the first example in CW to show diurnal changes in oxygen (or metabolism) were

linked to weather conditions and able to be correlated with changes in nutrient

concentrations and importantly, the degree of nutrient attenuation. This opened up the

possibility for in situ sensors to be used to provide a near-real time measure of

stormwater wetland function.

5) The implementation of this CW concept in a highly seasonal Mediterranean

climate demonstrated that urban liveability and waterways protection can be improved

through careful design. Future CW developments could be justified by performing a

non-market cost-benefit analysis.

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Chapter 5

Storm event-scale nutrient attenuation and

metabolism in constructed wetlands

This chapter is based on manuscript published as: T. M. Adyel, M. R. Hipsey and C.

E. Oldham (2017) Storm event-scale nutrient attenuation in constructed wetlands

experiencing a Mediterranean climate: A comparison of surface flow and hybrid

surface-subsurface flow system. Science of the Total Environment, 598, 1001-1014.

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Abstract

Among different Water Sensitive Urban Design options, constructed wetlands

(CWs) are used to protect and restore downstream water quality by attenuating

nutrients generated by stormwater runoff. This research compared the nutrient

attenuation ability during a diverse population of storm events of two CWs: (a) a

hybrid CW with multiple alternating surface flow (SF) and laterite-based subsurface

flow (SSF) compartments, and (b) a single stage SF CW. Within-storm variability,

nutrient concentrations were assessed at 2 to 3-h intervals at both the main inlet and

outlet of each CW. Dissolved oxygen concentrations of the surface waters were also

monitored at 10-min intervals using high frequency in situ sensors. Nutrient loads into

the CWs were observed to be higher when a high rainfall event occurred, particularly

after longer antecedent dry conditions. Longer hydraulic retention times promoted

higher attenuation at both sites. However, the relative extent of nutrient attenuation

differed between the CW types; the mean total nitrogen (TN) attenuation in the hybrid

and SF CW was 45 and 48%, respectively. The hybrid CW attenuated 67% total

phosphorus (TP) loads on average, while the SF CW acted as a net TP source.

Periodic storm events transitioned the lentic CW into a lotic CW and caused riparian

zone saturation; it was therefore hypothesized that such saturation of organic matter

rich-riparian zones led to release of TP in the system. The hybrid CW attenuated the

released TP in the downstream laterite-based SSF compartments. Diel oxygen

metabolism calculated before and after the storm events was found to be strongly

correlated with water temperature, solar exposure and antecedent dry condition during

the pre-storm conditions. Furthermore, the SF CW showed a significant relationship

between overall nutrient load attenuation and the change in oxygen metabolism during

the storm perturbation, suggesting oxygen variation could be a useful proxy indicator

of CW function.

Keywords

Dissolved oxygen; EMC; metabolism, nutrient load; storm event

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5.1 Introduction

Increasing catchment imperviousness associated with industrial and residential

growth in cities with conventional drainage systems has led to increased volumes and

peak flows from storm events. This stormwater runoff carries a range of pollutants and

nutrients, integrating both point and non-point sources within the urban catchment

(Filoso et al. 2015; Ma et al. 2017b, a). Depending on the pattern of the storm event,

the antecedent dry and wet conditions can influence the periodic build up as well as

the extent of the subsequent wash-off and export of nutrients. Nutrients ultimately

make their way into downstream waterways and can lead to water quality impairment,

such as excessive algal growth or eutrophication, dissolved oxygen (DO) depletion,

fish kills, amenity reduction and disruption of ecological services (Taylor et al. 2004;

Burns et al. 2012; Chen et al. 2012). Furthermore, these storm events can cause flash

floods and river bank erosion, and thereby alter the morphology and hydrograph

characteristics of waterways (Walsh et al. 2012). It is, therefore, increasingly common

practice to retain stormwater within catchments for a period before it is released to

downstream water bodies as part of Water Sensitive Urban Design (WSUD) (Lloyd

2001). One of the frequently implemented WSUD elements for water quality

improvement is the use of constructed wetlands (CWs) to attenuate episodic

stormwater flows and nutrient concentrations (Roy et al. 2008; Fletcher et al. 2013;

Fletcher et al. 2014).

The total load of nutrients exported during episodic storm events depends on

the hydro-meteorological conditions including the amount, duration and frequency of

rainfall, antecedent conditions (dry or wet), and the extent of runoff generation

Episodic water pulses make nutrient attenuation within CWs challenging due to the

low hydraulic retention time (HRT), since this limits the extent to which

biogeochemical reactions can take place. As outlined in previous studies, CWs in

Mediterranean climate experience prolonged periods of low flows, and the

performance of these systems during base flow conditions is highly variable (Adyel et

al. 2016; Adyel et al. 2017a). Furthermore, it is not clear how effectively these CWs

attenuate nutrients during episodic storm events or pulses when loads are the highest.

During low flows, CWs can become stagnant and transition into a lentic stage,

however, increased flow rates and water levels during storm pulses shift them into a

lotic stage. Understanding the significance of this lentic-lotic transition on the overall

nutrient dynamics of a CW is challenging and has not been investigated in detail. We

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have previously found that diurnal change in CW metabolism (the balance of

processes that generate or consume oxygen) was correlated with solar radiation during

base flow conditions (Adyel et al. 2016; Adyel et al. 2017a). However, shifts in

metabolism during storm events have not previously been monitored in CWs. In turn,

understanding the possible linkages between CW metabolism and nutrient attenuation

would be beneficial for CW design and optimization of its function.

In this study, nutrient attenuation during a range of storm events was compared

in two CWs located 4 km apart on the Swan Coastal Plain (SCP) of Western Australia.

These CWs were (a) a hybrid CW with alternating surface flow (SF) and laterite-

based subsurface flow (SSF) compartments, and (b) a single stage SF CW with a

meandering flow path. This research sought to determine the effectiveness of such

CWs for event-scale nutrient attenuation, under a range of antecedent and hydro-

biogeochemical conditions. Oxygen metabolism was explored as a proxy of CW

function and potential indicator of nutrient attenuation. It is envisioned that through

better understanding of the variability of CW function during storm events, this study

will help support the design of improved urban water systems for the protection of the

downstream water quality.

5.2 Materials and methods

5.2.1 Study sites

The first site was the hybrid or multi-compartment Wharf Street Constructed

Wetland (WSCW) that receives stormwater from a 129 ha urban watershed, before

discharging into the Canning River. Approximately 1 ha of the WSCW (Figure 5. 1)

consists of three vegetated and open water SF compartments and two laterite-based

SSF compartments. The WSCW was built in 2009, while the SSF compartments were

incorporated in October 2012. Details of the WSCW are provided in Adyel et al.

(2016).

The second study site was the Anvil Way Compensation Basin (AWCB), an

approximately 0.9 ha meandering single stage SF CW (Figure 5. 2), that receives

stormwater from a neighbouring 360 ha residential, heavy traffic way and light-

industrial catchment. The site was initially built in 2004 as a drainage compensating

basin to retain small amounts of stormwater and reduce the export of stormwater

nutrients to the Canning River. The AWCB was restored to a “living stream” in

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November 2010. Details of the AWCB are described in Adyel et al. (2017a). A

comparison of main features of two CWs is given in Table 5. 1.

5.2.2 Data and field campaign

The study aimed to compare the response of the CWs to several storm events

over the period 2009 and 2015. The assessment of events combined a range of

hydrographic and water quality data. In total 14 events were assessed for changes in

wetland metabolism and 9 events were chosen for nutrient attenuation analysis based

on logistical constraints and data availability. Further procedures of sampling, analysis

and data synthesis are given in following sections.

5.2.2.1 Meteorological and water quantity data

Meteorological data were obtained from the Department of Agriculture and

Food (DAFWA) weather station located approximately 3.8 km north-west of the

WSCW and 5 km north-west of the AWCB. Daily rainfall data was obtained from the

Department of Water (DoW) and the Bureau of Meteorology (BoM). The DoW

station was approximately 0.3 km north-west of the WSCW and 0.8 km north-west of

the AWCB; while the BoM station was approximately 7 km north-east of the WSCW

and 5 km north-east of the AWCB. 5-min intervals water discharge and level data at

the inflow and outflow stations of the WSCW and AWCB were obtained from DoW.

In brief, the main inflow of the WSCW was measured via a structure comprising a

rock riffle (primary flow control) with a set of three by-pass pipes (under the riffle)

and a hydrostatic water level probe to provide water stage information. The outflow of

the WSCW was measured at the concrete V-notch weir using a water level transducer

in a float well system (Adyel et al. 2015b). A Starflow ultrasonic instrument

(UnidataTM, Australia) at the inflow and a float well sensor at the outflow of the

AWCB were used to measure discharge (Ruibal-Conti et al. 2015)

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Figure 5. 1 (a) Map of the Wharf Street Constructed Wetland indicating different sampling points. Water samples were collected at the main inlet

(W1) and main outlet (W8) during storm event flows and W1 to W8 during base flows. The ornamental lake (L) and Bebington Court Drain (W7)

deliver ungauged water during the episodic storm events. Flow rate was measured at inflow(1) station from 2010 to 2013 and inflow since 2013. (b)

Cross-section of flow path through the alternating SF and SSF compartments of the Wharf Street Constructed Wetland. Additional pipes allow the

SSF1 to be by-passed under high flow conditions and half of the SSF2 is covered by grass.

a)

b)

W1 W8

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Figure 5. 2 (a) Map of the Anvil Way Compensation Basin indicating different sampling

points. Water samples were collected at the main inlet (W1) and main outlet (W2) during

storm event flows, and W1, Mars Street Drain or MSD (W2) during base flows. W2 and

possibly groundwater deliver ungauged water during the episodic storm events and wet

periods. S1-S4 and M1-M4 indicate sediments and macrophytes sampling points, respectively.

(b) Cross section of the transect within the riparian zone indicating instrumental set-up and

sampling points. P1, P2 and P3 indicate the porewater monitoring points.

P3

P2

P1

P3

P2

P1

DO loggerDO logger

a)

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Table 5. 1 Comparative description of the Wharf Street Constructed Wetland and the Anvil

Way Compensation Basin.

WSCW AWCB

CW type Multi- compartment or hybrid

(multiple alternating SF and SSF

compartments)

SF

Year of establishment 2009, laterite incorporation in 2012 2004, restoration in 2009

CW Area 1ha 0.9ha

CW shape Multiple rectangular and oval Triangular

Catchment area 129 ha 180 to 360 haa

Specific filter media Laterite in SSF compartments Absence

Groundwater connectivity Absence, but groundwater top-up

performed during the dry summer periods

Possible groundwater

connection, particularly

during the wet winter

Recirculation system Present, particularly during the summer

periods

Absence

Inflow Main inlet, BCD and OL overflow Main inlet, MSD and

possibly groundwater

Outflow Main outflow Main outflow

Water storage Different SF and SSF compartments Meandering channel

Soil type Branded red soil Sandy

Dominant macrophytes Baumea articulata, B. rubiginosa, B.

preissii, Carex appressa, Juncus kraussii,

Schoenoplectus validus and Typha

domingensis

S. validus, B. articulata, B.

juncea, Juncus pallidus and

J. kraussii

BCD: Bebington Court Drain OL: The ornamental lake

MSD: Mars Street Drain aDepending on whether the upstream compensation basin network is hydraulically connected to AWCB

5.2.2 Nutrient data

Nutrient concentrations of water samples were measured at 2 to 3-h intervals

throughout the hydrograph for each storm event at the inlet and outlet of the CWs.

Unfiltered water samples were collected and analysed for unfiltered total nitrogen

(TN) and unfiltered total phosphorus (TP) concentrations (APHA 1998, 2012). The

AWCB water samples were additionally collected and filtered on-site using 0.45 μm

membrane filter, stored on ice until returning to the laboratory, and then frozen until

analysis. Water samples of the AWCB were analysed for filtered ammonia (NH3),

filtered total oxidised nitrogen (NOx), filtered nitrite (NO2), filtered urea nitrogen

(UreaN), filtered total nitrogen (FTN), filtered reactive phosphorus (FRP), filtered

total phosphorus (FTP), dissolved organic carbon (DOC) and dissolved inorganic

carbon (DIC) using Lachat Quick Chem procedure (APHA 2012). Dissolved

inorganic nitrogen (DIN), dissolved organic nitrogen (DON), dissolved non-urea

organic nitrogen (NUON), dissolved organic phosphorus (DOP) and total dissolved

carbon (TDC) within the water samples of the AWCB were calculated based on the

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direct measurements (Adyel et al. 2017a). Detailed sampling duration, number of

samples and hydro-meteorological characteristics including rainfall amount,

antecedent dry days (ADD) and inflow volume of the different events are provided in

Table 5. 2. . Events of the AWCB and WSCW were denoted as AE1 to AE3 and WE1

to WE6, respectively.

5.2.2.3 Dissolved oxygen data and physicochemical data

In situ DO concentrations and saturation were recorded at 10-min intervals

using a miniDOT DO logger (PMA, USA) at the top 20 cm of water column of CWs

(first SF compartment of the WSCW and meandering channel of the AWCB). These

points represented the area subject to influence by periodic solar exposure and flow

variation. DO dynamics during the pre- and post-storm events were considered during

14 occasions from August 2014 to July 2015. An additional DO logger (D-opto, New

Zealand) was also installed at the main outlet (W3) of the AWCB during first event

(AE1), and at the main inlet (W1) during second event (AE2) and third event (AE3) to

measure DO levels at 10-min intervals. Additional DO data were also compared with

DO data that obtained from meandering water column of the AWCB. Moreover,

physicochemical parameters of the meandering water column of the AWCB were also

monitored in every minute during AE1 and AE2 using an AAQ water quality sonde

(Advance Technology, Japan).

Table 5. 2 Event campaigns and associated hydro-meteorology for the assessment of the

Wharf Street Constructed Wetland and the Anvil Way Compensation Basin.

Event Date Event

sampling

duration

(hrs)

No of

samples

at inlet &

outlet

Rainfall

(mm)

ADD

(day)

Inflow

volume

(m3)

Outflow

volume

(m3)

Site 1: The WSCW

Event 1 (WE1) 17-20 November 2009 70.00 15 & 15 31.20 3 17056 11700

Event 2 (WE2) 22-24 March 2010 50.00 9 & 8 40.80 23 6408 6599

Event 3 (WE3) 20-21 May 2011 27.00 8 & 8 30.30 1 1928 2518

Event 4 (WE4) 1-3 February 2012 48.00 7 & 8 20.50 4 1329 444

Event 5 (WE5) 7-10 May 2014 73.00 13 &13 58.00 0 9722 9144

Event 6 (WE6) 17-20 June 2014 70.00 12 &12 59.20 5 18361 14970

Site 2: The AWCB

Event 1 (AE1) 11-19 March 2015 28.00 12 &12 2.60 38 1239 336

Event 2 (AE2) 6-12 April 2015 47.00 12 &12 21.20 0 17210 19699

Event 3 (AE3) 15-18 May 2015 95.00 12 & 11 65.20 11 86605 111495

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5.2.2.4 Soil porewater monitoring at the AWCB

Periodic wetting and drying can change the oxidation reduction potential (Eh)

of soils and water, and Eh would then influence nutrient processing within the riparian

zone and porewater. Eh and porewater nutrient concentrations of the riparian soils of

the AWCB were therefore additionally monitored at three points (P1, P2 and P3)

along a transect extending from the water's edge through to the riparian zone (Figure

5. 2b). P1, P2 and P3 were approximately 60, 40 and 20 cm below the soil surface and

each point was horizontally separated by 50 cm. Three Eh sensors (Sensorex, USA)

were inserted vertically into these points and connected to a data logger (DaqPro,

USA), recording at 30-min intervals. One suction cup (UTM, Germany) was also

placed at each point (same depth of Eh sensors) with the other end attached to

sampling bottles (500 mL capacity). The suction cups periodically collected water

samples from the soil porewater and stored them for later analysis. A perforated PVC

pipe was inserted up to 40 cm below the soil surface in the transect. A CTD

(conductivity, temperature and depth) diver (Schlumberger, Germany) was placed at

the bottom of the pipe. The CTD pressure changes were compared with an on-site

atmospheric Baro diver (Onset HOBO, USA). Electrical conductivity (EC),

temperature and water pressure were monitored at 10-min intervals.

5.2.3 Water balance

Water balance was estimated during nine events (Table 5. 2), using gauged

flows at the main inflow and outflow of the two CWs. When total incoming water

volume (Vinflow) was higher than outgoing water volume (Voutflow), the scenario was

considered a negative water balance (Voutflow < Vinflow). A positive water balance

(Voutflow > Vinflow) was observed when the volume of outgoing water was higher than

the volume of incoming water. These are described in Adyel et al. (2016) for the

WSCW and in Adyel et al. (2017a) for the AWCB.

5.2.4 Nutrient attenuation estimation during events

Nutrient loads passing through the inlet and outlet of the two sites were

calculated to estimate nutrient load attenuation:

𝐿 = 𝑄𝑖 × 𝐶𝑖 (5.1)

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𝐿𝐴 =∑ 𝐿𝑖−∑ 𝐿𝑜

∑ 𝐿𝑖 × 100 (5.2)

where L is the load (mg/s), Qi is the flow rate at ith timestep (m3/s), Ci is the nutrient

concentration at ith timestep (mg/L), 𝐿𝐴 is load attenuation (%), 𝐿𝑖 is the load at the

inlet (mg/s) and 𝐿𝑜 is the load at the outlet (mg/s). The total number of sample

collected per event is shown in Table 5. 2.

The event mean concentration (EMC) as mg/L of nutrients at the inlet and

main outlet of two sites were also estimated to indicate volume and time weighted

nutrient concentrations during events as:

𝐸𝑀𝐶 =∑ 𝑉𝑖

𝑛𝑖=1 ×𝐶𝑖

𝑉𝐸 (5.3)

where Vi is the volume proportional to the flow rate at ith timestep (m3), Ci is the

nutrient concentration at ith timestep (mg/L), n is the total number of events

considered and 𝑉𝐸 is the total runoff volume across an event (m3).

The site mean concentration (SMC) as mg/L was defined as the mean EMC

value recorded at the inlet and outlet of the site during all studied events, and was

calculated as:

𝑆𝑀𝐶 = ∑ 𝐸𝑀𝐶𝐸𝑛𝑖=1 × 𝑉𝐸/𝑉𝐴𝐸 (5.4)

where EMCE is the EMC for a particular event (mg/L), VE is the total runoff volume

across an event (m3), n is the total number of events considered for a specific site and

𝑉𝐴𝐸 is the total volume discharged during all the events (m3)

The event flux (EF) as kg/ha was defined as the total delivery of nutrients from

respective catchments during an event, and was calculated as:

𝐸𝐹 =𝐸𝑀𝐶 ×𝑉𝐸

𝐴 (5.5)

where A is the active surface of the catchment that effectively contributed to runoff

(ha), EMC is the event mean concentration (mg/L) and 𝑉𝐸 is the total runoff volume

across an event (m3).

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5.2.5 Metabolism estimation

Metabolism as ∆DO (%) is defined as the daily fluctuation of maximum and

minimum DO saturation in the CW, as:

𝛥𝐷𝑂 = 𝐷𝑂𝑚𝑎𝑥 − 𝐷𝑂𝑚𝑖𝑛 (5.6)

where DOmax is the maximum DO saturation during the afternoon (%) and DOmin is the

minimum DO saturation during the morning (%).

Metabolism was further analysed over four consecutive days before and after

storm perturbation. Average metabolism over four consecutive days before the storm

perturbation, ∆DO̅̅ ̅̅ ̅̅pre (%), was estimated as:

∆𝐷𝑂̅̅ ̅̅ ̅̅𝑝𝑟𝑒 =

∑ (𝐷𝑂𝑚𝑎𝑥𝑖𝑛𝑖=1 − 𝐷𝑂𝑚𝑖𝑛𝑖

)

𝑛 (5.7)

where 𝐷𝑂𝑚𝑎𝑥𝑖 is the average maximum DO saturation per day during the afternoon

before the storm perturbation over four consecutive days (%), 𝐷𝑂𝑚𝑖𝑛𝑖 is the average

minimum DO saturation per day during the morning before the storm perturbation

over four consecutive days (%) and n is number of studied days i.e., 4 days.

Similarly, average metabolism over four consecutive days after the storm

perturbation, ∆DO̅̅ ̅̅ ̅̅post (%), was estimated as:

∆𝐷𝑂̅̅ ̅̅ ̅̅𝑝𝑜𝑠𝑡 =

∑ (𝐷𝑂𝑚𝑎𝑥𝑖𝑛𝑖=1 − 𝐷𝑂𝑚𝑖𝑛𝑖

)

𝑛 (5.8)

where 𝐷𝑂𝑚𝑎𝑥𝑖 is the average of maximum DO saturation per day during the afternoon

after the storm perturbation over four consecutive days (%), 𝐷𝑂𝑚𝑖𝑛𝑖 is the average of

minimum DO saturation per day during the morning after the storm perturbation over

four consecutive days (%) and n is number of studied days i.e., 4 days.

The overall average change in metabolism due to a storm perturbation,

∆(∆DO̅̅ ̅̅ ̅̅ ) (%), was estimated as:

∆(∆𝐷𝑂̅̅ ̅̅ ̅̅ ) = ∆𝐷𝑂̅̅ ̅̅ ̅̅𝑝𝑜𝑠𝑡 − ∆𝐷𝑂̅̅ ̅̅ ̅̅

𝑝𝑟𝑒 (5.9)

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where ∆𝐷𝑂̅̅ ̅̅ ̅̅𝑝𝑜𝑠𝑡 is average metabolism over four consecutive days after the storm

perturbation (%) and ∆𝐷𝑂̅̅ ̅̅ ̅̅𝑝𝑟𝑒 is average metabolism over four consecutive days

before the storm perturbation (%).

5.3 Results

5.3.1 Water balance during events

The negative water balance was observed during WE1, WE4, WE5, WE6 and

AE1, while the positive water balance was observed during WE2, WE3, AE2 and

AE3. For the former, stormwater flooded the CWs, and was stored within the SF and

SSF compartments of the WSCW and the meandering channel of the AWCB.

Additional water other than main inflow came from ungauged sources during the

positive water balance. These ungauged sources included BCD and OL in the WSCW,

and the MSD and possible groundwater in the AWCB. Event hydrographs showed

ongoing storm flows at the outlet for 2–24 h after the cessation of the storm event

indicating ungauged water inputs.

5.3.2 Water quality and nutrient attenuation during events

Physicochemical parameters in the main channel of the AWCB varied over

events. AE1 delivered more turbid water than occurred during AE2. EC reduced by

two-thirds in AE2 compared to that of AE1. AE2 flushed out one-fourth of the

chlorophyll-a that previously existed in the AWCB. pH was slightly reduced within

the AWCB during AE2 (6.8–7) compared to AE1 (7–7.5). No such data were

available in the WSCW.

Nutrient concentrations at the inlet and outlet of the studied CWs varied across

the events. The average outlet TN concentration was higher in the WSCW than that

measured in the AWCB (Figure 5. 3a). A reverse scenario was observed in case of TP

(Figure 5. 3b). The outlet concentrations of TN in both CWs were within the

prescribed Australian and New Zealand Environmental Conservation Council

(ANZECC) guideline and Healthy River Action Plan (HRAP) target. However, TP

concentrations at the outlet of the AWCB increased and exceeded the ANZECC

guideline and HRAP target. This additional TP was likely generated within the system

or from ungauged sources, and had limited time to be attenuated in the AWCB. Water

samples from the AWCB were also analysed for other nutrient parameters. NH3,

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DON, FRP, DOP, DIC and DOC concentrations decreased within the AWCB while

NOx and DIN concentrations increased (Figure 5. 4).

Figure 5. 3 (a) TN and (b) TP concentrations at the inlet and outlet of the Wharf Street

Constructed Wetland and Anvil Way Compensation Basin during different storm events.

Solid circles and solid horizontal lines within individual box indicate the mean and median

value of nutrient at respective storm events. Dashed vertical lines separate two CWs. Bottom

and upper parts of the shaded horizontal panels of TN indicate HRAP target and ANZECC

guideline, respectively and reverse for TP.

Nutrient EMCs were calculated to explore how nutrient concentrations varied

over events in two CWs. EMCs of dissolved and particulate nutrients varied across

spatial and temporal scales. The WSCW received stormwater containing higher TN

and TP EMCs than that received by the AWCB (Table 5. 3). Between the two CWs,

TP EMCs at the outlet were higher in the AWCB. AE1 delivered stormwater at the

inlet of the AWCB with higher EMC of NH3, FTN, DON, FRP, FTP, DOP, DOC,

DIC and TDC. The inlet EMC for NOx, DIN, NO3 and PP was higher during AE3

(Table 5. 4). The average EMC of NH3, DIN, DON, DOP, DOC and DIC decreased

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at the outlet compared to that measured at the inlet; however, the reverse scenario was

observed for NOx and FRP (Table S1). SMCs of incoming and outgoing nutrients also

varied across the CWs. SMC of TN and TP was higher at the WSCW than that of the

AWCB (Table 5. 3).

Figure 5. 4 Nutrient concentrations at the inlet and outlet of the Anvil Way Compensation

Basin during three storm events.

Incoming nutrient loads also showed variability across the two different

catchments. The MSMD catchment delivered a higher nutrient load than that of the

WSMD (Table 5. 3). For example, the AWCB received up to 78.21 kg TN and

7.74 kg TP, while the WSCW received up to 19.14 kg TN and 2.12 kg TP during the

events. Moreover, the MSMD catchment delivered slightly higher nutrient mass per

unit area than that of the WSMD. The AWCB also received higher average inorganic

loads than organic loads of N, P and carbon (C) (Table 5. 4). Storm event nutrient

attenuation varied between the WSCW and AWCB depending on flow conditions.

Typical hydrographs and pollutographs over the storm events are shown in Figure 5.

5. On average, the WSCW attenuated 45% TN and 67% TP loads. Although the

AWCB attenuated 48% TN loads, the CW also released 23% TN loads during AE3.

The AWCB attenuated all nutrient species during AE1. Loads of NH3, NOX and DIN

in the AWCB were attenuated as about 24, 35 and 31%, respectively during AE1,

while NH3, DON, FRP, DOP, DOC and DIC loads generated during AE2 and AE3.

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Overall, the AWCB attenuated inorganic N while released organic N, both inorganic

and organic P and C during the events.

Table 5. 3 Variation of EMC, SMC, EF, load and load attenuation of TN and TP during storm

events in the Wharf Street Constructed Wetland and the Anvil Way Compensation Basin.

5.3.3 Changes of soil porewater properties due to riparian saturation

Saturation can influence the characteristics of riparian zones during

hydrological variability including rainfall and groundwater seepage. Saturation due to

water level change modified Eh, EC and temperature of the riparian zone and

ultimately the nutrient dynamics within soil porewater of the AWCB. Temperatures

within the riparian soil decreased due to saturation and ranged from 15 to 21 °C. EC

sharply reduced after saturation occurred. When the saturated zone started to dry

again, EC of that area increased (Figure 5. 6a). Eh of the riparian soil varied with

saturation and monitoring depth. Eh slowly decreased following the soil saturation and

showed a distinct pattern (Figure 5. 6b). The deepest point of the transect exhibited

reduced conditions (Eh ~ − 340 to − 310 mV), while Eh was slightly higher (ranging

from − 310 to − 295 mV) at P2. P1, the point 20 cm below the soil surface, showed

high variability in Eh, ranging from reducing to oxidizing conditions (Eh ~ − 200 to

Parameter

WSCW AWCB

Storm events

WE1 WE2 WE3 WE4 WE5 WE6 AE1 AE2 AE3

TN EMCinflow (mg/L) 0.83 2.0 1.28 0.90 1.07 1.04 1.02 0.38 0.90

TN EMCoutflow (mg/L) 0.78 1.38 0.72 0.88 0.64 0.72 0.21 0.45 1.11

TN SMCinflow (mg/L) 1.09 0.82

TN SMCoutflow (mg/L) 0.82 1.00

TP EMCinflow (mg/L) 0.11 0.33 0.23 0.20 0.18 0.09 0.21 0.09 0.09

TP EMCoutflow (mg/L) 0.06 0.14 0.06 0.05 0.06 0.05 0.05 0.15 0.16

TP SMCinflow (mg/L) 0.15 0.09

TP SMCoutflow (mg/L) 0.07 0.16

TN loadinflow (kg) 14.09 12.84 2.46 1.20 10.36 19.14 1.26 6.58 78.21

TN loadoutflow (kg) 9.13 9.10 1.28 0.39 5.84 10.82 0.26 0.73 96.43

TN load reduction (kg) 4.96 3.74 1.18 0.81 4.52 8.32 1.00 5.85 -18.22

TN load reduction (%) 35.20 29.13 47.97 67.50 43.63 43.47 79.37 88.91 -23.30

TP loadinflow (kg) 1.96 2.12 0.45 0.27 1.72 1.61 0.26 1.59 7.74

TP loadoutflow (kg) 0.75 0.95 0.14 0.02 0.59 0.73 0.07 2.51 14.19

TP load reduction (kg) 1.21 1.17 0.31 0.25 1.13 0.88 0.19 -0.92 -6.45

TP load reduction (%) 61.73 55.19 68.89 92.59 65.70 54.66 73.08 -57.86 -83.33

TN EF (kg/ha) 0.11 0.10 0.02 0.01 0.08 0.15 < 0.01 0.02 0.26

TP EF (kg/ha) 0.01 0.02 0.00 0.00 0.01 0.01 < 0.01 0.01 0.03

TN SEF (kg/ha) 0.08 0.14

TP SEF (kg/ha) < 0.01 0.02

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140 mV). A reduced Eh at P2 and P1 was likely related to increased organic matter

content of the AWCB.

Table 5. 4 EMC and load variability at the inlet and outlet for nutrient species in the Anvil

Way Compensation Basin during different storm events.

Parameter Events Parameter Events

AE1 AE2 AE3 AE1 AE2 AE3

NH

3

EMCinflow (mg/L) 0.44 0.03 0.22

FR

P

EMCinflow (mg/L) 0.13 0.05 0.05

EMCoutflow (mg/L) 0.04 0.03 0.23 EMCoutflow (mg/L) 0.04 0.10 0.11

Loadinflow (kg) 0.55 0.45 18.98 Loadinflow (kg) 0.16 0.94 4.52

Loadoutflow (kg) 0.05 0.52 19.49 Loadoutflow (kg) 0.05 1.71 9.68

Load reduction (kg) 0.50 -0.07 -0.51 Load reduction (kg) 0.11 -0.77 -5.16

Load reduction (%) 90.91 -15.56 -2.69 Load reduction (%) 68.75 -81.91 -114.16

NO

x

EMCinflow (mg/L) 0.01 0.09 0.32

FT

P

EMCinflow (mg/L) 0.20 0.07 0.06

EMCoutflow (mg/L) 0.00 0.07 0.36 EMCoutflow (mg/L) 0.06 0.13 0.12

Loadinflow (kg) 0.01 1.55 27.38 Loadinflow (kg) 0.25 1.16 5.13

Loadoutflow (kg) 0.00 1.25 31.26 Loadoutflow (kg) 0.07 2.16 10.67

Load reduction (kg) 0.01 0.30 -3.88 Load reduction (kg) 0.18 -1.00 -5.54

Load reduction (%) 100.00 19.35 -14.17 Load reduction (%) 72.00 -86.21 -107.99

FT

N

EMCinflow (mg/L) 0.98 0.33 0.88 P

P

EMCinflow (mg/L) 0.02 0.02 0.03

EMCoutflow (mg/L) 0.21 0.41 1.01 EMCoutflow (mg/L) 0.01 0.02 0.04

Loadinflow (kg) 1.22 5.61 76.05 Loadinflow (kg) 0.02 0.43 2.61

Loadoutflow (kg) 0.26 7.00 87.89 Loadoutflow (kg) 0.01 0.36 3.53

Load reduction (kg) 0.96 -1.39 -11.84 Load reduction (kg) 0.01 0.07 -0.92

Load reduction (%) 78.69 -24.78 -15.57 Load reduction (%) 50.00 16.28 -35.25

PN

EMCinflow (mg/L) 0.03 0.06 0.06

DO

P

EMCinflow (mg/L) 0.07 0.01 0.01

EMCoutflow (mg/L) 0.01 0.04 0.14 EMCoutflow (mg/L) 0.02 0.03 0.01

Loadinflow (kg) 0.04 0.96 5.52 Loadinflow (kg) 0.09 0.22 0.61

Loadoutflow (kg) 0.01 0.73 11.71 Loadoutflow (kg) 0.02 0.45 0.98

Load reduction (kg) 0.03 0.23 -6.19 Load reduction (kg) 0.07 -0.23 -0.37

Load reduction (%) 75.00 23.96 -112.14 Load reduction (%) 77.78 -104.55 -60.66

DIN

EMCinflow (mg/L) 0.45 0.12 0.54

DO

C

EMCinflow (mg/L) 11.40 4.56 3.93

EMCoutflow (mg/L) 0.04 0.10 0.59 EMCoutflow (mg/L) 3.39 6.34 6.08

Loadinflow (kg) 0.56 2.00 46.35 Loadinflow (kg) 14.14 78.53 340.79

Loadoutflow (kg) 0.05 1.77 50.75 Loadoutflow (kg) 4.20 109.06 526.80

Load reduction (kg) 0.51 0.23 -4.40 Load reduction (kg) 9.94 -30.53 -186.01

Load reduction (%) 91.07 11.50 -9.49 Load reduction (%) 70.30 -38.88 -54.58

NO

3

EMCinflow (mg/L) 0.00 0.08 0.30

DIC

EMCinflow (mg/L) 27.33 5.74 2.98

EMCoutflow (mg/L) 0.00 0.06 0.33 EMCoutflow (mg/L) 7.91 8.51 3.29

Loadinflow (kg) 0.00 1.43 25.85 Loadinflow (kg) 33.89 98.83 258.27

Loadoutflow (kg) 0.00 1.10 28.95 Loadoutflow (kg) 9.81 146.51 285.27

Load reduction (kg) 0.00 0.33 -3.10 Load reduction (kg) 24.08 -47.68 -27.00

Load reduction (%) 0.00 23.08 -11.99 Load reduction (%) 71.05 -48.24 -10.45

DO

N

EMCinflow (mg/L) 0.53 0.21 0.34

TD

C

EMCinflow (mg/L) 38.75 10.31 6.92

EMCoutflow (mg/L) 0.16 0.30 0.43 EMCoutflow (mg/L) 11.30 14.85 9.37

Loadinflow (kg) 0.66 3.61 29.70 Loadinflow (kg) 48.04 177.37 599.45

Loadoutflow (kg) 0.20 5.23 37.14 Loadoutflow (kg) 14.01 255.57 811.87

Load reduction (kg) 0.46 -1.62 -7.44 Load reduction (kg) 34.03 -78.20 -212.42

Load reduction (%) 69.70 -44.88 -25.05 Load reduction (%) 70.84 -44.09 -35.44

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Figure 5. 5 Stormwater hydrographs, pollutographs and nutrients dynamics in the Wharf

Street Constructed Wetland from 7 to 11 May 2014: (a) flow rate and TN concentrations at the

inlet, (b) flow rate and TP concentrations at the inlet, (c) flow rate and TN concentrations at

the outlet and (d) flow rate and TP concentrations at the outlet. Stormwater hydrographs,

pollutographs and nutrients dynamics in the Anvil Way Compensation Basin from 12 to 14

March 2015: (e) flow rate and TN concentrations at the inlet, (f) flow rate and TP

concentrations at the inlet, (g) flow rate and TN concentrations at the outlet and (h) flow rate

and TP concentrations at the outlet. Horizontal dashed lines in each box indicate EMC of

nutrients. Tables indicate the total water volume passed through the inlet and outlet, inlet and

outlet load, inlet and outlet EMC, load attenuation and volume of stormwater treated during

the event.

Figure 5. 6 Temporal variability of soil porewater properties in the transect of the Anvil Way

Compensation Basin along with rainfall. (a) Changes in EC and temperature and (b) Eh along

with water level variations during and after rainfall.

Soil porewater samples were analysed to explore the variability in nutrient

concentrations during soil saturation (Figure 5. 7). Nutrient concentrations varied with

sampling depth. Interestingly, P3 showed higher concentrations of NH3, NOx, DIN,

DON, FRP, FTP and DOP compared to other two points. Average DOC and DIC

concentrations were maximum at P1 during AE1, and concentrations slightly

decreased in the following events. Soil porewater nutrient concentrations were

compared with surface water nutrient concentrations. NH3, DON and DIN

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concentrations were 2–3 times higher in the porewater than that observed in the inlet.

NOx, FRP and DOP concentrations were lower in the porewater compared to that of

inlet water, while other parameters i.e., NH3, DIN, DON, DIC and DOC showed

higher porewater concentrations compared to that measured at the inlet.

Figure 5. 7 Nutrient concentrations in porewater samples of the Anvil Way Compensation

Basin during events AE1 and AE2.

5.3.4 DO dynamics during events

High resolution DO data was monitored at 10-min intervals from July 2014 to

June 2015 in the SF1 compartment of the WSCW and the central channel of the

AWCB. DO showed a distinct diurnal signal, with night-time anoxia and day-time

peaks. Fourteen storm events were further assessed to investigate DO dynamics within

the CWs during pre- and post-storm events. Meteorological dry periods (November to

May) showed DO concentrations < 2 mg/L or saturation levels about 5% during the

pre-event in the AWCB at the day-time. However, the pre-event during the wet season

(June to October) exhibited DO concentrations above 6 mg/L. The WSCW showed

slightly higher DO concentrations and saturation levels than that measured in the

AWCB in the pre- and post-event during both dry and wet seasons. The maximum DO

levels were observed between 12:00 to 15:00 h on a diurnal scale during the pre-event.

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Metabolism was estimated over four consecutive days during the pre-and post-event

periods to indicate the function of the CWs at the event scale. Metabolism due to

storm perturbation increased after some storm events in both CWs (Figure 5. 8),

however also showed no change in other storm events; it is unclear the reason for the

difference and this needs further exploration. The post-event metabolism was always

higher in the WSCW compared to that of the AWCB. Metabolism under the pre-event

in the AWCB was correlated with increased solar exposure (R2 = 0.67), water

temperature (R2 = 0.47) and ADD (R

2 = 0.55). After the events, the observed

correlations disappeared as changes in CW volume, flow rate and HRT re-set the

AWCB (Figure 5. 9). A similar pattern was observed in the SF1 compartment of the

WSCW.

The SF1 compartment of the WSCW showed a total of 5 and 6 events with

higher metabolism during the pre- and post-event, respectively, while the AWCB

showed 5 and 3 events with higher metabolism during the pre- and post-event,

respectively. Therefore, positive metabolism was less dominant in the AWCB

compared to the WSCW. However, the SF compartments of the WSCW exhibited

almost double the metabolism even during the pre- and post-event, compared to that

measured in the meandering channel of the AWCB. High ΔDO was observed in the

CWs during the pre-event after prolonged ADD e.g., January 2015 in both sites. DO

concentrations in the water increased after that event, however the water remained

100% saturated for several days and minimal DO fluctuations occurred throughout the

post-event periods.

5.4 Discussion

5.4.1 Hydro-climate and catchment character determine nutrient export

Climatological conditions including rainfall and the number of ADD, and

catchment characteristics including area and land use determine nutrient export to the

CWs. The first few hours of the incoming stormwater usually wash away any loosely

bound soil particles from the catchment and cause higher nutrient loads and turbidity.

Nutrient exports were also higher, when the event was preceded by either long ADD

or when the rainfall intensity was high (Table 5. 2). Storm events with lower rainfall

amount and shorter ADD can deliver limited nutrient loads compared to loads that

were delivered in previous events, and therefore variation in intra-storm nutrient EMC

and loads were observed in the studied CWs (Figure 5. 10). Among three events

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recorded at the AWCB, AE2 consisted lower concentrations of TN and TP. AE2

experienced with single ADD and therefore, nutrients likely to be washed-off from the

catchment prior to the event. ADD also influenced nutrient accumulation in other

catchments, and large rain events were found to have higher erosive capacity (Inamdar

et al. 2015; Gunaratne et al. 2016).

Figure 5. 8 Temporal variability of metabolism in the (a) SF1 compartment of the Wharf

Street Constructed Wetland and (b) the Anvil Way Compensation Basin during four

consecutive days of pre-storm events (∆𝐃𝐎̅̅ ̅̅ ̅̅𝐩𝐫𝐞) and post-storm events (∆DO̅̅ ̅̅ ̅̅

post). Solid

circles and lines in individual boxes indicate mean and median values, respectively. Error bars

of the box plots indicate standard error. Green and yellow panels indicate that significant

positive and negative metabolism, respectively took place during the pre-event conditions

compared to post-event conditions.

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Figure 5. 9 Principal component analysis of different parameters (average over four

consecutive days) during the (a) pre-event and (b) post-event in the Anvil Way Compensation

Basin. Dis: Discharge and SR: Solar radiation exposure.

Hydrological variability also influences nutrient dynamics. Stormwater flows

have the capacity to flush turbid water from the CW (Tuttle et al. 2008) or settle

within the CW, and therefore less turbid water was observed in the CWs at 2 to 3 h

after the cessation of the storm events, when the flow rate was about 0.02 m3/s at the

outflow. The CWs received ungauged water making up to 70% of storm flows; the

ungauged contribution to the WSCW was less than that of AWCB. More importantly,

the AWCB received anoxic groundwater that can lower DO levels in the CW, and

impact the overall nutrient load estimation. The ungauged water also impacted the

overall performance of the system under different flow conditions. For example, when

the contribution of ungauged water was considered, the estimated performance of the

WSCW and AWCB was about 40% higher than the performance when ungauged

ΔDO SR Tem

ADD

Dis

CW volume

HRT

-1

-0.5

0

0.5

1

-1 -0.5 0 0.5 1F

2 (

19.5

6 %

)

F1 (57.60 %)

axes (F1 and F2: 77.16 %) a)

ΔDO

SR

Tem

Rainfall

Dis

CW volume

HRT

-1

-0.5

0

0.5

1

-1 -0.5 0 0.5 1

F2 (

26.6

4 %

)

F1 (48.80 %)

axes (F1 and F2: 75.44 %) b)

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water wasn't considered during base flows (Adyel et al. 2016; Adyel et al. 2017a).

Moreover, stormwater during the events saturates or floods the riparian zones, and

shifts the CWs from a lentic to lotic stage. Such saturation after prolonged dry periods

released nutrients to the system (Table 5. 3).

Catchment properties including soil types, land use pattern, residential or

industrial setting and imperviousness influence nutrient exports to the CWs during

storm events. The area of the MSMD is larger than that of the WSMD. The MSMD

catchment is a combination of residential and semi-industrial area with high traffic

land use, while the WSMD is predominantly a residential area with high traffic.

Therefore, it is expected the MSMD generate higher runoff than that of the WSMD

(Table 5. 2). However, the WSMD delivered higher nutrient loads and showed a

higher SMC, possibly arising from residential gardening lots or activities within the

nearby residential areas. However, the WSMD delivered higher nutrient loads and

showed a higher SMC, possibly arising from residential gardening lots or activities

within the nearby residential areas. Further study is necessary to indicate the exact

contribution of each garden lot or significance of lot size on nutrient delivery after a

storm event to support targeted management.

Figure 5. 10 Intra-storm variability flow and EMC of TN and TP in the (a) Wharf Street

Constructed Wetland and (b) Anvil Way Compensation Basin.

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5.4.2 CWs design and hydrological variability control nutrient attenuation

CW design, effective treatment areas, flow patterns, conditions of

soils/sediments, and the presence of filter media and macrophytes can all be important

drivers of nutrient attenuation. The total available effective area of nutrient attenuation

was higher in the WSCW compare to the AWCB. The WSCW was constructed and

retrofitted more recently than that of the AWCB, and the hybrid nature of the WSCW

provided conditions more suitable for nutrient attenuation. A retrofitted stream-

constructed wetland showed reduced suspended solids and N export to downstream

waters (Filoso & Palmer 2011; Filoso et al. 2015). Moreover, the WSCW contained

alternating SF and SSF compartments that provided aerobic and anaerobic conditions,

respectively for nutrient processing. Similar conditions have previously been observed

in other CWs (Headley et al. 2005; Konnerup et al. 2009; Headley & Tanner 2012) to

support nutrient attenuation. In the WSCW, laterite-based SSF compartments

provided additional roughness for the vertical and horizontal mixing of water and

increased HRT to promote settling of particulate nutrients. Furthermore, laterite is

known to adsorb FRP via ligand exchange reactions, where phosphate displaces water

or hydroxyls from the surface of iron (Fe) and aluminium (Al) hydrous oxides (Wood

& McAtamney 1996). Therefore, the WSCW showed higher P attenuation.

Hydrological variability shaped nutrient dynamics in the CWs during the

events. Decreased flow rate in the CWs usually increased water travel time, and this

increased water travel time correlated with increased attenuation of TN (R2 = 0.45)

and TP (R2 = 0.83) in the WSCW, and attenuation of TN (R

2 = 0.51) and TP

(R2 = 0.96) in the AWCB (Figure 5. 10a) during the events. High flow and low HRT

during events saturated the riparian zones of both CWs and converted the system from

lentic to lotic phase. Subsequently, the riparian zones released nutrients, and therefore,

the CW acted as a net producer of nutrients. Although the WSCW released some

nutrients during riparian zone saturation/flooding, the released nutrients were

attenuated in the subsequent SSF compartments. As there is no alternating

compartment in the AWCB, the released nutrients had very limited opportunity to be

attenuated before downstream release (Table 5. 3). Moreover, high flows result in

changing inundation areas with new areas becoming incorporated into the CW. Hence,

sediment nutrient fluxes or suspension can take place during events that deliver some

nutrients back into the system. In addition, stormwater from MSD travelled very

quickly within the AWCB, and get minimal chance to be attenuated. Therefore, outlet

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concentrations of the AWCB indicated nutrient release from the system, which is

similar to other studies that also have shown that flooding of CWs can release

nutrients (Dupas et al. 2015). Careful investigation of the relationship between flow

and nutrient attenuation is further needed to determine how travel time and reaction or

exposure time interact to control the overall attenuation.

Event flow and saturation may trigger rapid changes of Eh within the riparian

zone and thus initiate rapid nutrient attenuation or release to the water column.

Seasonal groundwater level fluctuations and seepage have previously been shown to

modify Eh in riparian soils and to release already adsorbed nutrients (Hoffmann et al.

2009). Nutrient dynamics in the inflowing or outgoing water were compared within

the riparian porewater of the AWCB. NOx, FRP and DOP concentrations were lower

in the porewater compared to the inflowing stormwater. Biogeochemical processing

can reduce NOx concentrations in the riparian soil via denitrification. Bioavailable

porewater C can be utilized for NOx processing, and therefore NOx concentrations in

the porewater samples were less relative to the inflowing water. However, P releases

were observed from the same soils during large events (AE2 and AE3).

Soils/sediments usually release P in CWs through (a) diffusion due to P concentration

gradient between soils/sediments and the overlying water column and (b) advection

due to microbial activities, bioturbation and vertical movement of porewater (Reddy et

al. 1999). Soil saturation after prolonged dry periods can also cause osmotic shock

and microbial cell lysis that mobilizes and releases P in the CWs (Turner & Haygarth

2001; Dupas et al. 2015). Soil saturation and associated anoxic conditions can also

generate reductive dissolution of Fe(hydr)oxides that release P to the porewater

(Dupas et al. 2015). Ultimately, solubilisation-mobilisation-transport is the likely

route of P processing or release after the saturation of riparian soils in the AWCB.

DOC and DIC concentrations were 3–4 times higher in the porewater than that

at the inlet of the AWCB. Accumulation of organic matter from the decay of plant

biomass, whether from locally planted macrophytes or from material deposited during

seasonal flood events, is a possible source of organic nutrients in the riparian transect.

Sediment re-suspension and transport during events can also deliver the particulate C

accumulated across the riparian zone back to the main basin of the AWCB. DOC

entering the AWCB can be attenuated as it travelled through the wetland, however it

can also be replaced by new DOC produced within the system, ultimately resulting in

a net export. However, the SSF compartments of the WSCW contained no or limited

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dead macrophytes and sediments, and provided roughness of incoming stormwater

ultimately showed higher C attenuation.

Macrophytes, both living and senescent, are important component of CWs.

Both CWs contained a variety of macrophytes (Table 5. 1)

where B. articulata and S. validus were the most common species. Macrophytes are

natural purifiers of CWs that increase hydraulic roughness, promote uniform flow,

enhance sedimentation of particles, provide surface area for small-particle adhesion,

and protect sediments from erosion during the events. Nutrient uptake or release by

macrophytes during the storm events was not measured directly in this study and

needs further investigation.

Figure 5. 11 (a) Nutrient loads attenuation as a function of travel time of water flow in the

Wharf Street Constructed Wetland and Anvil Way Compensation Basin. (b) Relationship

between nutrient load attenuation and changes in metabolism due to storm perturbation in the

AWCB.

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5.4.3 Diurnal DO and metabolism shape nutrient dynamics

Three events in the AWCB were assessed to provide insights into how DO

influence biogeochemical processing of nutrients in diurnal scale. DO concentrations

were usually low during base flow or lentic stage. However, DO concentrations

increased during high flow or episodic pulses that shift CW to lotic stage. Frequent

rainfall also increased DO concentrations due to aeration, and flushing of anoxic water

and other oxygen-consuming substances (Tuttle et al. 2008; Reeder 2011).

Interestingly, nutrients at the outlet exhibited a diurnal trend responding to DO

concentrations and available sunlight. For example, NH3 was attenuated when ample

solar radiation was available, and therefore, nitrification was likely significant.

NOX attenuation was dominant at night and under low DO levels. Therefore, at the

event scale when the system became autotrophic, NH3 attenuation was dominant,

while heterotrophic state supported NOx attenuation via denitrification. FRP

attenuation was also dominant during day-time probably through autotrophic process

under high DO concentrations and solar radiation. The process declined at night and

additional FRP was released from the system most likely from sediments experiencing

low oxygen. The CW was net autotrophic when diurnal DO concentrations increased

from morning to afternoon, indicating that average daily photosynthesis exceeded

respiration.

The use of wetland metabolism as a proxy indicator of CW function was also

considered. Metabolism estimation in stormwater treating CWs is complex as these

systems are dynamic from both hydrological and biogeochemical perspectives. DO

based metabolism was investigated in CWs (Cronk & Mitsch 1994b; Tuttle et al.

2008; Reeder 2011) over short timescales i.e., several days to a week using the lake

metabolism concept (Staehr et al. 2010). Metabolism of a lentic CW during the dry

summer in a Mediterranean climate can be defined using the lake metabolism concept.

However, storm events or frequent rainfall can shift the CW from a lentic to a lotic

system where the lake metabolism concept is not applicable. Therefore, metabolism

was estimated over four consecutive days before and after storm perturbation during

lentic condition. Water temperature, solar exposure, ADD, water volume and water

level influenced DO and daily DO level fluctuation, and ultimately the wetland

metabolism during the events in the AWCB. We attempted to link metabolism due to

the storm perturbation with nutrient attenuation in the AWCB. Positive metabolism

due to perturbation occurred when the post-event metabolism was higher than the pre-

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event metabolism, and negative metabolism occurred when the pre-event metabolism

was higher than the post-event metabolism. It was assumed that nutrients can be

attenuated or released in the CWs due to autotrophic or heterotrophic processes. These

processes use DO and provide a metabolic signature. The positive metabolism showed

a linear link with attenuation of nutrients including NH3 (R2 = 0.84), NOx (R

2 = 0.9),

TN (R2 = 0.76), FRP (R

2 = 0.98), TP (R

2 = 0.75), DIC (R

2 = 0.67) and DOC

(R2 = 0.96) (Figure 5. 11b). Autotrophic microbial processes likely consumed or

converted nutrients to simpler compounds and positive metabolism took place.

Therefore, data supported the concept that microbial processing of nutrients or CW

function could be assessed using a proxy indicator of metabolism. The six storm

events in the WSCW could not be used for this analysis due to the absence of diurnal

DO data. Future research should investigate metabolism in different compartments of

hybrid CW systems during storm events. The time taken by CWs to respond to a

storm event and to return to its pre-storm conditions was assessed across fourteen

events (Figure 5. 8). The SF of the AWCB could maintain its pre-event metabolism

i.e., it was more resistant to the storm-perturbation. The SF AWCB developed low DO

levels compared to the WSCW, due to presence of sludgy sediment, senescent

macrophytes and anoxic groundwater inputs. All of these can contribute to low

metabolism and make the CW more resistant to DO fluctuations during events. Due to

macrophyte senescence and organic rich nutrients in the inflows of the CWs, oxygen

consuming process can be intensified throughout the year and therefore induced

higher daily DO fluctuations. In another study, disturbances to diurnal DO changes

were associated with storm pulses, and the recovery times for stream metabolism were

found as two categories: < 5 days (30% of the disturbances) or > 15 days (70% of the

disturbances) (O'Connor et al. 2012). Large flow pulses can cause full-bed

mobilization that disrupts stream metabolism by destroying periphyton habitats with

long recovery times. Estimation of metabolism resistance and recovery, and their

drivers in stormwater treatment CWs need to be further investigated under different

rainfall and flow patterns to better predict CW performance.

5.5 Conclusions

This work investigated stormwater nutrient attenuation during episodic storm

events in two urban CWs: a hybrid CW with alternating SF and laterite-based SSF

compartments and a meandering SF CW. Major outcome of this research included:

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1) The research indicated that rainfall amount, ADD and catchment

characteristics influenced nutrient wash-off from the catchment after the storm events

and its subsequent delivery to the CWs. The research provided important empirical

evidence showing how the CWs changed over time between anoxic-lentic and oxic-

lotic conditions.

2) The research demonstrated the variability of nutrient attenuation across two

CWs during the storm events. The multi-compartment or hybrid WSCW was more

effective than that of single stage AWCB due to having alternating compartments, a

recirculation system, juvenile macrophytes and the absence of anoxic groundwater as

in the former CW. The study can therefore provide a benchmark for future CW

design.

3) The research indicated both hydrological and biogeochemical processes

were important for nutrient attenuation and transformation not only during events, but

also during the days before and after the storm events. Storm events after prolonged

dry conditions caused riparian zone saturation and subsequently released of P and C

based nutrients. However, laterite-based SSF compartments of the WSCW acted as an

effective P sink.

4) The study showed that CWs can transition between oxic and anoxic

conditions within a diurnal cycle. The study also used high frequency DO data to

explore CW metabolism due to storm perturbation and to indicate its effectiveness as

a proxy indicator of CW function. Positive metabolism was linked with nutrient

attenuation, particularly in the AWCB during the storm events. Water temperature,

solar exposure and ADD influenced such metabolism before any storm event. This

metabolism approach should be explored in other CWs for the prediction of nutrient

attenuation, using easily available and inexpensive DO sensors that can provide real-

time data. This study also indicated that AWCB showed resistance to the metabolism

recovery after the storm perturbations.

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This research investigated stormwater nutrient attenuation in two constructed

wetlands (CWs) on the Swan Coastal Plain in Western Australia at diurnal to decadal

time-scale. Studied CWs were varied in type, flow pattern, surface area and catchment

characteristics. The first site was the Anvil Way Compensation Basin (AWCB), a

meandering surface flow (SF) system that was built in 2004 and retrofitted in 2010.

The second site was the Wharf Street Constructed Wetland (WSCW), a hybrid CW

with multiple alternating SF and laterite-based subsurface flow (SSF) compartments.

Although the WSCW was initially constructed in 2010, a retrofication effort was

conducted in 2012 when laterite-based SSF compartments were incorporated. Both

CWs experience a Mediterranean climate including the prolonged dry summer period

with low or sometimes near zero flows and nutrient-rich episodic storm pulses during

the wet winter. These CWs were further complicated by the summer macrophyte

senescence. This thesis explored the impact of different hydro-climatological and

subsequent biogeochemical variabilities on the nutrient attenuation in two CWs.

This research is amongst the first to investigate stormwater nutrient attenuation

at the same sites across a range of scales, from diurnal to long term (up to 12 years)

time-scale. It is also a rare example of an investigation of CW performance under a

Mediterranean climate with variable i.e., near zero and pulse flow conditions (Chapter

3 to 5). The study also assesses the effectiveness of CW restoration or retrofication on

the nutrient attenuation (Chapter 3) and demonstrates the impact of alternating SF and

SSF compartments on the nutrient attenuation in a hybrid CW (Chapter 4 and 5). The

research used a novel index for estimating nutrient attenuation when ungauged water

sources contribute significantly to the CWs (Chapter 3 to 4). The research also used

wetland metabolism by exploring dissolved oxygen (DO) dynamics as a proxy for the

CW functions. This metabolism index was linked to the nutrient attenuation during the

base flows (Chapter 4) and the episodic storm pulses (Chapter 5).

Antecedent conditions shaped the nutrient delivery from catchment to the CW.

High nutrient load export took place during the event accompanied with higher

antecedent dry days and rainfall amount. The relative extent of nutrient attenuation

varied across spatial and temporal scales. The multi-compartment or hybrid WSCW

showed a better nutrient attenuation per unit area than that of the single stage SF

AWCW by providing alternating multiple compartments, laterite substrate, negligible

groundwater connectivity, water recirculation option, and extending hydraulic

retention time (HRT). Nutrient attenuation was impacted by variation in design, the

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143

effective treatment area, the presence of macrophytes and their age, the available filter

media and its roughness, the availability of alternating aerobic or anaerobic

conditions, and the exposure of wetland compartments to light and air. CW performed

very well (up to 95% efficiency) during first couple of years of operation, however the

perforce reduced in long term and system acted a nutrient source. Nitrogen-based

species attenuation was dominant in the SF compartments of the hybrid CW, while

phosphorus-based species attenuated initially in the SF compartments and then further

polished in the laterite-based SSF compartments (Adyel et al. 2017a).

The CWs experienced strong seasonal hydrology. During the summer

condition, groundwater probably the main source of water in the AWCB, and

recirculation and groundwater top up at the WSCW. Hydrological variabilities i.e.,

flow and HRT shape nutrient attenuation more intensely in hybrid CW than that of SF

CW. Hybrid CW increased nutrient attenuation by extending HRT both during the

base and event flow. Although the SF CW was sensitive to HRT during the event

flows, there was high variability in attenuation during the low flow and HRT

conditions. At diurnal scale CW respond to available solar radiation and DO levels.

For example, ammonia (NH3) was attenuated when ample solar radiation and DO

were available. Filtered total oxidized nitrogen (NOX) attenuation was dominant,

particularly at night and under low DO levels. Therefore, at the event scale when the

system became autotrophic, NH3 attenuation was dominant, while heterotrophic state

supported NOx attenuation. Therefore, care should take during sampling collection

plan to assess CW performance in respect of particular nutrient species. Nutrient

attenuation also varied across the events depending on antecedent condition, total

rainfall, inflowing water and catchment area. Therefore intra storm variability of

nutrient loads and subsequent load attenuation was observed in CW.

The CW restoration had a significant influence on the nutrient attenuation.

Retrofitted six-year old SF CW showed increased the nutrient attenuation, except for

NOx. Replacement recycled concrete material with laterite increased nutrient

attenuation in the hybrid system through providing active sites for nutrient adsorption

and extending water travel time. Sediments and macrophytes stored about one-third

and one-fifth of the incoming nutrient loads, respectively. Nutrient accumulation was

higher during early to mature growth stages, particularly for the first two years of CW

operation, and below ground biomass i.e. roots and rhizospheres stored more nutrients

than above ground biomass i.e., shoots and leaves. However, summer macrophytes

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senescence and sediment flux increased internal loading of “new” material contribute

lower the attenuation capacity of the system. Saturation of riparian zone after

prolonged dry periods led to NOx attention and P release in SF system; however,

released P attenuated in subsequent alternating SSF compartment of the hybrid

system. The lowest NOx concentrations at the deepest point of the AWCB transect

indicating that denitrification was dominant in the porewater. Furthermore senescent

macrophytes and floating debris shaded the water column, prevented light penetration

and resulted in lower daily DO levels.

DO in the CWs showed intense diurnal trends, particularly in the dry summer,

with anoxia at night and maxima during the day-time. As macrophytes shading

reduced DO levels, it subsequently reduced daily metabolism of the CWs. The CW

was net autotrophic when diurnal DO concentrations increased from morning to

afternoon, indicating that average daily photosynthesis exceeded respiration. Diel

oxygen metabolism was correlated with water temperature, solar exposure and

antecedent dry days during the pre-storm conditions. Significant relationship between

overall nutrient attenuation and change metabolism during the storm perturbation in

the SF system suggested this metabolism could be a useful proxy indicator of CW

function (Adyel et al. 2017b).

Spatial heterogeneity of riparian soils in CWs can affect the water distribution

as well as the nutrient attenuation or release under Mediterranean climates. Further

investigation of nutrient dynamics in the riparian - hyporheic zone needs to be

considered. Moreover, the contribution of groundwater to the nutrient inputs during

the events requires more studies in the SF CW. Dimensionless numbers such as the

Damköhler number can be applied to investigate the relative timescales of reaction

and travel/exposure of nutrients in the CWs under different flow regimes. Further

investigation using hydrodynamic-biogeochemical models can parameterize the

nutrient attenuation rates. A careful design of CW needs to be considered, not only for

nutrient attenuation but also to integrate it within residential areas and downstream

sensitive waterways, providing a passive eco-recreation and educational asset

consolidated by safety, amenity and accessibility.

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