Establishing the importance of pollutant attenuation at the aquifer-river interfaceJonathan Smith

Overview of presentationg Background and contextg Objectives of the Agency’s Hyporheic Zone projectg National scale HZ attenuation classification schemeg Reach scale NA process researchg Knowledge transfer and disseminationg Conclusions

Objectives of the HZ projectg to determine the importance of pollutant attenuation

processes in fluvial sediments where there is GW-SW exchange;

g to identify the important attenuation processes for key pollutants at the GW-SW interface;

g to understand the controls on, and variability of, those attenuation processes;

g to apply the new scientific understanding in effective environmental management tools;

g to disseminate the results widely.

Why is this a priority now?g WFD requires integrated

management of surface and groundwater

g GW quality can affect status of surface water body, and vice-versa

g GW-SW interface a biogeochemically active zone

g Existing models and guidance often ignore the interface

The GW-SW interfaceg Water exchange

between stream and subsurface;

g Chemical & temperature gradients; microbiologically active;

g Organic carbon rich compared to aquifer

g ‘Last Chance Saloon’for NA processes

g Habitat - ecotone

Courtesy USGS

Conceptual models

Hyporheic attenuation classificationg Aim: To derive a classification scheme for HZ

attenuation capacity(ies) for British riversg ID processes expected to influence NA capacity

g Sediment thicknessg stream powerg sediment supply

g Sediment permeabilityg Sediment geochemistry

g fOC, CEC, TICg Each derived from contributing factors using national

datasets

g Ranking approach (H/M/L score for each)

Example conceptual model: Fine sediment supply

Land Use Type Rainfall (SAAR)

Sediment Supply

Mean Slope

Sediment Transportability

Total Supply of Fine Sediments

Sediment Transport Potential Matrix

Area of Erodible Land Area of W B catchment

Land use Erodibility

Potential SupplyTranspotability

Potential Fine Sediment Supply

Land Use Type

% Erodible Land adjacent W B

h l

Land use Erodibility

Sediment Supply

W B catch vs corridor supply Decision Matrix

Fine Sediment Supply - WB catchment

Fine Sediment Supply - WB corridor

Drainage Density

Each variable is assigned a H, M, L score

Table 1 Rainfall class data table.Rainfall class SAAR (mma-1)Low < 800 Moderate 800 - 1500High > 1500

Table 2 Slope class data table.Slope class angle (deg)Low <3Moderate 3 - 7High >7

Table 3 Erosivity weighting as defined by slope and rainfall (SAAR).SAAR

Slope Low (1) Moderate (2) High (3)Low (1) 1 1 2Moderate (2) 2 2 2High (3) 2 3 3

Sediment erosivityclasses (slope;SAAR)

HZ classification data

Fine sediment supply

Stream power

High

Low

Aquifer geochemistry

TICƒOC CECHigh NA

Moderate NA

Low NA

Rf = 5, 50, 500nfK

nKR OCOCD

fρρ ..11 . +=+=

Pollutant attenuation class ƒOC (fraction) CEC (meq/100g) TIC (%) Low attenuation potential ƒOC < 0.002 CEC < 5 TIC < 0.2 Moderate attenuation potential 0.002 ≤ ƒOC < 0.02 5 ≤ CEC < 20 0.2 ≤ TIC < 2 High attenuation potential 0.02 ≤ ƒOC < 0.2 ≥ 20 TIC ≥ 2 Extremely high attenuation potential ƒOC ≥ 0.2 No class defined No class

defined

HZ classification

Incr

easi

ng

HZ

NA

po

ten

tial

Classification testingg National nitrate database (GW & SW TON data used for

NVZ designation) re-run for baseflow (Q10) conditionsg Multiple regression analysis used to test whether the HZ

classification criteria are good explanatory variablesg Correlation to sediment thickness, sediment permeability,

fOC and overall HZ factor all statistically significant at P<0.001

g Combined, the HZ factors describe up to ~4% of the variance (R2) in observed baseflow TON concentrations (R2~0.56). This improves existing predictions by ~7%

Results: analysis of varianceAccumulated analysis of variance for Sqrt(P10Ave) model

Max % change in predicted river TON due to change in explanatory variable

Change d.f. s.s. m.s. v.r. F pr. + Crops 1 529.90 529.90 2101.9 <.001 82+ Grass 1 160.63 160.63 637.2 <.001 62+ Urban 1 78.18 78.18 310.1 <.001 38+ Ground 1 13.67 13.67 54.2 <.001 18+ Sediment thickness

2 24.01 12.00 47.6 <.001 30

+ Aquif 3 32.67 10.89 43.2 <.001 22+ BFI 1 10.47 10.47 41.5 <.001 25+ Atmos 1 4.01 4.01 15.9 <.001 11+ SedPerm 2 7.68 3.84 15.2 <.001 20+ DischF 3 10.62 3.54 14.0 <.001 14+ Geo1 (Foc) 2 6.70 3.35 13.3 <.001 16+ Flow 1 1.38 1.38 5.5 0.020 1+ Subsurface perm

2 0.52 0.26 1.0 n.s.

Residual 2702 681.20 0.25 Total 2723 1561.63 0.57

HZ classification: resultsCoefficients of the modified HZ index

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

1 2 3 4 5 6 7 8 9 10

Index level

Size

of c

oeff

icie

nt

Regression coefficient for combined HZ classification factors.

X-axis varies from :

Index = 1 (low NA potential) to

Index = 10 (high NA potential)

Hyporheic zone attenuationg Effort focussed on WFD-directed priority pollutants

g nitrate; g Pollutant causing largest number of ‘WB at risk’ designationsg Potential for denitrification in organic carbon-rich and lower

permeability sediments

g minewaters; g Co-precipitation of Mn with Fe minerals

g industrial pollutants, e.g. chlorinated ethenesg GW-SW exchange

g How variable is the flux across interface?

Flow variability at reach scaleg Natural temperature time

series used as a tracer of GW-SW flux

g Tested in River Tern - lowland, sand-bed river. ca. 75% sand-bed run at study reach

g High BFI: 0.72. Regional GW contours suggest gaining stream throughout catchment

g Diurnal T signal used to determine water flux locally

River Tern: Lowland TSS catchment

Tern streambed temp: time series

(Dynamic Harmonic Regression)

Tern flux variations

024

54 4

42

3

3

2

2

22

3

3

=−⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎠⎞

⎜⎝⎛+⎟

⎠⎞

⎜⎝⎛−⎟

⎠⎞

⎜⎝⎛

zDcv

zHDv

zDHv

zDH

eτλρπ

e

wwcHλρ

=

sediment saturated ofty conductivi thermaleffective waterofdensity

waterofheat specific cnoscillatio re temperatuof period

z t timez,depth at n oscillatio of amplitude Attime0,depth at n oscillatioofamplitudeA

e

w

w

ztz,

t0,

====

∆+==∆+

λρ

τ

Winter roaming survey

Run: sand-bed

Riffle: gravel

Dominant feature:

Geochemical variability in sedimentsg Determine how geochemical properties of sediments

vary withg fluvial geomorphologyg dominant sediment type

g NA-relevant propertiesg ƒOC, CEC, Fe/Mn (total/bio), grain size

A

B

C

EA boreholesLOCAR boreholesGauging stationEdge of floodplain

River Tern study reaches

0 50m

D

A

D

B

C

N

Severn /Tern sediment geochemistry

Geomorphology

Foc

(fra

ctio

n)

tillrunrifflepoollowland reachaquiferalluvium

0.25

0.20

0.15

0.10

0.05

0.00

Boxplot of Foc (fraction) by Geomorphology

Geomorphology

CEC

(meq

/100

g)_1

tillrunrifflepoollowland reachaquiferalluvium

140

120

100

80

60

40

20

0

Boxplot of CEC (meq/100g)_1 by Geomorphology

• ANOVA analysis: sediment chemistry varies with geomorphology and dominant grain size different (P<0.001)

Cation exchange capacity

alluvium aquiferlowland reach pool riffle run till

alluvium 0.999 0.266 0 0.876 0.238 0.968aquifer 0.019 0 0.566 0.0669 0.991

lowland reach 0.0098 0.995 0 0.0217pool 0.0099 0 0riffle 0.0108 0.377run 0.9456till

alluvium aquiferlowland reach pool riffle run till

Mean CEC (meq/100g) 8.55 4.96 9.78 27.8 12.3 5.1 6.6SD 11 1.41 5.94 29.9 19.1 6.37 6.06

Fraction of organic carbon

alluvium aquiferlowland reach pool riffle run till

alluvium 0 0.322 0 0.363 0.0047 0.2577aquifer 0 0 0 0 0

lowland reach 0.004 0.999 0 0.0001pool 0.33 0 0riffle 0 0.0009run 0.998till

alluvium aquiferlowland reach pool riffle run till

Mean foc (fraction) 0.015 0.0003 0.012 0.0495 0.0315 0.0054 0.0027SD 0.019 0.0001 0.0094 0.0637 0.0548 0.0141 0.0031

Tern/Severn geochem.

High NA

Moderate NA

Low NA

Key

Different, P<0.05

Grain size control at catchment scale

R2 = 0.6769

R2 = 0.5466

R2 = 0.6348

0.01

0.1

1

10

100

0 1 2 3 4

Mean grain size (Phi units)

Clay fraction (%)

CEC (meq/100g)

foc (%)

Linear (foc (%))

Linear (CEC(meq/100g))Linear (Clay fraction(%))

Nitrogen cycling

SW

HZGW

SW

Redox Boundary

Nitrification

Denitrification

Nitrification decreases, denitrification variable

NO3-, dO2 , DOC

decrease with depth, NH4+

increases

REDOX potential decreases

Bacterial abundance, pH

decreases, anaerobic

processes increase

Denitrification zone dependent on

microscaleconditions and redox boundary

which is determined by DO, DOC and

sediment properties

Ecological Impact: Greater hydrological exchange and biogeochemical rates means greater significance of hz

High hydrologic exchange and shifting sediments lead to high colonisation beneath

central river bed

Temporal Effects: Denitrification highest in summer and autumn and

lowest in spring and winter due to temperature

and OM effects

Conceptual Model 1Redox-driven N cycling in the hyporheic zone

See: Riess et al. (poster)

0

10

20

30

40

50

60

0.00 50.00 100.00 150.00 200.00

Concentration (mg/l)

Dept

h (c

m)

acetatenitrate

Courtesy Riess et al. 2007

Hyporheic ecologyg International literature also suggests

HZ has a distinct ecology and habitat value, includingg contribution to biodiversity - distinct hyporheos

(permanent hyporheos)g larval stage of many benthic invertebrates

(temporary hyporheos)g refuge in periods of stress?g fish spawning

g New GW Directive encourages future assessment of GW ecosystem quality and protection

g Review of the hypogean ecology of the UK

Parabathynella cf. stygia

Syncarida: 92 species in European GWNone in SW

Courtesy: J Gibert

The Hyporheic Networkg A NERC Knowledge Transfer Network on

groundwater - surface water interactions and hyporheic zone processes;

g Runs 2007 - 2010, to disseminate science to science end-user groups and to highlight their priorities to the research community

g Prepare a Handbook on GW-SW interactions for catchment managers

g Workshops to generate new multidisciplinary research proposals and teams

g Please visit: www.hyporheic.net

Conclusionsg Growing literature suggests GW-SW interface is an important zone for

pollutant cycling and retardationg New classification scheme for the HZ NA capacity improves existing

predictions of SW nitrate concentrationsg GW-SW fluxes can be highly variable, even in ‘simple’ river corridorsg HZ sediments have a greater NA potential (per unit volume) than

adjacent aquifer or drift, but are spatially and temporally heterogeneousg Decreased nitrate (R Tern) and R-Cl (R Tame) concentrations observed

in most organic rich-sedimentsg Sediment geochemistry (CEC, Foc) varies with both geomorphology and

grain sizeg Pollutant attenuation potential varies with river corridor characteristicsg But, is the interface a pollutant attenuation zone or emerging habitat?

Establishing the importance of pollutant attenuation at the aquifer-river interface

Funded by

Completed by

HZ project publicationsg Journal papers

g Gandy, Smith, Jarvis, 2007. Attenuation of mine pollutants.... Sci. Tot. Env., 373, 435-446 g Keery, Binley, Crook & Smith, 2007 (in press). Variability of GW-SW fluxes. J. Hydrol.g Smith & Lerner, submitted. A framework for assessing retardation capacity… QJEGHg Smith et al. submitted. GW-SW interactions: Science into management Hydrol. Proc.

g Environment Agency Reportsg SC030155/1, 2005. Groundwater - surface water interactions in the hyporheic zoneg SC030155/2, 2005. In situ monitoring of hyporheic zone biogeochemistryg SC030155/3, 2005. In situ monitoring of flow at the GW-SW interfaceg SC030155/4, 2005. A review of GW-SW interactions fieldsite infrastructure in the UKg SC030155/5, 2005. A review of nitrate attenuation in the subsurface environmentg SC030155/6, 2006. Attenuation of mine pollution in the hyporheic zoneg SC030155/7, 2007 (in press). A classification scheme for HZ attenuation capacityg SC030155/8, 2007 (in press). Tracer tests for determining hyporheic zone processesg SC030155/9, 2007 (draft). Temp. measurements for determining aquifer-river fluxes

g Please visit: www.publications.environment-agency.gov.uk/