lessons from soil water dynamics in the management of urban landscapes

Connellan, G., Symes, P., Dalton, M., Buss, P. & Liu, S.

Lessons from Soil Water Dynamics in the Management

of Urban Landscapes

IAL Conference, Adelaide, 26 June 2012

Areas of Investigation

A. Plant water demand – Landscape Coefficients

B. Plant Stress monitoring (ETSI)

C. Optimisation of soil water storage

D. Effectiveness of irrigation and rainfall

E. Tools – Thermographic imagery

Project: Water management of complex landscapes using soil moisture sensors.

RBG Melb., Melb Uni. & Sentek Pty Ltd

Wireless communication to a web host 5 sensors to

700 mm

RBG Soil Water Profiling

10cm

20cm

30cm

50cm

40cm

Soil moisture readings: 10 cm, 20 cm, 30 cm, 40 cm and 50 cm

RBG Soil Moisture Study – Hourly data

5 mm Daily water use

Daytime water extraction

Real Time Soil Moisture SensingWhat does it tell you? Soil moisture level to initiate irrigation Water available and extracted in each soil

layer

Root system profile

Effectiveness of irrigation and functioning of irrigation system

Effectiveness of rainfall

Soil drainage characteristics

ETL = KL (Ks x Kmc x Kd) x ETo

ETL = Landscape EvapotranspirationETo = Reference EvapotranspirationKL = Landscape CoefficientKs = Plant Species Factor

Kmc = Microclimate FactorKd = Vegetation Density Factor

Ref: Costello and Jones (2000)

B. Landscape Coefficient (KL)

Determination of KL

Ks 0.5

Kmc - Microclimate 1.0

Kd – Density 1.3

Viburnum Bed (5A)

Determining KL

KL = ETc ETo

KL - Landscape coefficient

ETc - Determined from soil moisture readings

ETo – Weather station reference

Site-specific Soil Calibration

Accurate determination of water extraction/loss requires site

specific soil calibration

SF=9.131xVWC0.049-9.892r2=0.9122

Default versus Site-specific Soil Calibration

• VWC higher or lower depending on relative position on calibration curve

• Same trending

Default Calibrated

Site-specific Calibrated

25.85

30.29

Crop Coefficients (KL) determined for Viburnum Bed, RBG Melbourne

(1)

Note: (1) Additional irrigation, not scheduled.

Typical Landscape Coefficients (KL)

used in summer at RBG Melbourne

KL 0.5

KL 0.6-0.7

<KL 0.3

KL 0.4

Landscape Coefficient Lessons1. KL derived from soil moisture readings is valuable in irrigation management.

2. KL varies significantly over time, e.g. daily, weekly. It is not a constant over season or year.

3. Opportunity for increased efficiency if irrigation is matched to current KL and adjusted regularly.

4. Note, RBG irrigation schedules.

5 Vegetation standard levels

4 Adjustments for season

B. Plant Stress Indicator

Evapotranspiration Stress Index (ETSI)

ETSI = Evapotranspiration Daily Water Use

Based on Daily Water Use from Sentek data and ETo from weather station

1. The size of the evaporative

demand

and

2. Water uptake by plant and

release into the atmosphere

(transpiration)

Level of Stress indicated by:

ETo and Daily Water Use

ETo

Similar ETo and Declining Daily Water Use

Similar ETo

Water Stress

Declining DWU

Critical values of Evapotranspiration Stress Index

(ETSI)

ETSI Threshold set to 3

ETSI Plant Stress Indicator Lessons

1.Assessing ETSI in conjunction with monitoring of plant condition provides an enhanced understanding of plant response to soil moisture

2.Identifying ETSI for particular landscape assists in establishing an appropriate refill point.

TotalHerbarium400500RBG

RBG Melbourne, Herbarium Bed – Mixed trees and shrubs

SMS used to show trends in total water stored deep root system layers.

Feb. 2009 Feb. 2010Feb. 2011

Summed water in 400 mm and 500 mm soil layers.

Water Banking

Linking Stormwater to Urban Landscape

Stormwater Harvesting – Meeting irrigation demand

Storage

“Water banking” – Storing water deep in soil profile for use at later

time

New approaches to irrigation scheduling - Subsoil Storage and Recovery (SSR)

-Potential to optimise stormwater harvesting systems-Split scheduling/water balance approach- Applied December = KL 0.5 for top 30 cm compared to KL 0.89 for full 100cm profile

Fine roots found in subsoil clay greater

from >70- 90 cm depth

Water Banking Lessons1.Requires paradigm shift in scheduling:

Maintenance in late summer/autumnWater banking in winter/spring

2. Maximise use of available stormwater

3. Highly suited to many trees of Mediterranean climate origin 4. It can be applied to maintain both tree and landscape health with a minimum of potable water use

5. Insurance/risk management strategy for predicted water scarcity i.e. restrictions/drought.

Measuring Effective Rainfall and Irrigation

Catch cans

Up to 60% of rainfall can be intercepted per

month

Throughfall measurement

apparatus

Source: Dunkerley D (2011) Geo.Research Abstracts Vo 13, EGU2011-4016

Note: Event-based interception loss can be up to 80-90%

Effective Rainfall MeasurementMeasurements are yearly averages and do not include rainfall amounts less than 2 mm (actual annual rainfall reaching the surface is less)

Additional moisture loss is expected in mulch/leaf litter layers

Water preferential flow in water repellent soil of Australian Forest Walk (RBG Melb.)

Moisture ‘fingers’ after irrigation or preferential flow

Proximate soil is non-wetted and

very dry

Hydrophobicity

Water repellence

Corrected

Future Studies – The Next Stage

1.Deep 1.5 m sensors

2. Further in-situ site specific soil calbration

3. Determining Soil Water Stress (Kws) factor with Kc

4. Refining KL for scheduling

5. Validation using thermal imagery

Project Partners– Royal Botanic Gardens Melbourne, Peter

Symes & Steven Liu– Department of Resource Management and

Geography, University of Melbourne, Geoff Connellan

– School of Geography and Environmental Science, Monash University, David Dunkerley

– Sentek Pty. Ltd., Peter Buss, Michael Dalton