lessons from soil water dynamics in the management of urban landscapes
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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) - PowerPoint PPT PresentationTRANSCRIPT
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