Transcript Slide 1

Lessons from Soil Water
Dynamics in the Management of
Urban Landscapes
Connellan, G., Symes, P., Dalton, M., Buss, P.
& Liu, S.
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
Soil moisture readings: 10 cm, 20 cm, 30 cm, 40 cm and 50 cm
10cm
20cm
30cm
40cm
50cm
RBG Soil Moisture Study – Hourly data
Daytime
water extraction
5 mm Daily water use
Real Time Soil Moisture Sensing
What 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
B. Landscape Coefficient (KL)
ETL = KL (Ks x Kmc x Kd) x ETo
ETL
=
Landscape Evapotranspiration
ETo
=
Reference Evapotranspiration
KL
=
Landscape Coefficient
Ks
=
Plant Species Factor
Kmc
=
Microclimate Factor
Kd
=
Vegetation Density Factor
Ref: Costello and Jones (2000)
Determination of KL
Ks 0.5
Kmc Microclimate 1.0
Kd – Density 1.3
Viburnum Bed (5A)
Determining KL
KL =
KL -
ETc
ETo
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=9.131xVWC0.049-9.892
r2=0.9122
Default versus Site-specific Soil Calibration
Site-specific Calibrated
25.85
30.29
Default Calibrated
• VWC higher or lower
depending on relative
position on calibration
curve
• Same trending
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 0.4
KL 0.6-0.7
<KL 0.3
KL 0.5
Landscape Coefficient Lessons
1. 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
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
Level of Stress indicated by:
1. The size of the
evaporative demand
and
2. Water uptake by
plant and release
into the atmosphere
(transpiration)
ETo and Daily Water Use
ETo
Similar ETo and Declining Daily Water Use
Similar ETo
Water Stress
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.
Water Banking
RBG Melbourne, Herbarium Bed
– Mixed trees and shrubs
SMS used to show trends in total water stored deep root system
layers.
Summed water in 400 mm and 500 mm soil layers.
Feb. 2009
TotalHerbarium400500RBG
Feb. 2010
Feb. 2011
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 Lessons
1. Requires paradigm shift in scheduling:
Maintenance in late summer/autumn
Water 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
Throughfall
measurement
apparatus
Catch cans
Note: Event-based interception loss
can be up to 80-90%
Up to 60% of rainfall can be
intercepted per month
Source: Dunkerley D (2011) Geo.Research Abstracts Vo 13, EGU2011-4016
Effective Rainfall Measurement
Measurements 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.)
Proximate soil is
non-wetted and
very dry
Moisture ‘fingers’ after irrigation
or preferential flow
Hydrophobicity
Corrected
Water repellence
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