1. 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

2. 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

3. 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

4. RBG Soil Water Profiling 10cm 20cm 30cm 50cm 40cm Soil moisture readings: 10 cm, 20 cm, 30 cm, 40 cm and 50 cm

5. RBG Soil Moisture Study – Hourly data 5 mm Daily water use Daytime water extraction

6. 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

7. ET L = K L (Ks x Kmc x Kd) x ETo ET L =Landscape Evapotranspiration ETo=Reference Evapotranspiration KLKL = Landscape Coefficient Ks=Plant Species Factor Kmc=Microclimate Factor Kd=Vegetation Density Factor Ref: Costello and Jones (2000) B. Landscape Coefficient (KL)

8. Determination of K L Ks 0.5 Kmc - Microclimate 1.0 Kd – Density 1.3 Viburnum Bed (5A)

9. Determining K L K L = ETc ETo K L - Landscape coefficient ETc - Determined from soil moisture readings ETo – Weather station reference

10. Site-specific Soil Calibration

11. Accurate determination of water extraction/loss requires site specific soil calibration SF=9.131xVWC 0.049 -9.892 r 2 =0.9122

12. 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

13. Crop Coefficients (K L ) determined for Viburnum Bed, RBG Melbourne (1) Note: (1) Additional irrigation, not scheduled.

14. Typical Landscape Coefficients (K L ) used in summer at RBG Melbourne K L 0.5 K L 0.6-0.7 <K L 0.3 K L 0.4

15. Landscape Coefficient Lessons 1. K L derived from soil moisture readings is valuable in irrigation management. 2. K L 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 K L and adjusted regularly. 4. Note, RBG irrigation schedules. 5 Vegetation standard levels 4 Adjustments for season

16. B. Plant Stress Indicator Evapotranspiration Stress Index (ETSI) ETSI = Evapotranspiration Daily Water Use Based on Daily Water Use from Sentek data and ET o from weather station

17. 1. The size of the evaporative demand and 2. Water uptake by plant and release into the atmosphere (transpiration) Level of Stress indicated by:

18. ETo and Daily Water Use ETo

19. Similar ETo and Declining Daily Water Use Similar ETo Water Stress Declining DWU

20. Critical values of Evapotranspiration Stress Index (ETSI) ETSI Threshold set to 3

21. 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.

22. 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. 2010 Feb. 2011 Summed water in 400 mm and 500 mm soil layers. Water Banking

23. Linking Stormwater to Urban Landscape

24. Stormwater Harvesting – Meeting irrigation demand Storage

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

26. New approaches to irrigation scheduling - Subsoil Storage and Recovery (SSR) -Potential to optimise stormwater harvesting systems -Split scheduling/water balance approach - Applied December = K L 0.5 for top 30 cm compared to K L 0.89 for full 100cm profile Fine roots found in subsoil clay greater from >70- 90 cm depth

27. 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.

28. 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%

29. 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

30. 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

31. Hydrophobicity Water repellence Corrected

32. 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 K L for scheduling 5. Validation using thermal imagery

33. 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