1 / 33

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)

olina
Download Presentation

Lessons from Soil Water Dynamics in the Management of Urban Landscapes

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

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

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

  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. ETL = KL (Ks x Kmc x Kd) x ETo B. Landscape Coefficient (KL) Ref: Costello and Jones (2000)

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

  9. Determining KL KL = ETc ETo KL - 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=9.131xVWC0.049-9.892 r2=0.9122

  12. Default versus Site-specific Soil Calibration Site-specific Calibrated 25.85 • VWC higher or lower depending on relative position on calibration curve • Same trending 30.29 Default Calibrated

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

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

  15. 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 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 ETo 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 Declining DWU Water Stress

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

  21. ETSI Plant Stress Indicator Lessons • Assessing ETSI in conjunction with monitoring of plant condition provides an enhanced understanding of plant response to soil moisture • Identifying ETSI for particular landscape assists in establishing an appropriate refill point.

  22. Water Banking TotalHerbarium400500RBG 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. 2011 Feb. 2010 Feb. 2009

  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 optimisestormwater 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

  27. Water Banking Lessons • 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 Throughfall measurement apparatus Catch cans Up to 60% of rainfall can be intercepted per month Note: Event-based interception loss can be up to 80-90% Source: Dunkerley D (2011) Geo.Research Abstracts Vo 13, EGU2011-4016

  29. Effective Rainfall Measurement Measurementsare 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.) Proximate soil is non-wetted and very dry Moisture ‘fingers’ after irrigation or preferential flow

  31. Hydrophobicity Corrected Water repellence

  32. Future Studies – The Next Stage 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

  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

More Related