1. The Role of Vegetation in Minimising GW Recharge – application to mining and waste management industries Derek Eamus, C Macinnis-Ng, I Yunusa, M Zeppel Terrestrial Ecohydrology Research Group University of Technology, Sydney

2. Outline of the talk Why do we need to minimise GW recharge?Why do we need to minimise GW recharge? How can we minimise it?How can we minimise it? Design of store-release caps requires knowledge of rate of water use by vegetationDesign of store-release caps requires knowledge of rate of water use by vegetation How might we model veg water use?How might we model veg water use?

3. Outline of the talk A modified Jarvis-Stewart modelA modified Jarvis-Stewart model Using a Soil-Plant Atmosphere modelUsing a Soil-Plant Atmosphere model A case study of a site in NSWA case study of a site in NSW

4. Minimising GW recharge is important for: Minimising development of dryland salinityMinimising development of dryland salinity Preventing leachates from waste storage dumps poisoning an aquiferPreventing leachates from waste storage dumps poisoning an aquifer Preventing acid drainage from mine-site rock dumpsPreventing acid drainage from mine-site rock dumps

5. How can we minimise GW recharge? Use vegetation to transpire rain back to the atmosphere before it percolates beyond the root zoneUse vegetation to transpire rain back to the atmosphere before it percolates beyond the root zone Therefore need to design a “cap” on the siteTherefore need to design a “cap” on the site This raises many questions of design, eg:This raises many questions of design, eg: How deep should the soil be on the clay cap?How deep should the soil be on the clay cap? How do we know how much water the vegetation will transpire on a daily/seasonal/annual basis?How do we know how much water the vegetation will transpire on a daily/seasonal/annual basis?

6. Water use by vegetation – a reminder Water use by vegetation is determined by:Water use by vegetation is determined by: Solar radiation inputSolar radiation input Soil moisture contentSoil moisture content Atmospheric water content (humidity or vapour pressure deficit)Atmospheric water content (humidity or vapour pressure deficit) Leaf area index of the vegetationLeaf area index of the vegetation

7. Current models require parameterisation for each site individually – eg SPA, VADOSE, Penman-MonteithCurrent models require parameterisation for each site individually – eg SPA, VADOSE, Penman-Monteith Models have a large number of input variables – SPA has about 15, VADOSE has far too many, the P-M has 6Models have a large number of input variables – SPA has about 15, VADOSE has far too many, the P-M has 6 We can model veg water use

8. Parameterising models for every site and vegetation type is too slow and expensiveParameterising models for every site and vegetation type is too slow and expensive We have developed a modified Jarvis- Stewart model that can be used for any ecosystem dominated by woody vegetationWe have developed a modified Jarvis- Stewart model that can be used for any ecosystem dominated by woody vegetation We can model veg water use

9. Modelling tree water use – the original JS approach Penman-Monteith Equation and Jarvis-Stewart Model 1.Needs measurements of G c 2.Circular, Complex and Time Consuming A modified Jarvis-Stewart Model 1.Measurements in E c 2.Retains Mechanistic understanding of processes

10. Model Functional Dependencies Dependence of G c and E c on changing solar radiation Dependence of G c on changing vapour pressure deficit Dependence of G c and E c on changing soil moisture content Dependence of E c on changing vapour pressure deficit

11. Veg water use varies as a function of light, VPD and soil moisture

12. How well does the modified Jarvis-Stewart model perform? We compared it to the standard P-M approach and to an artificial neural network statistical model

13. Summer Winter

14. With our modified JS model, the slope of the regression for observed and modelled is close to oneWith our modified JS model, the slope of the regression for observed and modelled is close to one

15. A comparison of three sites – all three behave similarly

16. Do we need to parameterise the model independently for each site? If average parameter values work, this would be a massive saving in effort.....If average parameter values work, this would be a massive saving in effort.....

17. The modified JS using average parameter values does very well (Paringa data)

18. Using an averaged set of parameter values allows us to generate daily rates of water use from just a set of met data

19. Applying a modelling approach to testing the mechanism We applied the Soil-Plant-Atmosphere model of Williams et al. 2001 to the problemWe applied the Soil-Plant-Atmosphere model of Williams et al. 2001 to the problem The SPA model is a detailed mechanistic model that calculates C fluxes, water fluxes, leaf water potential and GPP of landscapesThe SPA model is a detailed mechanistic model that calculates C fluxes, water fluxes, leaf water potential and GPP of landscapes

20. The SPA models water flux from Soil, through the Plant to the Atmosphere Plant data Soil data Soil water uptake Sap flow Leaf water potential Met data Stomatal conductance Photosynthesis GPP Transpiration INPUTS OUTPUTS

21. The SPA model does well in modelling sap flow at our site

22. Veg water use was independent of the water content of the upper 80 cm of soil – highlighting the importance of deep roots in the clay layer

23. Conclusions The modified JS model allows quantification of water use from basic met data and using average parameter valuesThe modified JS model allows quantification of water use from basic met data and using average parameter values The SPA model is a detailed model that allows us to examine the mechanisms underlying observed behaviourThe SPA model is a detailed model that allows us to examine the mechanisms underlying observed behaviour Management of deep drainage through vegetation is a realistic option for the waste and mining industriesManagement of deep drainage through vegetation is a realistic option for the waste and mining industries

24. Published by CSIRO 2006 ISBN 0 643 06834 1