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GRACE in the Murray-Darling Basin: integrating remote sensing with field monitoring to improve hydrologic model prediction. Kevin M. Ellett Department of Civil and Environmental Engineering, University of Melbourne, Australia and USGS WRD Sacramento, California
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GRACE in the Murray-Darling Basin: integrating remote sensing with field monitoring to improve hydrologic model prediction Kevin M. Ellett Department of Civil and Environmental Engineering, University of Melbourne, Australia and USGS WRD Sacramento, California Colleagues: Jeffrey Walker, Rodger Grayson, Adam Smith and Matt Rodell (NASA-GSFC)
Outline • Motivation for Research • Contributions from GRACE • Research Approach • Preliminary Results
Western and Grayson, 1998 Motivation for Research • Modeling hydrological processes at the catchment-scale • Soil moisture is a key component in the terrestrial water and energy balance • Primary controls on soil moisture distribution • climate, soils, vegetation, topography • Scaling of soil moisture and hydrological processes?
Motivation for Research • Current policy initiatives on sustainable water resource management in Australia • Murray-Darling Basin (MDB) • Land clearing has resulted in devastating impacts from salinity • Long-term increase in terrestrial water storage • Re-vegetation to reverse this trend
GRACE Contributions in the MDB • Measuring the trend in storage change • Re-vegetation • Limited 5 year lifespan • Assessment of regional-scale hydrological models • Water balance closure • Model bias • Can GRACE help to improve modeling at the catchment-scale? • Scaling
Objectives • GRACE “validation” (comparison) from an observational network • Examine the utility of GRACE observations at the catchment-scale • Downscaling
Approach • Installation of a ground-based measurement network for monitoring changes in gravity and terrestrial water storage • Nested catchment and grid-based designs provide data at 4 different scales using 46 total sites • Development of a modelling framework for the downscaling and assimilation of GRACE data into a catchment-based land surface model • Assessing the utility of GRACE by comparing model results with and without GRACE data assimilation to the measurement network • Results will depend on downscaling approach, model physics, data assimilation, and observations- uncertainty in each component • Testing of alternative model with simple water balance parameterization allowing automated calibration • Testing of alternative downscaling schemes
MDB and MurrumbidgeePrecipitation minus Evapotranspiration (mm)
Murrumbidgee Monitoring Network Yanco Study Area (50km x 50km Grid) Irrigation Areas Kyeamba Ck. Study Area
Monitoring Site Instrumentation Logger Gravity monitoring with CG-3M on stable platform Raingauge T107 Star pickets (2.5 m length) Backfilled soil TDR CS616 Piezometer (water level and neutron probe) Schematic diagram of instrumentation installed at monitoring sites
Preliminary Results Observed average monthly dS = 13.5 mm Annual amplitude approx. 50 mm
Conclusions • Murray-Darling Basin is a reasonable candidate for GRACE validation/comparison • Signal dominated by soil moisture component • Magnitude? • Modeling framework for testing the utility of GRACE is currently being developed • Catchment-based LSM [Koster et al., 2000] • Assimilation scheme for GRACE and AMSR-E • Development of alternative downscaling schemes and simple “bucket” model calibrated