COMPARISON OF CHANGES IN GROUNDWATER STORAGE USING GRACE DATA AND A HYDROLOGICAL MODEL IN CALIFORNIA'S CENTRAL VALLEY

摘要

The Gravity Recovery and Climate Experiment (GRACE) measures gravity anomalies on earth to estimate changes in total water storage (TWS), and may be a useful tool for calculating changes in groundwater storage for California's agriculturally productive Central Valley region. Under current California law, well owners are not required to report groundwater extraction rates, making estimation of total groundwater extraction difficult. As a result, other groundwater change detection techniques are used to estimate changes in groundwater storage in the Central Valley aquifer. From October 2002 to September 2009, GRACE was used to measure changes in TWS for the Sacramento River Basin, and the San Joaquin River Basin (including the Tulare Lake Basin), which contain the Central Valley aquifer. Net groundwater storage changes were calculated from the changes in TWS by incorporating estimates for additional components of the hydrological budget including soil moisture, snow pack, and surface water storage. The changes in groundwater storage at the river basin and regional level (the two basins combined) were then compared to modeled values calculated using the California Department of Water Resources' Central Valley Groundwater-Surface Water Simulation Model (C2VSIM). At the regional level (the Central Valley aquifer) it was found that GRACE-derived estimates of groundwater change in storage produced comparable results to C2VSIM. However, at the river basin level (Sacramento and San Joaquin), GRACE-derived estimates were significantly different from those modeled by C2VSIM, highlighting the current limit of GRACE'S spatial resolution. This work has the potential to improve California's groundwater resource management at the regional level and in validating existing hydrological models for the Central Valley. The work also underscores the need for higher resolution satellite data that are applicable smaller scale management.