The San Joaquin Valley and Tulare basins in California’s Central Valley have intensive agricultural activity and groundwater demand that has caused significant subsidence and depletion of water resources in the past. We measured groundwater pumping-induced land subsidence in the southern Central Valley from March 2015 to May 2017 using Sentinel-1 interferometric synthetic aperture radar (InSAR) data. The InSAR measurements provided fine spatial details of subsidence patterns and displayed a superposition of secular and seasonal variations that were coherent across our study region and correlated with precipitation variability and changes in freshwater demand. Combining InSAR and Global Positioning System (GPS) data, precipitation, and in situ well records showed a broad scale slowdown/cessation of long term subsidence in the wetter winter of 2017, likely reflecting the collective response of the Central Valley aquifer system to heavier-than-usual precipitation. We observed a very good temporal correlation between the Gravity Recovery and Climate Experiment (GRACE) satellite groundwater anomaly (GWA) variation and long-term subsidence records, regardless of local hydrogeology and mechanical properties. This indicates the subsidence from satellite geodesy is a very useful indicator for tracking groundwater storage change. With the continuing acquisition of Sentinel-1 and other satellites, we anticipate decadal-scale subsidence records with a spatial resolution of tens to hundreds of meters will be available in the near future to be combined with basin-averaged GRACE measurements to improve our estimate of time-varying groundwater change.

Abstract Despite numerous advances in continental-scale hydrologic modeling and improvements in global Land Surface Models, an accurate representation of regional water table depth (WTD) remains a challenge. Data assimilation of observations from the Gravity Recovery and Climate Experiment (GRACE) mission leads to improvements in the accuracy of hydrologic models, ultimately resulting in more reliable estimates of lumped water storage. However, the usually shallow groundwater compartment of many models presents a problem with GRACE assimilation techniques, as these satellite observations also represent changes in deeper soils and aquifers. To improve the accuracy of modeled groundwater estimates and allow the representation of WTD at finer spatial scales, we implemented a simple, yet novel approach to integrate GRACE data, by augmenting the Variable Infiltration Capacity (VIC) hydrologic model. First, the subsurface model structural representation was modified by incorporating an additional (fourth) soil layer of varying depth (up to 1000 m) in VIC as the bottom ‘groundwater’ layer. This addition allows the model to reproduce water storage variability not only in shallow soils but also in deeper groundwater, in order to allow integration of the full GRACE-observed variability. Second, a Direct Insertion scheme was developed that integrates the high temporal (daily) and spatial (∼6.94 km) resolution model outputs to match the GRACE resolution, performs the integration, and then disaggregates the updated model state after the assimilation step. Simulations were performed with and without Direct Insertion over the three largest river basins in California and including the Central Valley, in order to test the augmented model's ability to capture seasonal and inter-annual trends in the water table. This is the first-ever fusion of GRACE total water storage change observations with hydrologic simulations aiming at the determination of water table depth dynamics, at spatial scales potentially useful for local water management.