USING CONTINUOUS GNSS TO EVALUATE AQUIFER STORAGE CHANGES IN CALIFORNIA’S CENTRAL VALLEY

California’s Central Valley is home to a robust agricultural economy producing over 250 different crops valued at an estimated 17 billion dollars annually. However, the Mediterranean and semi-arid climate of the valley requires farms to supplement annual precipitation with other water sources. Additionally, cities in the valley continue to grow, increasing municipal water demands. In some instances, these water demands are met by redirecting surface water, in others, groundwater is withdrawn. In 2014, California passed the Sustainable Groundwater management act (SGMA), enacting groundwater regulation for the first time in the state’s history. This left the monumental task for local water agencies to understand, manage, and mitigate water use over 47,000 sq. km. of aquifer within 20 years.

To further improve our understanding of this aquifer, we use observation of vertical land motion at 128 GNSS stations with the Gravity Recovery and Climate Experiment (GRACE) gravity observations and the subsurface texture of the Central Valley within a first order poromechanical model. We associate surface GPS measurements to fine-grained layer compaction, which is usually irrecoverable and representative of lost water storage potential. We further note the minimal surface rebound upon groundwater recharge. The model accounts for this surface response by incorporating the equilibrium pressure delay known to occur in clay aquitards. Using the total, average thickness of fine-grained layers, we calculate a delay term for all interbeds in the system. Including this delayed compaction is a necessary refinement of existing approaches that solely rely on surface deformation data to resolve groundwater volume change.

With the successful application of this technique, we provide an unbiased estimate of the groundwater change across the valley. This technique is advantageous for water management applications because it is accessible, uses existing equipment and software, and provides a more detailed model of spatiotemporal groundwater volume change.