Using Multiple Points Statistics in Indian Wells Valley, California to estimate the aquifer storage capacity

The recently finalized Stanford Groundwater Architecture Project (GAP) was designed to define the optimal workflow using advanced geophysical and computational methods for the development of hydrogeological conceptual models (HCMs) in California. The basin in Indian Wells Valley (IWV) was one of the pilot areas in the project and is categorized by the California Department of Water Resources as subject to critical conditions of overdraft and is categorized as a High Priority Basin under the California Sustainable Groundwater Management Act. Being able to map the potential aquifers in the IWV is therefore of great importance. To do this, Multiple Points Statistics (MPS) were used. The target of the MPS simulations was to locate potential local aquifers within a hydrogeologic zone mainly consisting of clay, and in turn to estimate their groundwater storage capacity. This was done by combining Airborne Electromagnetic data, borehole information, and geological background knowledge, and to compute 75 extensive 3D models of the area. Based on the simulated models, we could point out areas with increased probability of being local aquifers and compute their potential storage capacity.