REGIONAL SCALE GROUNDWATER MODELING FOR HAZARD ANALYSES IN THE SAN FRANCISCO BAY AREA

Much of the professional practice of geologic and geotechnical engineers is driven by hazard evaluation. Many geologic hazards, including precipitation-induced landslides and coseismic liquefaction, are strongly influenced by shallow groundwater. Consequently, estimates of groundwater depth are critical for engineers, planners, and construction professionals. For regional-scale analysis and planning, very simple or coarse-resolution groundwater models are available; however, these models often do not consider spatial and temporal variations observed within wells and may not provide sufficient local resolution for critical infrastructure studies.

In this study, we extend a conventional, physics-based groundwater model to better understand the local and temporal variation between groundwater well measurements. In our probabilistic model, the physics-based groundwater elevation model serves as the mean ergodic function and a Gaussian process (GP) interpolation function serves as a model of the well observation residuals. We demonstrate the applicability and accuracy of the model by developing a phreatic groundwater model for an approximately 10,000 km² area surrounding San Francisco Bay. Comparison to a blind holdout dataset indicates the model accurately estimates the mean groundwater elevations within ± 1 m. The model also indicates that the average seasonal variability is small relative to nonseasonal events such as long-term drought and El-Nino-related precipitation, which can cause wide deviations from the mean. The nonseasonal variability has important consequences for hazard and risk evaluation and demonstrates the need to consider the uncertainty of groundwater for coseismic risk evaluations.