A probabilistic model of aquifer susceptibility to earthquake-induced groundwater-level changes

A probabilistic model for earthquake-induced persistent groundwater-level response as a function of peak ground velocity (PGV) has been constructed using a catalog of monitoring well observations spanning multiple earthquakes. The regional-scale, multi-site, multi-earthquake investigation addresses the occurrence and absence of hydraulic responses to large earthquakes spanning almost a decade of seismic shaking. Persistent ground-water-level changes, or absences of change, have been quantified in 495 monitoring wells in response to one or more of 11 recent New Zealand earthquakes larger than Mw 5.4 that occurred between 2008 and 2017. A binary logistic regression model with random effects has been applied to the dataset using three predictors: earthquake shaking (PGV), degree of hydrogeological confinement (monitoring well depth), and rock strength (site-average shear-wave velocity). Random effects were included as a partial proxy for variations in monitoring wells’ susceptibilities to earthquake-induced persistent water-level changes. Marginal probabilities have been calculated as a function of PGV and related to modified Mercalli intensity (MMI) levels using a New Zealand-specific MMI–PGV relationship that enables the likelihood of persistent water-level changes to be expressed for MMIs of II–VIII. This study capitalizes on one of the largest catalogs of earthquake hydrological observations compiled worldwide and is the first attempt at incorporating seismic and hydrogeological factors in a common probabilistic description of earthquake-induced groundwater-level changes. This modeling framework provides a more generalizable approach to quantifying responses than alternative metrics based on epicentral distance, magnitude, and seismic energy density. It has potential to enable better comparison of international studies and to inform practitioners making engineering or investment decisions to mitigate risk and increase the resilience of water-supply infrastructure.