Explainable AI reveals new hydroclimatic insights for ecosystem-centric groundwater management

Abstract

Trustworthy projections of hydrological droughts are pivotal for identifying the key hydroclimatic factors that affect future groundwater level (GWL) fluctuations in drought-prone karstic aquifers that provide water for human consumption and sustainable ecosystems. Herein, we introduce an explainable artificial intelligence (XAI) framework integrated with scenario-based downscaled climate projections from global circulation models. We use the integrated framework to investigate nonlinear hydroclimatic dependencies and interactions behind future hydrological droughts in the Edwards Aquifer Region, an ecologically fragile groundwater-dependent semi-arid region in southern United States. We project GWLs under different future climate scenarios to evaluate the likelihood of severe hydrological droughts under a warm-wet future in terms of mandated groundwater pumping reductions in droughts as part of the habitat conservation plan in effect to protect threatened and endangered endemic aquatic species. The XAI model accounts for the expected non-linear dynamics between GWLs and climatic variables in the complex human-natural system, which is not captured in simple linear models. The XAI-based analysis reveals the critical temperature inflection point beyond which groundwater depletion is triggered despite increased average precipitation. Compound effects of increased evapotranspiration, lower soil moisture, and reduced diffuse recharge due to warmer temperatures could amplify severe hydrological droughts that lower GWLs, potentially exacerbating the groundwater sustainability challenges in the drought-prone karstic aquifer despite an increasing precipitation trend.