AUTHOR=Kitlasten Wes , Moore Catherine , Doherty John 

TITLE=Exploring the use of new data assimilation technologies to map groundwater quality vulnerability in a large alluvial aquifer

JOURNAL=Frontiers in Earth Science

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2025.1609778

DOI=10.3389/feart.2025.1609778

ISSN=2296-6463

ABSTRACT=Integrity of simulator-based Bayesian analysis requires adequate representation of prior parameter probabilities, and quantification and reduction of posterior predictive uncertainties through history-matching. In many groundwater management contexts, hydrogeological complexity and long numerical model run times can render both of these tasks difficult. We present three new technologies that can make simulator-based Bayesian analysis that is undertaken in complex hydrogeological environments more effective and more tractable. These are demonstrated using a case study where groundwater head, streamflow and groundwater age data are assimilated in order to assess groundwater vulnerability to anthropomorphic deterioration of its quality. Bayesian analysis begins by generating ensembles of realizations of hydraulic property and other parameters used by a multi-layer groundwater model. The first technology supports this first step, by ensuring that respect for complex hydrogeology is embodied in nonstationary representations of hydraulic properties, as well as in stochasticity of so-called “hyperparameters” which govern their spatially variable geostatistics. The second and third technologies support data assimilation in two different ways, both of which are numerically cheap. One of these options, Ensemble Space Inversion (ENSI) requires adjustment of parameter fields in order for model outputs to match field measurements. The other option, Data Space Inversion (DSI) avoids parameter field adjustment through construction of direct statistical linkages between model-generated counterparts to field measurements and groundwater predictions of management interest. This statistical model is then history-matched in lieu of the numerical model. Deployment of both of these strategies at our case study site yields similar results. They reveal the likely existence of young water at depth over large parts of a regional aquifer system. This has repercussions for the quality of extracted water, and for land management in recharge areas.