The effects of droughts on pumping fields at the watershed scale: building a model from a heterogeneous dataset.

Water management is becoming an increasingly complex task that must account for not only climate change but socio-economic pressures as well. This is particularly true in the case of alluvial aquifers which are often connected to surface waters, thus requiring a watershed scale policy. Conflicts of use might emerge especially during droughts which are occurring more frequently. In this context, the alluvial aquifer of the Allier River (France) is an interesting case study. This is a major regional resource for drinking water, industries and irrigation which extends over 210 km long between Langeac and the confluence with the Loire River. The Naussac dam keeps the Allier River at a minimum flow rate and secures water uses downstream, but the summer drought of 2023 was extreme and the dam was almost completely emptied. If this situation were to repeat itself over a longer period, the consequences on the productivity of pumping fields implanted on the alluvial aquifer are unknown. This work is part of the MODALL² project in which we propose to build a transient model of the alluvial aquifer using MODFLOW (Groundwater Vistas 8). One of the main challenges is to gather and organize a set of often heterogeneous data (incomplete time series, spatial data sparsely distributed etc.) from various sources. With the intention of improving the existing network, 50 additional water loggers have been deployed for groundwater level monitoring. 30 Electrical Resistivity Tomography (ERT) profiles were carried out to refine the thickness of alluvial deposits on the well-fields and thus, the geometry of the model. Given the elongated dimension of the alluvial aquifer, the study area is divided into 9 sub-models with which a ‘cascade modelling’ is performed. The purpose is to better understand how droughts spread across the whole hydrosystem and to what extent the pumping fields will be affected. ERT surveys have revealed that the thickness of alluvial deposits varies significantly from one site to another, ranging from 5 to 15 m downstream where the alluvial plain is more widespread. Hydrodynamic data show the influence of the river on groundwater level variations depending on the distance from the river. Lastly, the heterogeneity of the input datasets introduces uncertainty into the model that will need to be estimated. Beyond the potential to use modeling to anticipate future water crises, this work also proposes a methodology for handling large-scale heterogeneous datasets.