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The value of data in reducing uncertainty in mountain groundwater modeling
Summary
Scientists studied underground water in mountain areas, which are important sources of drinking water for people living in valleys. They found that these underground water sources are getting contaminated with harmful substances like pharmaceuticals, PFAS chemicals, and microplastics from sewage that isn't properly treated. The research shows that better monitoring and modeling of these water systems could help protect this crucial drinking water source from contamination that threatens human health.
Mountain aquifers are receiving increasing attention as a key component of the so-called water towers. They sustain important freshwater ecosystems, river flow during droughts, and are a key water resource for populations living in mountain valleys and the nearby floodplains. These aquifers are exposed to emerging pollutants, such as pharmaceuticals, PFAS, and microplastics, whose adverse effects on ecosystems and human health are exacerbated by overexploitation. The interaction between surface and subsurface waters increases the risk of groundwater contamination by untreated sewage waters, and in several cases also by treated waters, because in most countries sewage treatment systems are not yet designed to remove pharmaceutical and emerging contaminants. A significant challenge that modelers face when dealing with these systems is the endemic lack of data to constrain the models, which limits their reliability in risk analysis and in the comparison of the effectiveness of alternative remediation actions. An example of application in a mountain valley aquifer of northeastern Italy is used to discuss how to make a convenient use of available data to reduce the uncertainty affecting groundwater modeling in such environments, where lateral fluxes stemming from hillslopes and the surface/subsurface water exchange fluxes are difficult to constraint and a source of large uncertainties in modeling both groundwater availability and groundwater contaminant transport. In particular, we explored the gain in model consistency that can be obtained by supplementing groundwater head data with geochemical and groundwater concentration data of a target contaminant at a few controlling groundwater wells. The geochemical data refer to river water and to springs emerging from the lateral hillslopes. Electrical conductivity and other geochemical data typically collected as part of the standard water quality monitoring performed by Environmental Protection Agencies may help in reducing the uncertainty in the lateral and surface/subsurface exchange fluxes and in improving the reliability of the transport model, when used in combination with contaminant concentration data at the available groundwater monitoring wells. The analysis suggests that considering the valley aquifer as part of a more complex system, including the contribution of the lateral mountain aquifers, and the exchange with surface water, is an opportunity for producing realistic models rather than an unnecessary complication.
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