Knowledge of water quality is crucial for sustainable management of the natural resource, yet such information is often limited by data scarcity and high monitoring costs. This study proposes a novel approach, leveraging underutilized hydrogeochemical data from (potentially) contaminated sites to characterize natural groundwater composition at the mesoscale. Although originally collected for remediation purposes, these data, if properly processed, can yield valuable insights into natural groundwater conditions, offering a cost-effective sustainable alternative to extensive monitoring programs. The proposed workflow is applied in the Ferrara province (Po Plain, Italy), a region affected by both anthropogenic and natural groundwater quality issues. Aggregated data processed through reproducible steps underwent multivariate analysis, confirming the method’s ability to depict natural geochemical heterogeneity. Results were validated against the official regional monitoring network, demonstrating improved spatial and temporal resolution. This approach provides a scalable solution for enhancing groundwater quality assessment and supporting sustainable groundwater management, without requiring significant new data collection.
Landi et al. (Thu,) studied this question.