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Application of influence diagrams for well contamination risk management: a case study in the Po plain, northern Italy

Cameron, Enrico, Pilla, Giorgio, Stella, Fabio A.
Hydrogeology journal 2019 v.27 no.1 pp. 273-289
aquifers, artificial intelligence, case studies, computer software, drilling, electrical resistance, geophysics, groundwater, models, prediction, risk, risk management, saline water, surveys, tomography, uncertainty, wells, Italy
The aquifer of the Oltrepò Pavese plain (northern Italy) is affected by paleo-saltwater intrusions that pose a contamination risk to water wells. The report first briefly describes how the presence of saline water can be predicted using geophysical investigations (electrical resistivity tomography or electromagnetic surveys) and a machine-learning tool specifically developed for the investigated area. Then, a probabilistic graphical model for addressing the risk of well contamination is presented. The model, a so-called ‘influence diagram’, allows researchers to compute the conditional probability that groundwater is unsuitable for use taking into account the results of the geophysical surveys, the predictions of the machine-learning software, the related uncertainties and the prior probability of contamination in different sectors of the plain. The model, in addition, allows for calculation and comparison of the expected utility of alternative decisions (drilling or not drilling the well, or using another water source). The model is designed for use in ordinary decision situations and, although conceived for a specific area, provides an example that may be adapted to other cases. Some adaptations and generalizations of the model are also discussed.