Abstract:Groundwater contamination risk mapping is one essential measure in groundwater management and quality control. The purpose of the present study is to address this mapping by means of a novel framework, which is more suitable for arid regions than other methods developed in previous work. Specifically, we integrate machine learning tools, interpolation and process-based models with a modified version of DRASTIC-AHP to evaluate groundwater vulnerability to nitrate contamination and to map this contamination in J… Show more
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