Harnessing machine learning tools for water quality assessment in the Kebili shallow aquifers, Southwestern Tunisia

An integrated method that implements multivariate statistical analysis and ML methods to evaluate groundwater quality of the shallow aquifers of the Djerid and Kebili district, Southern Tunisia, was adopted. An evaluation of their suitability for irrigation and/or drinking purposes is necessary. A comprehensive hydrochemical assessment of 52 samples with entropy weighted water quality index (EWQI) was also proposed. Eleven water parameters were calculated to ascertain the potential use of those resources in irrigation and drinking. Multivariate analysis showed two main components with Dim1 (variance = 62.3