Assessment and Prediction of the Water Quality Index for the Groundwater of the Ghiss-Nekkor (Al Hoceima, Northeastern Morocco)

Water quality index (WQI) is the primary method applied to characterize water in world. The current study employed statistical analysis and multilayer perceptron (MLP) approaches for predicting groundwater Ghiss-Nekkor aquifer, northeast of Al Hoceima, Morocco. Fifty sampled were identified analyzed major anions cations throughout May 2019. Several physicochemical parameters all samples this investigation, such as TDS, pH, EC, Na, K, Ca, Mg, HCO3, NO3, Br, SO4, Cl. entropy-weighted (EWQI) was calculated from these parameters. WQI procedure determined suitability consumption. value varied 90.98 337.28. WQI, Cl? spatial distribution showed that EC are associated with poor quality. A single sample (W16) represented unsuitable drinking purposes offered a 337.28, indicating due seawater intrusion, overexploitation, harsh weather conditions. majority values obtained exceeded recommended limit World Health Organization (WHO)’s guidelines findings show using straightforward indexes sufficient suitable precision. MLP model shows good predictive performances terms coefficient determination R2, mean absolute error (MAE), root-mean-square (RMSE) 0.9885, 5.8031, 4.7211, respectively. ANN approach develop can accurately predict utilizing mineralization, TH, NO2 inputs. MAE model’s performance be 4.72. Bland–Altman test used validate suitable. Following test, it appropriate an just 0.1%.