GeoAI Framework for Hydrochemical and Explainable Groundwater Quality Assessment in Akre District, Kurdistan

Groundwater quality assessment is essential for the sustainable management of water resources in arid and semi-arid regions where ground water is the main source of drinking and irrigation water. This study used hydrochemical analysis, the Water Quality Index (WQI), multivariate statistical techniques. Machine-learning methods were used to classify groundwater quality and determine the relative contribution of hydrochemical factors using SHAP explainability analysis, while kriging was used to map the spatial distribution of groundwater quality and hydrochemical parameters, and geographic information systems (GIS) to assess groundwater quality and identify the dominant factors influencing its spatial variability in Akre District, Duhok Governorate, Kurdistan region. Forty-three groundwater samples were analyzed for physicochemical characteristics. Hydrochemical processes were investigated using principal component analysis, factor analysis, and hierarchical clustering, while variable relevance was assessed using Random Forest and XGBoost models in conjunction with SHAP interpretation. WQI results indicated significant geographical diversity, with relatively fresh groundwater concentrated in the northern recharge zones and higher WQI values mostly found in the eastern and southeastern sectors. Based on hydrochemistry and multivariate analyses, the controlling factors in the chemistry of the groundwater are considered to be carbonate weathering, water-rock interaction, and local agriculture practices. Through ML and SHAP analyses, the findings show that EC has the greatest impact on groundwater quality, while NO3-, Ca2+, and Mg2+ follow. The GIS approach is used to identify areas in terms of groundwater quality risks. The combination of hydrochemistry, WQI, GIS, ML, and XAI approaches can serve as an effective means of assessing groundwater quality and a decision-making tool in groundwater quality management.