Integration of Geochemical Modeling, Multivariate Analysis, and Irrigation Indices for Assessing Groundwater Quality in the Al-Jawf Basin, Yemen

• Published in: Water (Basel) 2023-04, Vol.15 (8), p.1496
• Main Authors: Al-Mashreki, Mohammed Hezam, Eid, Mohamed Hamdy, Saeed, Omar, Székács, András, Szűcs, Péter, Gad, Mohamed, Abukhadra, Mostafa R., AlHammadi, Ali A., Alrakhami, Mohammed Saleh, Alshabibi, Mubarak Ali, Elsayed, Salah, Khadr, Mosaad, Farouk, Mohamed, Ramadan, Hatem Saad
• Format: Article
• Language: English
• Subjects: Adaptive sampling; Adaptive systems; Agriculture; Algeria; Analysis; Aquatic resources; Aquifers; basins; calcium; Calcium ions; Contamination; decision making; Drinking water; Egypt; Environmental health; Farmers; Fuzzy logic; Fuzzy systems; Geochemistry; Geographic information systems; Geology; Groundwater; Groundwater irrigation; humans; Hydrology; India; Irrigation; Irrigation water; Magnesium; Management; Mathematical models; Modelling; Multivariate analysis; Multivariate statistical analysis; Physicochemical analysis; Population growth; Precipitation; Quality assessment; Quality management; Salinity; Sodium; sodium adsorption ratio; sodium carbonate; spatial data; Statistical analysis; Surface water; Sustainable development; Water; Water management; Water monitoring; Water quality; Water quality assessments; Water quality management; Water resources; Water resources management; Water sampling; Water shortages; Water, Underground; Water-supply; Yemen
• ISSN: 2073-4441; 2073-4441
• DOI: 10.3390/w15081496

Water quality monitoring is crucial in managing water resources and ensuring their safety for human use and environmental health. In the Al-Jawf Basin, we conducted a study on the Quaternary aquifer, where various techniques were utilized to evaluate, simulate, and predict the groundwater quality (GWQ) for irrigation. These techniques include water quality indices (IWQIs), geochemical modeling, multivariate statistical analysis, geographic information systems (GIS), and adaptive neuro-fuzzy inference systems (ANFIS). Physicochemical analysis was conducted on the collected groundwater samples to determine their composition. The results showed that the order of abundance of ions was Ca2+ > Mg2+ > Na+ > K+ and SO42− > Cl− > HCO3− > NO3−. The assessment of groundwater quality for irrigation based on indices such as Irrigation water quality index (IWQI), sodium adsorption ratio(SAR), sodium percent (Na%), soluble sodium percentage (SSP), potential salinity (PS), and residual sodium carbonate RSC, which revealed moderate-to-severe restrictions in some samples. The Adaptive Neuro-Fuzzy Inference System (ANFIS) model was then used to predict the IWQIs with high accuracy during both the training and testing phases. Overall, these findings provide valuable information for decision-makers in water quality management and can aid in the sustainable development of water resources.