Evaluation of groundwater quality indices using multi-criteria decision-making techniques and a fuzzy logic model in an irrigated area

Abstract

The quality of water for irrigation presents a fundamental challenge to the sustainability of agricultural practices. This study, conducted in the Ras Jbel (RJ) aquifer of Tunisia, aims to evaluate the suitability of groundwater for both drinking and irrigation purposes and to identify regions suitable for agriculture. In this research, various indices were employed, including water quality index (WQI), entropy water quality index (EWQI), and Fuzzy logic for irrigation water quality index (FLIWQ). The conventional irrigation indices, such as sodium adsorption ratio (SAR), magnesium hazard (MH), sodium percentage (Na%), Kelly's ratio (KR), permeability index (PI), residual sodium carbonate (RSC), and potential salinity (PS) were converted into fuzzy membership and produced dry and wet seasons maps. The dry and wet season fuzzy logic maps were used as input for final FLIWQI. Eighty-nine groundwater samples were collected from shallow wells and analyzed for major cations and anions. Most parameters exceeded the recommended values for drinking, according to both WHO and Tunisian standards, across all samples. The results of the WQI and EWQI indicated that, during the wet season, over 90% and 86% of the water samples were classified as poor and very poor quality, respectively, compared to 93.33% and 49% during the dry season. For IWQI, the wet season fuzzy logic map suggests 55.57% groundwater suitability, mainly in the central area. In the dry season, the map indicates 41.11% suitability for irrigation. The FLIWQI map confirms that the groundwater in the central part of the study area is suitable for agriculture. This study can help decision-makers initiate efficient water quality management plans in similar water-scarce environments worldwide.