This study examines the problems with the assessment of river water quality, which is affected by multiple water quality parameters (WQPs) that have inherent uncertainties and uneven decision-maker judgments. To cope with these uncertainties, we use soft sets, fuzzy sets, and fuzzy soft sets. In particular, we first present the square root mean square (SQRTMS) and a water pollution score (WPS) for fuzzy soft sets and propose a novel water pollution assessment framework, i.e., the fuzzy soft multi-criteria group decision-making model (Ω-model). This model produces Ω score, a weighted water pollution score, to classify pollution levels. The proposed methodology is made on water quality indices of Haora River in Tripura India, which serves not only as an essential drinking water source for Agartala but also plays a critical role in supporting local ecosystems, agriculture, and livelihoods. Over the years, the river has faced increasing pollution from domestic wastewater discharge and agricultural runoff, exacerbating water quality issues. Its deteriorating condition has posed a threat to both aquatic life and public health. Our study involves nine key parameters in seven sampling sites situated along the river, which were sampled in January, February, and March of 2024 with an emphasis on waste discharge points. Finally, the proposed model is compared with existing approaches and the effectiveness and benefits are put forth.
Anthropogenic Impacts on Urban River Water Quality for Rating Water Pollution Using an Effective Fuzzy Soft Multi Criteria Group Decision Making Model
Multi-criteria decision-making
Soft set
Fuzzy set
Fuzzy soft set
River water quality
Water pollution
Uncertainty modeling