An efficient water quality evaluation model using weighted hesitant fuzzy soft sets for water pollution rating
Ajoy Kanti Das, Nandini Gupta, Tahir Mahmood, Binod Chandra Tripathy, Rakhal Das, Suman Das
Abstract
In this study, we propose an efficient water quality evaluation model, the weighted hesitant fuzzy soft decision-making model (Ω-model). This model combines hesitant fuzzy sets and soft sets to address uncertainty and ambiguity in water pollution assessment. We apply this methodology to evaluate water quality indices for pollution rating in the Haora River, located in Tripura, India. The river is crucial as it serves as the main drinking water source for Agartala, the capital city of Tripura. We introduce the Ω-score as a key indicator derived from the weighted hesitant fuzzy soft set (WHFZSS), which is a key indicator for evaluating water quality. Our assessment considers eight important parameters sampled at five strategic sites along the river, covering pre-monsoon, monsoon, and post-monsoon seasons from 2021 to 2022. These parameters include pH, biochemical oxygen demand, dissolved oxygen, total hardness, total alkalinity, total dissolved solids, total coliform, and fecal coliform. The novelty of this chapter lies in the introduction of the Ω-model, which uniquely integrates hesitant fuzzy sets and soft sets to address uncertainties and expert hesitancies in water quality evaluation. By incorporating WHFZSS, the model provides a more nuanced and reliable assessment framework. The Ω-score, a new indicator derived from the WHFZSS, enables precise measurement of water quality, with scores closer to zero indicating excellent quality and scores near one reflecting poor quality. This methodology is applied comprehensively to the Haora River, evaluating eight key water quality parameters across different seasons and sites, offering practical insights into pollution levels, and emphasizing the need for enhanced pollution control measures. Finally, we conclude our research by summarizing the key findings derived from our evaluation using the Ω-model. Additionally, we propose potential avenues for future research, highlighting areas where further investigation could lead to advancements in water quality assessment and management strategies, particularly for vital water sources like the Haora River.