An interval-valued triangular fuzzy decision analytics model for analyzing surface water quality of urban lakes for sustainable management

ABSTRACT We present a comparative assessment of the surface water quality (SWQ) of two prominent lakes in Udaipur, India: Pichola Lake (PL) and Fateh Sagar Lake (FS), during two distinct seasons, pre-monsoon (PM) and post-monsoon (POM). We measure the physicochemical parameters for assessing the SWQs of PL and FS during the PM and POM seasons. The physicochemical parameters are evaluated (in accordance with the standard specifications) within specified intervals, categorized as excellent, allowable, and unsuitable. For a precise discrimination among the alternatives in a scalable modeling framework while offsetting the uncertainty (imposed due to sample collection and seasonality), the present work uses interval-valued TFNs (IVTFNs). We utilize a hybrid multi-criteria decision-making (MCDM) framework, incorporating the opinion weight criteria method (OWCM) and root assessment method (RAM), to rank the SWQs of the lakes. The OWCM method provides a reliable outcome under imprecision and limited data, while avoiding the oversimplification of diverse alternatives. RAM offers a realistic treatment of contributions by inferior criteria while rewarding superior performance. We observe that FS demonstrates an inseparable SWQ for both the PM and POM seasons. At the same time, PL reports a significant effect of seasonal changes, where PM performance is found to be better.