Development of a Fractional Orthopair Fuzzy MCDM Framework for Sustainable Water Resource Management in Lahore

The evaluation of alternative water sources under uncertain, imprecise, and hesitant environments is a critical challenge in sustainable urban water management. To address this, the present study introduces a novel Fractional Orthopair Fuzzy (FOF) Sets-based multi-criteria decision-making (MCDM) framework that systematically integrates expert uncertainty using hesitancy degrees and fractional parameterization. Leveraging the technique for order preference by similarity to ideal solution (TOPSIS) with standardized parameters (\(\:p=3\), \(\:q=2\)), the model incorporates Entropy-derived weights (\(\:\omega\:\:=\:\text{0.355,0.287,0.358}\)) and a newly formulated FOF weighted average (FOFWA) operator to robustly assess competing water sources. This approach is applied to the case of Lahore, Pakistan, a major metropolitan center confronting a worsening drinking water crisis driven by groundwater depletion (0.49–0.92 m/year), unchecked urban expansion, and pollution of the Ravi River despite receiving substantial annual rainfall (600–700 mm). The model evaluates three alternative water sources Surface Water, Groundwater, and Rainwater across the criteria of Quality, Availability, and Affordability. Results identify Rainwater as the most promising alternative, with a closeness coefficient of 0.8396, indicating its potential to serve as a cost-effective and sustainable resource. The integration of orthopair fuzzy logic and hesitancy metrics allows for nuanced modeling of vagueness in expert evaluations. Sensitivity analysis reveals a ranking deviation of less than 5% under varied weights, and comparative analysis indicates 92.5% decision accuracy and 97.5% stability, affirming the model’s reliability. This framework not only supports strategic interventions by the Water and Sanitation Agency (WASA) of Lahore but also offers a replicable tool for water resource planning in other vulnerable regions worldwide.