A Hybrid Nonlinear-OWA Framework for Comprehensive Risk Assessment in Dam Construction: Evidence from the Gotvand Case Study

Abstract

Large dam projects pose multifaceted risks spanning environmental, biological, health, and security domains. Conventional multi-criteria decision-making (MCDM) methods often suffer from two critical limitations: fixed or subjective weighting schemes and rigid aggregation rules that cannot capture decision-makers’ optimism or pessimism. This study introduces a novel hybrid framework that integrates a nonlinear optimization model with the Ordered Weighted Averaging (OWA) operator under the minimax disparity approach. The nonlinear model ensures fairness in weighting by deriving closed-form solutions that prevent dominance by individual criteria, while the OWA operator provides flexibility by explicitly incorporating the decision-maker’s attitude through the orness parameter. The framework is applied to the Gotvand Dam in Iran, where 19 risk indicators across four categories were evaluated using expert surveys. Results highlight that ecological and health-related risks, such as pest breeding, vegetation change, and biodiversity threats, consistently rank above structural and security hazards. Importantly, rankings remain stable across moderate optimism levels (-) but change at higher optimism (), demonstrating both robustness and sensitivity to stakeholder perspectives. The main contribution of this work lies in combining analytical tractability with decision-making flexibility, offering a mathematically rigorous yet practical tool for dam risk governance. The findings not only shift attention toward long-term ecological and public health risks but also provide a generalizable framework for large-scale infrastructure risk assessment.