A stochastic multi-criteria decision making framework for robust water resources management under uncertainty

Abstract

Water planner and managers always work in a changing and uncertain environment, since the majority of water resource-related data is imprecise or uncertain to some extent. MCDM (multi-criteria decision making) is a well-suited decision support tool for water resources management, however multiple uncertainties existed in criteria weights (CWs) and performance values (PVs) hinder the application of MCDM methods in real-world problems. This paper proposes an application-oriented stochastic MCDM framework for robust water resources management under uncertainty. A weight aggregation approach based on the game theory coupled with feasible weight space (FWS) is developed for conflict resolution and uncertainty estimation. We propose a novel SMAA-GRA model by combining the stochastic multi-criteria acceptability analysis (SMAA) theory and grey relational analysis (GRA). The risk of errors in decision making and rank uncertainty degree are utilized to assess decision-making uncertainty. We perform significance analysis to examine the impacts of input parameter uncertainties on the final assessment of alternatives. The proposed framework is demonstrated via two water resources management case studies. Numerical experiments are conducted to investigate the robustness and computational efficiency of the framework as well as the effects of uncertainty level and probability distribution type on decision-making results. The results indicate that the framework enables water managers to examine the robustness of final decisions and allows a risk-informed water resource decision to be made with higher reliabilities.