A Game-Theoretic Combination Weighting–TOPSIS Integrated Model for Sustainable Floodplain Risk Assessment Under Multi-Return-Period Scenarios

Xuejing Ruan, Hai Sun (), Qiwei Yu, Wenchi Shou and Jun Wang
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Xuejing Ruan: College of Civil Engineering and Architecture, Qingdao Agricultural University, Qingdao 266109, China
Hai Sun: College of Engineering, Ocean University of China, Qingdao 266100, China
Qiwei Yu: College of Engineering, Ocean University of China, Qingdao 266100, China
Wenchi Shou: School of Engineering, Design and Built Environment, Western Sydney University, Sydney 2745, Australia
Jun Wang: School of Engineering, Design and Built Environment, Western Sydney University, Sydney 2745, Australia

Sustainability, 2025, vol. 17, issue 12, 1-25

Abstract: Global climate change has altered precipitation patterns, leading to an increased frequency and intensity of extreme rainfall events and introducing greater uncertainty to flood risk in river basins. Traditional assessments often rely on static indicators and single-design scenarios, failing to reflect the dynamic evolution of floods under varying intensities. Additionally, oversimplified topographic representations compromise the accuracy of high-risk-zone identification, limiting the effectiveness of precision flood management. To address these limitations, this study constructs multi-return-period flood scenarios and applies a coupled 1D/2D hydrodynamic model to analyze the spatial evolution of flood hazards and extract refined hazard indicators. A multi-source weighting framework is proposed by integrating the triangular fuzzy analytic hierarchy process (TFAHP) and the entropy weight method–criteria importance through intercriteria correlation (EWM-CRITIC), with game-theoretic strategies employed to achieve optimal balance among different weighting sources. These are combined with the technique for order preference by similarity to an ideal solution (TOPSIS) to develop a continuous flood risk assessment model. The approach is applied to the Georges River Basin in Australia. The findings support data-driven flood risk management strategies that benefit policymakers, urban planners, and emergency services, while also empowering local communities to better prepare for and respond to flood risks. By promoting resilient, inclusive, and sustainable urban development, this research directly contributes to the achievement of United Nations Sustainable Development Goal 11 (Sustainable Cities and Communities).

Keywords: basin flood; multi-return period; simulation modeling; game-theoretic combination weighting; risk assessment; sustainable flood management (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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