Urban flood disaster risk management using multi-criteria decision-making methods: A scoping review

Abstract

Statistical data indicates a rising trend in the frequency and unpredictability of floods globally. Regions traditionally less affected by flooding are reportedly experiencing an increased impact, underscoring the widespread nature of this phenomenon. Over the past decade, the overall incidence of floods has significantly increased, affecting billions of people worldwide. If appropriate measures are not taken, floods driven by climate change, urbanization, and the consequences of human activities will continue to increase in frequency and intensity, leading to even greater economic, social, and environmental losses. Proper selection of management strategies and risk reduction measures is becoming particularly important for reducing flood risks. Multi-Criteria Decision Making (MCDM) methods are well-suited for addressing such complex, multi-criteria problems. Therefore, this study aims to explore the research fields of MCDM application in flood management and identify the most widely used methods. This is done to clarify their benefits and enhance their applicability. The Systematic Literature Review (SLR) revealed that the research field is broad and dynamic, evolving over the decades. However, the application of MCDM remains popular and, according to current trends, continues to gain popularity. New research fields are also emerging, such as “Identification and/or Mapping of Flood-Prone Areas” and “Sustainable Infrastructure Assessment”, highlighting scientist growing concern about the importance of evaluating vulnerable areas and applying sustainable solutions to address flood management challenges. The findings are particularly relevant to real estate and property management, as they support the development of evidence-based frameworks for assessing property-level flood resilience and for guiding investment decisions to protect built assets.

Affiliated Institutions

• Vilnius Gediminas Technical University LT

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