Multi-criteria decision-making for flood risk management: a survey of the current state of the art

• Published in: Natural hazards and earth system sciences Vol. 16; no. 4; pp. 1019 - 1033
• Main Authors: de Brito, Mariana Madruga, Evers, Mariele
• Format: Journal Article
• Language: English
• Published: Katlenburg-Lindau Copernicus GmbH 26.04.2016; Copernicus Publications
• Subjects: Additives; Alternatives; Analytic hierarchy process; Decision making; Emergency preparedness; Environmental risk; Flood management; Flood risk; Floods; Literature reviews; Marine conservation; Methods; Mitigation; Multiple criterion; Objectives; Preferences; Risk management; Surveying; Surveys; Uncertainty analysis; Vulnerability
• ISSN: 1684-9981; 1561-8633; 1684-9981
• DOI: 10.5194/nhess-16-1019-2016

This paper provides a review of multi-criteria decision-making  (MCDM) applications to flood risk management, seeking to highlight trends and identify research gaps. A total of 128 peer-reviewed papers published from 1995 to June 2015 were systematically analysed. Results showed that the number of flood MCDM publications has exponentially grown during this period, with over 82 % of all papers published since 2009. A wide range of applications were identified, with most papers focusing on ranking alternatives for flood mitigation, followed by risk, hazard, and vulnerability assessment. The analytical hierarchy process (AHP) was the most popular method, followed by Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), and Simple Additive Weighting (SAW). Although there is greater interest in MCDM, uncertainty analysis remains an issue and was seldom applied in flood-related studies. In addition, participation of multiple stakeholders has been generally fragmented, focusing on particular stages of the decision-making process, especially on the definition of criteria weights. Therefore, addressing the uncertainties around stakeholders' judgments and endorsing an active participation in all steps of the decision-making process should be explored in future applications. This could help to increase the quality of decisions and the implementation of chosen measures.