Multi-criteria decision-making for flood risk management: a survey of the current state of the art
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 f...
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2016-04-01
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Series: | Natural Hazards and Earth System Sciences |
Online Access: | http://www.nat-hazards-earth-syst-sci.net/16/1019/2016/nhess-16-1019-2016.pdf |
Summary: | 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. |
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ISSN: | 1561-8633 1684-9981 |