TY - JOUR
T1 - Flood vulnerability analysis using different aggregation frameworks across watersheds of Ardabil province, northwestern Iran
AU - Azizi, Elham
AU - Nikoo, Mohammad Reza
AU - Mostafazadeh, Raoof
AU - Hazbavi, Zeinab
N1 - Funding Information:
The support of the University of Mohaghegh Ardabili, Iran who provided the facilities to do the present study is appreciated. The authors are also very grateful to the editor and reviewers for their comments and suggestions on improving this study.
Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/6/1
Y1 - 2023/6/1
N2 - Flood-vulnerable-area selection could be interpreted as an intricate multiple-criteria decision-making (MCDM) problem. Lacking systematic flood vulnerability maps in Iran usually leaves the National Disaster Management Organization and provincial authorities to rely on limited knowledge to inform their emergency actions. Therefore, the present study was conducted as pioneer research in flood problematization for solving disaster issues that have not been adequately considered in the country. To obtain a more trustworthy and safer decision, a complex set of multivariate flood vulnerability assessments was done for 26 watersheds of Ardabil province using the novel-ensemble MCDM frameworks. Towards this, the complex proportional assessment of alternatives (COPRAS) and the UK Department for International Development (DFID) approach was integrated with widely used weighting methods of Shannon's entropy (Entropy) and analytical hierarchy process (AHP). Finally, four different aggregation frameworks of COPRAS-Entropy, COPRAS-AHP, DFID-Entropy, and DFID-AHP were developed and compared based on 19 criteria and three factors (exposure, sensitivity, and resilience). The flood vulnerability was obtained as 0.70 ± 0.13, 0.66 ± 0.18, 0.17 ± 0.10, and 0.20 ± 0.15, respectively, based on COPRAS-Entropy, COPRAS-AHP, DFID-Entropy, and DFID-AHP. As can be seen, higher values were estimated according to COPRAS-based frameworks rather than DFID-based frameworks, except for resilience. The top-ranked watersheds in terms of exposure (i.e., Mashiran) and sensitivity (i.e., Samian) produced by aggregation frameworks match entirely. However, the top-ranked watersheds based on resilience and flood vulnerability slightly mismatch among the used aggregation's frameworks. These findings help the responsible authorities for natural disaster risk reduction to promote sustainable development processes and equitable access to financial resources.
AB - Flood-vulnerable-area selection could be interpreted as an intricate multiple-criteria decision-making (MCDM) problem. Lacking systematic flood vulnerability maps in Iran usually leaves the National Disaster Management Organization and provincial authorities to rely on limited knowledge to inform their emergency actions. Therefore, the present study was conducted as pioneer research in flood problematization for solving disaster issues that have not been adequately considered in the country. To obtain a more trustworthy and safer decision, a complex set of multivariate flood vulnerability assessments was done for 26 watersheds of Ardabil province using the novel-ensemble MCDM frameworks. Towards this, the complex proportional assessment of alternatives (COPRAS) and the UK Department for International Development (DFID) approach was integrated with widely used weighting methods of Shannon's entropy (Entropy) and analytical hierarchy process (AHP). Finally, four different aggregation frameworks of COPRAS-Entropy, COPRAS-AHP, DFID-Entropy, and DFID-AHP were developed and compared based on 19 criteria and three factors (exposure, sensitivity, and resilience). The flood vulnerability was obtained as 0.70 ± 0.13, 0.66 ± 0.18, 0.17 ± 0.10, and 0.20 ± 0.15, respectively, based on COPRAS-Entropy, COPRAS-AHP, DFID-Entropy, and DFID-AHP. As can be seen, higher values were estimated according to COPRAS-based frameworks rather than DFID-based frameworks, except for resilience. The top-ranked watersheds in terms of exposure (i.e., Mashiran) and sensitivity (i.e., Samian) produced by aggregation frameworks match entirely. However, the top-ranked watersheds based on resilience and flood vulnerability slightly mismatch among the used aggregation's frameworks. These findings help the responsible authorities for natural disaster risk reduction to promote sustainable development processes and equitable access to financial resources.
KW - Environmental impact
KW - Flood zoning
KW - Index-oriented evaluation
KW - Resilience
KW - Weighting and ranking
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UR - https://www.mendeley.com/catalogue/2c0063f9-aaca-36cd-81fa-304a845e706d/
U2 - 10.1016/j.ijdrr.2023.103680
DO - 10.1016/j.ijdrr.2023.103680
M3 - Article
AN - SCOPUS:85153225918
SN - 2212-4209
VL - 91
JO - International Journal of Disaster Risk Reduction
JF - International Journal of Disaster Risk Reduction
M1 - 103680
ER -