scholarly journals Flood Vulnerability Assessment for Prioritizing and Evaluating Rehabilitation of Ungauged Reservoirs Considering Climate Change

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1901
Author(s):  
Sang-Min Jun ◽  
Moon-Seong Kang ◽  
Soonho Hwang ◽  
Jihoon Park ◽  
Jung-Hun Song

The objective of this research was to apply the flood vulnerability assessment to ungauged reservoirs for prioritizing and evaluating the reservoir rehabilitation according to climate change. The flood vulnerability index (FVI) can quantitatively compare the flood vulnerabilities of the analysis targets and can be used for the relative comparison of hydraulic structures to determine the reinforcement priority. In this study, we proposed a simple FVI that contained exposure and adaptive capacity of the hydraulic structure. We selected ten dam heightening reservoirs in Korea and constructed data for flood vulnerability assessment. The FVI was calculated before and after the dam heightening to analyze the priority and effect of reservoir rehabilitation under climate change. Flood vulnerability indices were estimated for four periods (1995s: 1981–2010, 2025s: 2011–2040, 2055s: 2041–2070, 2085s: 2071–2100) and before/after the dam heightening project. As a result, flood vulnerability indices decreased after the dam heightening project for all reservoirs, and the indices have increasing tendencies in the future. The indices developed in this study can be useful to determine the priority and to evaluate the effect of rehabilitation for hydraulic structures.

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ismaila Usman Kaoje ◽  
Muhammad Zulkarnain Abdul Rahman ◽  
Nurul Hazrina Idris ◽  
Tze Huey Tam ◽  
Mohd Radhie Mohd Sallah

Purpose The purpose of this paper is to introduce a geospatial approach for buildings flood vulnerability assessment using an indicator-based method (IBM) to support flood risk assessment and mapping of physical elements at risk in Kota Bharu District, Kelantan, Malaysia. Design/methodology/approach The study developed an indicator-based approach to undertake physical flood vulnerability assessment of buildings. The approach takes into consideration flood hazard intensity, building characteristics and structures surrounding the environment as factors that influence flood vulnerability. The aggregation of the total flood vulnerability index is carried out in a geographic information system (GIS) environment. Findings The results provide a spatial representation of buildings flood vulnerability index in Kota Bharu Malaysia, and the degree of expected vulnerability is expressed on a scale between 0 to 1 (low damage to total damage). Mapping flood vulnerability index of buildings should be considered in future flood mitigation and evacuation planning. Originality/value Unlike other indicator-based methods (IBMs) developed for physical flood vulnerability assessment, in the current study, hazard intensity has been considered and incorporated in the physical flood vulnerability model.


2011 ◽  
Vol 44 (3) ◽  
pp. 231-248 ◽  
Author(s):  
Min-Woo Son ◽  
Jin-Young Sung ◽  
Eun-Sung Chung ◽  
Kyung-Soo Jun

2018 ◽  
Vol 22 (1) ◽  
pp. 373-390 ◽  
Author(s):  
Mariana Madruga de Brito ◽  
Mariele Evers ◽  
Adrian Delos Santos Almoradie

Abstract. This paper presents a participatory multi-criteria decision-making (MCDM) approach for flood vulnerability assessment while considering the relationships between vulnerability criteria. The applicability of the proposed framework is demonstrated in the municipalities of Lajeado and Estrela, Brazil. The model was co-constructed by 101 experts from governmental organizations, universities, research institutes, NGOs, and private companies. Participatory methods such as the Delphi survey, focus groups, and workshops were applied. A participatory problem structuration, in which the modellers work closely with end users, was used to establish the structure of the vulnerability index. The preferences of each participant regarding the criteria importance were spatially modelled through the analytical hierarchy process (AHP) and analytical network process (ANP) multi-criteria methods. Experts were also involved at the end of the modelling exercise for validation. The final product is a set of individual and group flood vulnerability maps. Both AHP and ANP proved to be effective for flood vulnerability assessment; however, ANP is preferred as it considers the dependences among criteria. The participatory approach enabled experts to learn from each other and acknowledge different perspectives towards social learning. The findings highlight that to enhance the credibility and deployment of model results, multiple viewpoints should be integrated without forcing consensus.


2017 ◽  
Author(s):  
Mariana Madruga de Brito ◽  
Mariele Evers ◽  
Adrian Almoradie

Abstract. This paper presents a participatory multi-criteria decision-making (MCDM) approach for flood vulnerability assessment while considering the relationships between vulnerability drivers. The applicability of the proposed framework is demonstrated in the municipalities of Lajeado and Estrela, Brazil. The model was co-constructed by 101 experts from governmental organizations, universities, research institutes, NGOs, and private companies. Participatory methods such as the Delphi survey, focus groups and workshops were applied. A participatory problem structuration, in which the modellers work closely with end-users, was used to establish the structure of the vulnerability index. The preferences of each participant regarding the criteria importance were spatially modelled through the Analytical Hierarchy Process (AHP) and Analytical Network Process (ANP) multi-criteria methods. Experts were also involved at the end of the modelling exercise for validation. The final product is a set of individual and group flood vulnerability maps. Both AHP and ANP proved to be effective for flood vulnerability assessment; however, ANP is preferred as it considers the relationships between vulnerability drivers. The participatory approach enabled experts to learn from each other and acknowledge different perspectives towards social learning. The findings highlight that to enhance the credibility and deployment of model results, multiple viewpoints should be integrated without forcing consensus.


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