Towards a flood vulnerability assessment of watershed using integration of decision-making trial and evaluation laboratory, analytical network process, and fuzzy theories

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.

Download Full-text

Participatory flood vulnerability assessment: a multi-criteria approach

10.5194/hess-2017-368 ◽

2017 ◽

Author(s):

Mariana Madruga de Brito ◽

Mariele Evers ◽

Adrian Almoradie

Keyword(s):

Vulnerability Assessment ◽

Vulnerability Index ◽

Private Companies ◽

Flood Vulnerability ◽

Governmental Organizations ◽

Network Process ◽

Vulnerability Maps ◽

Criteria Importance ◽

Hierarchy Process ◽

Flood Vulnerability Assessment

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.

Download Full-text

Towards a Flood Vulnerability Assessment of Watershed Using Integration of Decision Making Trial and Evaluation Laboratory, Analytical Network Process, and Fuzzy Theories

10.21203/rs.3.rs-276992/v1 ◽

2021 ◽

Author(s):

Farzaneh Sajedi Hosseini ◽

Shahram Khalighi Sigaroodi ◽

Ali Salajegheh ◽

Alireza Moghaddamnia ◽

Bahram Choubin

Keyword(s):

Decision Making ◽

Land Use ◽

Data Availability ◽

Fuzzy Membership Function ◽

Residential Areas ◽

Flood Vulnerability ◽

Analytical Network Process ◽

Integrated Method ◽

Mining Areas ◽

Network Process

Abstract Among natural disasters, flood is increasingly recognized as a serious worldwide concern that causes the most damages in parts of agriculture, fishery, housing, and infrastructure, and strongly affects economic and social activities. Universally, there is a requirement to increase our conception of flood vulnerability and to outstretch methods and tools to assess it. Spatial analysis of flood vulnerability is part of non-structural measures to prevent and reduce flood destructive effects. Hence, the current study proposes a methodology for assessing the flood vulnerability in the area of watershed in a severely flooded area of Iran (i.e., Kashkan Watershed). First interdependency analysis among criteria (including population density, PD; livestock density, LD; percentage of farmers and ranchers, PFR; distance to industrial and mining areas, DTIM; distance to tourist and cultural heritage areas, DTTCH; land use; distance to residential areas, DTRe; distance to road, DTR; and distance to stream, DTS) was conducted using the decision-making trial and evaluation laboratory (DEMATEL) method. Hence, the cause and effect factors and their interaction levels in the whole network were investigated. Then, using the interdependency relationships among criteria, a network structure from flood vulnerability factors to determine their importance of factors was constructed and the analytical network process (ANP) was applied. Finally, with aim of overcome ambiguity, reduce uncertainty, and keep the data availability, an appropriate Fuzzy membership function was applied to each layer by analyzing the relationship of each layer with flood vulnerability. Importance analysis indicated that the variables of land use (0.197), DTS (0.181), PD (0.180), DTRe (0.140), and DTR (0.138) were the most important variables. The flood vulnerability map produced by the integrated method of DEMATEL-ANP-FUZZY showed that about 19.2% of the region has a high to very high flood vulnerability.

Download Full-text