Abstract
Flood vulnerability assessment as an essential part of the urban flood management is done by various methods by several researchers. In fact, the improvement in assessment methods is related to the necessity for enhanced decision-making procedures; for instance, economic or infrastructural investments in cities can be assigned in the best form. To achieve this aim, introducing indices for evaluating vulnerability and identifying more vulnerable zones and then doing relevant comparisons can be useful. District flood vulnerability index (DFVI) developed by the author uses 25 indicators in its calculation. Nevertheless, it is obvious that some of these indicators have no effect on the consequences. This paper presents the results of the analysis for the selection of the most significant indicators of the DFVI construction. This index is appropriate for urban district scaling (or: the urban district scale) and the various components of flood vulnerability (social, economic, environmental and physical). DFVI was made by analyzing the indicators’ relevance and by studying the main indicators needed to depict reality of the urban district floods in an effective way. For this purpose, expert elicitation was done by Delphi and AHP method in two separate phases. Then, all these results were combined in order to construct DFVI equations. Finally, the index was implemented in Kuala Lumpur city’s districts. This paper outlines which district of cities (in this case Kuala Lumpur) are most vulnerable to flood hazard with regard to the system’s components, that is, social, physical, environmental and economic.
Highlights
Flood hazards are expected to occur more severely and frequently because of the effects of climate change
Unplanned or poorly planned urbanization, rapid conversion in land use, and fragile flood management are some of the factors contributing to adverse flood effects which would lead to escalating risks for the inhabitants (Nasiri et al 2016)
Recent section is divided into some steps: first is the screening the different indicators of an urban district which will make it vulnerable to floods through Delphi Fuzzy method
Summary
Flood hazards are expected to occur more severely and frequently because of the effects of climate change. Many areas in the world are facing the serious threat of flood hazards. Unplanned or poorly planned urbanization, rapid conversion in land use, and fragile flood management are some of the factors contributing to adverse flood effects which would lead to escalating risks for the inhabitants (Nasiri et al 2016). Nonstructural measures involve numerous mitigation actions but do not include altering the river flow. They cover training, flood insurance, assessment methods, emergency services, land-use planning, construction codes, warning and forecasting, etc. The goal is to reduce loss of life and property, but it is inevitable, even structural measures could have useful consequences for a specific period; they lead to potential threats as well because they rebuild natural processes but do not follow natural rules (Gao et al 2007)
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