4.5 Article

A Spatial Decision Support Approach for Flood Vulnerability Analysis in Urban Areas: A Case Study of Tehran

出版社

MDPI
DOI: 10.3390/ijgi11070380

关键词

vulnerability mapping; GIS; risk in decision making; sensitivity analysis; Tehran

资金

  1. Agrohydrology Research Group of Tarbiat Modares University [IG-39713]

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This study aims to propose a spatial decision support tool for mapping flood vulnerability in Tehran under different risk scenarios. Several factors were considered, and their weights were determined using expert opinions and the FAHP method. The vulnerability maps for different scenarios were prepared using the OWA method. The results can be used by stakeholders such as urban planners, decision makers, and hydrologists to plan and build resilience against floods.
Preparedness against floods in a hazard management perspective plays a major role in the pre-event phase. Hence, assessing urban vulnerability and resilience towards floods for different risk scenarios is a prerequisite for urban planners and decision makers. Therefore, the main objective of this study is to propose the design and implementation of a spatial decision support tool for mapping flood vulnerability in the metropolis of Tehran under different risk scenarios. Several factors reflecting topographical and hydrological characteristics, demographics, vegetation, land use, and urban features were considered, and their weights were determined using expert opinions and the fuzzy analytic hierarchy process (FAHP) method. Thereafter, a vulnerability map for different risk scenarios was prepared using the ordered weighted averaging (OWA) method. Based on our findings from the vulnerability analysis of the case study, it was concluded that in the optimistic scenario (ORness = 1), more than 36% of Tehran's metropolis area was marked with very high vulnerability, and in the pessimistic scenario (ORness = 0), it was less than 1%was marked with very high vulnerability. The sensitivity analysis of our results confirmed that the validity of the model's outcomes in different scenarios, i.e., high reliability of the model's outcomes. The methodical approach, choice of data, and the presented results and discussions can be exploited by a wide range of stakeholders, e.g., urban planners, decision makers, and hydrologists, to better plan and build resilience against floods.

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