Flash flood-risk areas zoning using integration of decision-making trial and evaluation laboratory, GIS-based analytic network process and satellite-derived information

Article


Taherizadeh, Mehrnoosh, Niknam, Arman, Nguyen-Huy, Thong, Mezősi, Gábor and Sarli, Reza. 2023. "Flash flood-risk areas zoning using integration of decision-making trial and evaluation laboratory, GIS-based analytic network process and satellite-derived information." Natural Hazards. 118 (3), p. 2309–2335. https://doi.org/10.1007/s11069-023-06089-5
Article Title

Flash flood-risk areas zoning using integration of decision-making trial and evaluation laboratory, GIS-based analytic network process and satellite-derived information

ERA Journal ID1986
Article CategoryArticle
AuthorsTaherizadeh, Mehrnoosh, Niknam, Arman, Nguyen-Huy, Thong, Mezősi, Gábor and Sarli, Reza
Journal TitleNatural Hazards
Journal Citation118 (3), p. 2309–2335
Number of Pages27
Year2023
PublisherSpringer
Place of PublicationSwitzerland
ISSN0921-030X
1573-0840
Digital Object Identifier (DOI)https://doi.org/10.1007/s11069-023-06089-5
Web Address (URL)https://link.springer.com/article/10.1007/s11069-023-06089-5
Abstract

Assessing areas prone to flash floods is crucial for effective disaster management and mitigation. This study proposes a framework for mapping flood-prone areas by integrating geographic information system (GIS), remote sensing data, and multi-criteria decision-making (MCDM) techniques. The hybrid MCDM model combines the decision-making trial and evaluation laboratory (DEMATEL) with GIS-based analytic network process (ANP) to evaluate flood vulnerability in Golestan province, Iran. Fourteen criteria related to flood potential, including elevation, slope, aspect, vegetation density, soil moisture, flow direction, river distance, rainfall and runoff, flow time, geomorphology, drainage density, soil type, lithology, and land use, were considered. In areas where official data was lacking, a questionnaire was administered to gather information from 15 specialists, experts, and 20 local managers. The relationships between criteria were analyzed using the DEMATEL method, and their weights were determined using the ANP method. Topography was found to have the greatest impact on flood risk, followed by the type of surface and vegetation cover. Hydrographic, soil and geology, climatic also influence flooding in the region. The study identified the northern and central parts of the study area being at higher risk of flooding compared to the southern part. Based on the flood intensity map, 68 villages (50% of all villages in the Qarasu watershed) with a population of approximately 83,595 were identified as at risk of flooding. The proposed GIS-DANP model provides a valuable tool for flood management and decision-making, aiding in risk reduction and minimizing casualties.

KeywordsNatural hazards; Flash food; Risk; MCDM; GIS-DANP; Qarasu
ANZSRC Field of Research 2020370101. Adverse weather events
370401. Computational modelling and simulation in earth sciences
Byline AffiliationsUniversity of Szeged, Hungary
Centre for Applied Climate Sciences
University of Agriculture in Krakow, Poland
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