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Research Article

Flood susceptibility mapping using fuzzy analytical hierarchy process for Cedar Rapids, Iowa

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Received 29 Aug 2022, Accepted 18 May 2023, Published online: 11 Jun 2023
 

ABSTRACT

Floods affect over 2.2 billion people worldwide, and their frequency is increasing at an alarming rate compared to other disasters. Presidential disaster declarations have issued increasingly almost every year in Iowa for the past 30 years, indicating that the state is on the rise of flood risk. A multi-disciplinary approach is required, in which the underlying hydrologic processes that cause floods are closely linked with watershed-level socio-economic functions using effective collaboration tools to ensure community participation in the co-production of mitigation plans while paying attention to socio-environmental justice principles. Considering the existing limitations and needs, we conducted a flood risk assessment by utilizing geophysical and socio-economic datasets for a case study in Cedar Rapids, Iowa. Flood risk outputs are generated based on three main risk groups: geophysical-based flood risk, socioeconomic risk, and combined flood risk. An extensive literature review is conducted to determine the pairwise comparison matrices for the parameters that are used in the analytical hierarchy process (AHP) and fuzzy AHP methods. Our results indicate that high- and very-high-risk flood susceptibility zones are primarily located in central urban areas with lower elevations, regardless of the method type (AHP or FAHP). According to overall results, a large area of Cedar Rapids consists of a medium risk level according to the flood risk map combined with the fuzzy AHP method. The results show that high and very high-risk areas are 16% of the studied region, medium, low and very low-risk areas correspond to 84%. Besides, nearly 40% of the population lives in high to very high flood risk zones.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement (DAS)

The datasets generated during and/or analysed during the current study are available from the Mendeley Data at https://doi.org/10.17632/2gskdybyfk.1.

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