Integration of SWAT, SDSM, AHP, and TOPSIS to detect flood-prone areas

Mehdi Karami, Jahangir Abedi Koupai () and Seyed Alireza Gohari
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Mehdi Karami: Isfahan University of Technology
Jahangir Abedi Koupai: Isfahan University of Technology
Seyed Alireza Gohari: Isfahan University of Technology

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2024, vol. 120, issue 7, No 15, 6307-6325

Abstract: Abstract Flood is one of the most frightening dangers in the world, which can cause a lot of human and financial losses. In this study, an attempt has been made to create a flood risk map with higher accuracy by using the combination of SWAT, SDSM, AHP, and TOPSIS models. The flood risk map helps to identify areas that have flood potential. Managers and officials can control and reduce human and financial losses caused by floods by using such maps and adopting correct policies. In this study, using the SWAT and SDSM models, the future runoff of the Kashkan basin of Lorestan Province in Iran was simulated for the period from 2049 to 2073. Simulated runoff with different return periods of 2, 5, 10, 25, 50, and 100 years was investigated. According to the obtained results, RCP2.6 was introduced as the most dangerous scenario of this watershed with a runoff forecast of 7715 cubic meters per second. With the help of the obtained flood risk map, sub-basins 22, 24, 28, and 32 representing Khorram Abad and Poldakhter cities were introduced as flood-prone areas of the study area. The simulation of the precipitation, maximum and minimum temperature of the studied basin in the period from 2006 to 2100 showed that the maximum and minimum temperatures can get warmer by 1.3–3 C, and 1 to 2 C can get colder. On the other hand, the rainfall of the entire basin will be able to decrease between 54 and 120 mm. The methods used in this study can also be used to detect flood-prone areas for other parts of the world that have been exposed to sudden floods due to climate change. Graphical abstract

Keywords: Flood risk map; Natural hazards; Flood risk analysis; Climate change (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11069-024-06483-7

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