Evaluation of widespread flooding of the Karkheh Basin in Iran using SWAT model and GLDAS database

Vahid Shokri Kuchak (), Saeed Morid () and Majid Delavar ()
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Vahid Shokri Kuchak: Tarbiat Modares University
Saeed Morid: Tarbiat Modares University
Majid Delavar: Tarbiat Modares University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2023, vol. 117, issue 3, No 3, 2165-2185

Abstract: Abstract Karkheh basin is a flood-prone region in Iran that was severely affected by devastating river floods in 2019. This study addressed some of the factors that affected on this event and were emphasized in the government inquiry committee. These include strategic questions such as the effect of prior precipitation in the basin and how the dams could mitigate the floods peak and volume. These questions as well as deficits in the rainfall data led to the application of the Soil and Water Assessment Tool model and the global land data assimilation system rainfall data to address the research questions. The results showed the initial managements of the dams prior to the occurrence of these floods was definitely affected by a decade continuous drought in the basin and the concerns about its continuation in 2019. The events occurred during March and April 2019, however, the precipitation occurred prior on October 2018 along with the resulted snowpack and soil saturation played a significant role in intensifying the floods. Although there were some limitations for the full operation of Seymareh Dam, the decision regarding its full operation could reduce the peak inflow to the Karkheh Dam from 8529 to 5447 m3/s. Finally, it is crucial to provide more accurate prediction systems, undertaking rapid and flexible responses and do not be misled by continuous droughts. Graphic Abstract Flowchart of the databases and models to address the research questions

Keywords: The 2019 flood events; Karkheh basin; SWAT model; GLDAS database; Iran (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11069-023-05881-7

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