Flood risk projection in Iran using CMIP6 models and frequency analysis of precipitation.

Autor: Behzadi, Farhad, Javadi, Saman, Hafezi, Shirin, Vasheghani Farahani, Ehsan, Golmohammadi, Golmar
Předmět:
Zdroj: Stochastic Environmental Research & Risk Assessment; Dec2024, Vol. 38 Issue 12, p4843-4861, 19p
Abstrakt: In this research, the impact of climate change on annual maximum daily precipitation (AMP) during the period 2024-2050 and the evaluation of flood risk in Ilam province have been investigated using the outputs of CMIP6 models. After identifying the top-performing CMIP6 models, the annual maximum daily precipitation for return periods of 2, 10, 100, and 1000 years was determined based on fitting 65 probability distributions, considering the 1992-2018 observational period and future periods (SSP1-2.6 and SSP5-8.5). The study also integrates hazard, vulnerability, and exposure components to assess flood risk at various return periods (2, 10, 100, and 1000 years). Vulnerability and exposure assessment involved the selection of indicators such as hamlet density (HD), land use (LU), population density (PD), land cover (LC), SAVI vegetation index, digital elevation model (DEM), slope, soil erodibility (SE), drainage density (DD), and distance from drainage (DFD). The AHP-Entropy weight method was employed to determine the relative importance of each component. The results indicated that changes in annual maximum daily precipitation and flood risk under the SSP1 scenario did not differ significantly from the observational period, exhibiting similar trends and patterns. However, conditions under the SSP5 scenario differed, showing significant fluctuations in annual maximum daily precipitation, particularly for the 1000-year return period, resulting in increased high-risk areas. For instance, in the SSP5-8.5 scenario, the moderate-risk area for the 1000-year return period expanded from 7% to over 13%, and a new high-risk classification arose, covering 5% of the province's area, which is unprecedented in the other scenarios. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index