Research on the risk of rainstorm and flood disasters in Songliao basin based on CMIP6

Jinggang Chu, Wenyu Ouyang (), Qian Xin, Xuezhi Gu, Xiaoyang Li and Lei Ye
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Jinggang Chu: Dalian University of Technology
Wenyu Ouyang: Dalian University of Technology
Qian Xin: Dalian University of Technology
Xuezhi Gu: Dalian University of Technology
Xiaoyang Li: Dalian University of Technology
Lei Ye: Dalian University of Technology

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2025, vol. 121, issue 9, No 30, 10779-10806

Abstract: Abstract Amid the ongoing impacts of climate change, the frequency and intensity of extreme precipitation, a key driver of flood disasters, have clearly increased. Currently, primarily focus on large-scale basins, often overlooking spatial heterogeneity within watersheds and rarely offering comprehensive frameworks to reliably analyze future extreme precipitation at the watershed scale. This paper presents a comprehensive and detailed framework for future flood risk assessment, which includes an analysis of the ability of various climate models to simulate extreme precipitation events across different spatial and temporal scales within a basin, the construction of regional climate multi-model ensembles, bias correction, and the development of a flood disaster risk assessment model under future scenarios. The Songhua and Liao River Basin (Songliao Basin) serves as a case study for employing CMIP6 climate models to simulate extreme precipitation, utilizing this framework to evaluate future flood risks. The results reveal that the extreme precipitation indices (Rx5day, R20mm, SDII) exhibit a decreasing pattern in magnitude, extending from the southeast to the northwest of the basin. Additionally, the pattern of flood risk variations across time and space under different development scenarios aligns with the shifts in extreme precipitation indices projected for the period between 2025 and 2099, especially in the SSP5-8.5 scenario, where the high-risk zone with a 100-year return period increases by 8.19 times relative to the historical period. By accounting for regional differences in climate model performance, the framework enhances the reliability of future extreme precipitation predictions, enables the analysis of spatiotemporal flood risk changes under various scenarios, and supports flood mitigation and disaster reduction efforts in the basin.

Keywords: Rainstorm and flood disaster risk; CMIP6 models; Future scenarios; Extreme precipitation simulation and prediction; Songliao Basin (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11069-025-07217-z

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