| Citation: |
WANG Hao, NIU Quanfu, LIU Bo, LEI Jiaojiao, WANG Gang, ZHANG Ruizhen. Spatial Distribution Prediction of Flash Flood Disaster in Longnan City Based on Particle Swarm Algorithm Combined with MaxEnt Model[J]. Geomatics and Information Science of Wuhan University, 2024, 49(8): 1444-1455. DOI: 10.13203/j.whugis20230219
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Flash floods are natural disasters caused by sudden rise in water levels in mountainous rivers, which are characterized by instantaneity and great destructiveness. In recent years, the frequent occurrence of flash floods in Longnan city, Gansu province, has posed a serious threat to the safety of local people's lives and property, thus it is urgent to carry out a risk assessment of flash floods in this region.
This study takes Longnan city as the study area, and utilizes the MaxEnt model combining with the particle swarm algorithm to evaluate the vulnerability of study area based on 834 flash flood hazard points investigated and 32 disaster-causing factors. It also predicts the spatial pattern changes and potential mass migration trends of the future flash flood vulnerability areas based on three periods of climate data from the current period (2021—2040) and the future period (2041—2060, 2061—2080, 2081—2100).
The area under receiver operating characteristic curve of the results of the study in each period is above 0.85, which indicates that the precision of the results of the method is good. The main cause factors in this study area are driest month precipitation, monthly mean diurnal temperature difference, coefficient of variation of precipitation, warmest month maximum temperature, land use, distance from the river, soil texture, profile curvature, elevation, and topographic relief. The flash flood-prone areas in the study area varies in different periods, but are mainly distributed in Wudu District, Wen County and Tanchang County, and the simulation results for the three future periods (2041—2060, 2061—2080, 2081—2100) reflected a decreasing trend compared with the current period (2021—2040).
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