Projecting Spatial Patterns of Flood Hazard: Recent Climate and Future Changes over Yangtze River Basin

He, Shiying; Ge, Quansheng; Wu, Shaohong; Dai, Erfu; Chunjian, Shi; Li, Mingqi

doi:10.1080/10042857.2010.10684995

Cited by 1 publication

(1 citation statement)

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“…The monthly data of precipitation at meteorological stations in Guilin City, Xing'an County, Lingchuan County, Yangshuo County, Lipu County, Pingle County and Gongcheng Yao Autonomous County were collected and the annual average precipitation from 1980 to 2020 was calculated as the hazard indicator of disaster causing factors. According to the natural breaks classification method, the disaster-causing hazard indicator was divided into five levels: danger, high risk, moderate risk, low risk, security 30 , and the spatial distribution for the hazard of disaster causing factors in the Lijiang River Basin was obtained (Fig. 4 ).…”

Section: Results and Analysismentioning

confidence: 99%

GIS-based risk assessment of flood disaster in the Lijiang River Basin

Tang

Liju

et al. 2023

Sci Rep

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This study is designed to provide a scientific reference for the establishment of rainstorm and flood disaster prevention system in Guilin region and improve the risk assessment of rainstorm and flood disasters. To realize the goal, a flood risk evaluation model is established by weight analysis methods including the entropy weight method and the analytic hierarchy process from 3 aspects, i.e., risk of disaster causing factors, sensitivity of disaster-pregnant environment and vulnerability of disaster bearing body. For the model, the daily precipitation 1980–2020 of 6 representative national meteorological stations in the Lijiang River Basin was used as reference data of disaster causing factors; six indicators, i.e., NDVI, river network density, geological hazard, slope, slope aspect and terrain undulation were selected as the sensitivity of disaster-pregnant environment; NPP, potential of farmland production, and population density were taken as the criteria for determining the vulnerability of disaster bearing capacity. Meanwhile, ArcGIS was used for analysis and calculation to complete the risk assessment of flood disaster in Lijiang River Basin, Guangxi. The results indicate that: (1) the hazard level of flood disaster causing factors in Lijiang River Basin shows a decreasing distribution pattern from north to south, and high-risk areas cover 3108.47 km2, accounting for 21.29%; (2) the stability grade of disaster-pregnant environment shows a decreasing trend from the surrounding mountains to the plains, and the low-stability and lower-stability areas are mostly found in the low-lying areas around Lijiang River, with an area of 4218.63 km2, accounting for 28.69%; (3) the vulnerability of the disaster bearing body is generally at a low level, and the areas with high level cover 246.96 km2, accounting for only 1.69%; (4) under the combined effect of the above factors, the northern part of Guilin City in the Lijiang River Basin has a high risk of flood disaster.

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Section: Results and Analysismentioning

confidence: 99%