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Position: Home > Articles > 基于云模型和GIS的神农架林区洪灾风险评价 Hubei Agricultural Sciences 2018 (13)

基于云模型和GIS的神农架林区洪灾风险评价

作  者：
汪婷;何亚伯;常秀峰
关键词：
洪水灾害;风险评价;云模型;熵权修正;神农架林区
摘  要：
以神农架林区内10 m*10 m大小的区域为研究单元,从灾害损失成因和洪灾形成机制出发,形成包含自然环境危险性和承灾体承灾能力两大部分20余项指标,建立了基于云模型和熵值的洪灾风险综合评价模型,从灾害成因和灾损成因的角度出发对山区村镇洪灾风险的各成分进行了指标因子分析,使用逆向云发生器结合熵值修正的方法确定各级指标权重,通过GIS实现指标的空间数据和属性数据的表达,并予以评价度量,最后结合权重获取水位上升5 m洪水强度下的自然环境危险性、承灾体承灾能力,用洪灾自然危险性评价结果代表值减去承灾能力代表值得到洪灾综合风险评价结果,为林区规划提供科学依据.结果表明,林区的灾害危险区域分布广泛,带有一定的集中度,主要因为全区自然环境危险度较高,而大部分地区经济发展落后、灾害防御工事缺失或不健全;风险较高的区域主要有木鱼镇、九湖镇、松柏镇、阳日镇、宋洛乡东部,下谷坪乡、新华镇和松柏镇北部风险相对较低.
作  者：
WANG Ting;HE Ya-bo;CHANG Xiu-feng;School of Civil Engineering,Wuhan University;
单  位：
WANG Ting%HE Ya-bo%CHANG Xiu-feng%School of Civil Engineering,Wuhan University
关键词：
flood disaster;;risk assessment;;cloud model;;entropy correction;;Shennongjia forest region
摘  要：
The area of the size of 10 meters by 10 meters in Shennongjia forest region is used as the research unit, from the flood disaster loss causes and formation mechanism of the formation of the natural environment including hazard and disaster bearing capacity of two parts more than 20 indicators, the establishment of a comprehensive evaluation of flood risk model based on cloud model and entropy of each component. The mountain village flood risk from the cause of disaster and disaster damage causes the angle of index factor analysis, using reverse cloud generator method combined with entropy correction to determine the index weight at all levels, through the realization of GIS expression, spatial data and attribute data and evaluation metrics, finally obtain the weight of the water level rise of natural environment risk, 5 meters of flood intensity under the disaster disaster bearing capacity for flood risk assessment results represent natural values minus the disaster bearing capacity to flood risk assessment results, in order to provide scientific basis for forest planning. The results show that the distribution of forest disaster risk area wide, with a certain degree of concentration, mainly because of the natural environment risk degree is higher, while the economic development of backward areas, most disaster fortifications lack or not perfect; the distribution of Muyu town and Jiuhu town and Pine Town, Yangri Town, song Luo Xiang Eastern valley high risk.Ping Xiang, Xinhua Town and the cypress northern town of lower risk.

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