文献类型：期刊文献

中文题名：基于GIS和Logistic回归模型的山洪灾害风险评估

英文题名：Risk assessment of mountain flood based on GIS and Logistic regression model

作者：张永民[1];程维明[2];王楠[2]

第一作者：张永民

机构：[1]河南财经政法大学资源与环境学院;[2]中国科学院地理科学与资源研究所

第一机构：河南财经政法大学资源与环境学院

年份：2018

卷号：28

期号：10

起止页码：21-26

中文期刊名：中国防汛抗旱

外文期刊名：China Flood & Drought Management

语种：中文

中文关键词：山洪灾害;风险评估;Logistic回归模型;GIS;卢氏县

外文关键词：mountain flood;risk assessment;Logistic regression model;GIS;Lushi County

摘要：风险评估是山洪灾害管理必不可少的重要内容,以往的评估多是使用基于AHP对致灾因子进行线性加权求和的方法,但是存在明显的缺点:致灾因子的选取及其权重的赋值存在一定的主观随意性;使用线性加权求和的方式,难以揭示致灾因子与山洪灾害之间复杂的非线性关系,从而导致评估结果出现较大误差。提出了基于GIS和Logistic回归模型的山洪灾害风险评估方法,并以河南卢氏县为例进行了实证研究。结果表明:(1)海拔高度、河网密度和距干流的距离是决定卢氏县山洪灾害危险度空间分布格局的显著致灾因素;同时,城乡工矿居民用地和耕地易损度较高,林地、草地、水域和未利用地的易损度较低;(2)卢氏县洛河、淇河和老灌河的河谷平原及附近山区山洪灾害风险较高,属山洪灾害管理的重点区域;而距离干流较远的高海拔山区山洪灾害风险相对较低;(3)相对于通常使用的AHP线性加权求和方法,Logistic回归模型能够揭示各致灾因素的复杂(非线性)作用及显著水平,能够精确地模拟山洪灾害危险度的空间分布格局,从而为风险评估提供客观、可靠的科学信息。
Risk assessment is necessary for mountain flood management. AHP-based linearly weighted addition approach was often used in existing assessment studies, but this approach has two obvious shortages. One is that some randomness is in- evitable in the selection of hazard factors and the assignment of weight values, and another is that it is difficult for linearly weighted addition method to reveal the nonlinear relationship between hazard factors and mountain flood, leading bigger er- ror. For this reason, a risk assessment method for mountain flood based on GIS and Logistic regression models is proposed and an empirical study is carried out in Lushi County, Henan Province. The results show that： ~The altitude, river network density and distance to main rivers are significant factors determining the spatial pattern of torrent hazard in Lushi County while the role of the slope was not important. Built-up land and cultivated land were more vulnerable ; however, forest land grassland, water, and vacant land were less vulnerable. River plains along Luo River, Qi River and Laoguan River, and near- by mountain areas were covered densely with high risk of mountain flood. Therefore, these areas should become hot spots for mountain flood management. In addition, other high elevation areas, far away from main rivers, were low risk for mountain flood. （3）GIS and logistic regression model based approach are effective for risk assessment of mountain flood hazard. It can accurately characterize the complex/nonlinear action of triggering factors to hazard system, and thus provide objective scientific information to evaluate mountain flood risks