草业学报2017，Vol.26Issue(2)：10-20,11.DOI:10.11686/cyxb2016108
青海牧区雪灾综合风险评估
Comprehensive risk assessment of snow disasters in Qinghai Province
摘要
Abstract
We collected data on 19 factors,including social,economic,and meteorological factors,leading to snow disasters in Qinghai Province.A combination of subjective and objective methods was used to filter these data.Then,logistic regression models were used to further screen the initial factors and identify five risk assessment factors (per capita gross domestic product,annual average temperature,number of snow-covered days,maximum snow depth,and slope).These data were analyzed using ArcGIS to construct a snow disaster average risk zoning map from 2001-2007 for the Qinghai region,to illustrate the spatial distribution of different snow disaster levels.The results of the subjective and objective analyses indicated that the key factors leading to snow disasters were not only natural and meteorological factors,but also social economic factors.The average risk distribution of snow disasters,and risk factors (maximum snow depth,slope,number of snowcovered days) showed consistent trends,in contrast to the trends in the distribution of annual mean temperature and per capita gross domestic product.The risk of snow disasters was higher in the south and lower in the north of Qinghai Province.The high risk areas were mainly distributed in the south region of Qinghai Province including Chengduo,Yushu,Xiangqian,Dari,Gande,and Maqin,while the low-risk areas included the Qaidam Basin in the northwest and the eastern agricultural region.A high risk of snow disasters was associated with topography and geomorphology.Mountainous areas above 4000 m (including the Qilian,Kunlun,Tanggula,Bayankala,and Anyemaqen mountains) were high-risk areas for snow disasters in Qinghai Province.关键词
青海/雪灾灾害风险/Logistic回归Key words
Qinghai/the snow disaster risk/Logistic regression model引用本文复制引用
马晓芳,黄晓东,邓婕,王云龙,梁天刚..青海牧区雪灾综合风险评估[J].草业学报,2017,26(2):10-20,11.基金项目
国家自然科学基金项目(31372367)和国家重点基础研究发展计划项目(2013CBA01802)资助. （31372367）
