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草业学报 ›› 2017, Vol. 26 ›› Issue (2): 10-20.DOI: 10.11686/cyxb2016108

• 研究论文 • 上一篇    下一篇

青海牧区雪灾综合风险评估

马晓芳, 黄晓东*, 邓婕, 王云龙, 梁天刚   

  1. 兰州大学草地农业科技学院,草地农业生态系统国家重点实验室,甘肃 兰州 730020
  • 收稿日期:2016-03-09 出版日期:2017-02-20 发布日期:2017-02-20
  • 通讯作者: huangxd@lzu.edu.cn
  • 作者简介:马晓芳(1991-),女,甘肃会宁人,在读硕士。E-mail:ymaxiaofangy@163.com
  • 基金资助:
    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

Comprehensive risk assessment of snow disasters in Qinghai Province

MA Xiao-Fang, HUANG Xiao-Dong*, DENG Jie, WANG Yun-Long, LIANG Tian-Gang   

  1. College of Pastoral Agriculture Science and Technology, State Key Laboratory of Grassland Agro-ecosystems, Lanzhou University, Lanzhou 730020, China
  • Received:2016-03-09 Online:2017-02-20 Published:2017-02-20

摘要: 本研究收集了影响青海省雪灾发生的社会经济、自然及气象共计19种因素,通过主客观结合的方法筛选基础因子,再利用Logistic回归模型自我挑选变量功能对初始因子进一步筛选,得到五项风险评价因子,即人均GDP、年均温、最大雪深、积雪覆盖日数及坡度,最后基于ArcGIS平台得到青海地区2001-2007年的雪灾平均风险区划图,并对其划分等级,分析不同雪灾等级在空间上的分布特征。得到以下结论:1)通过主客观的分析方法,得到诱发雪灾形成的关键因素与自然因素、气象因素、社会经济等因素有关;2)青海雪灾平均风险分布与风险因子最大雪深、坡度、积雪覆盖日数具有基本一致的趋势,而与年均温和人均GDP 的分布趋势相反;3)青海地区平均雪灾风险呈现南高北低的态势,其中高风险区主要分布在研究区南部的称多县、玉树县、囊谦县、达日县、甘德县以及玛沁县等地,相反,西北部的柴达木盆地和东部的农业区为低风险区;4)受地形地貌的影响,4000 m以上的山岭地带,即祁连山、昆仑山、唐古拉山、巴颜喀拉山、阿尼玛卿山等为青海雪灾高风险分布之地。

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 snow-covered 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.