| 内蒙古锡林郭勒盟牧区雪灾风险评估研究 |
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| 引用本文： | 德勒格日玛,李一平,孟雪峰,田颖,计燕霞,张莫日根.内蒙古锡林郭勒盟牧区雪灾风险评估研究[J].冰川冻土,2020,42(4):1353-1362. |
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| 作者姓名： | 德勒格日玛 李一平 孟雪峰 田颖 计燕霞 张莫日根 |
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| 作者单位： | 1.南京信息工程大学, 江苏 南京 210044;2.内蒙古自治区气象台, 内蒙古 呼和浩特 010051;3.内蒙古气象培训干部学院, 内蒙古 呼和浩特 010051 |
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| 基金项目： | 内蒙古暴雪（暴风雪）专家型预报员创新团队;国家自然科学基金项目(41265004) |
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| 摘 要： | 选取内蒙古锡林郭勒盟与积雪有关的雪灾致灾指标， 以气温、 风速为气象条件孕灾环境指标， 坡度、 植被盖度为下垫面孕灾环境指标， 人口密度、 牧民纯收入、 人均GDP、 牲畜超载率等数据为承灾体脆弱性指标， 基于BP方法、 层次分析法、 建立了内蒙古锡林郭勒盟白灾综合风险评价体系， 并对其进行了风险评价与区划。为提高灾害评估的准确率， 白灾的灾害等级是以月为尺度进行评定， 选取的气象指标多数都是以月为尺度的指标。研究表明： 白灾与积雪因子高度相关， 是气候灾害， 积雪、 低温、 大风等气象因子长期作用的结果。对白灾尝试用BP神经网络法进行风险评估， 评估的灾害等级和实际灾害等级十分吻合， 用训练好的神经网络对各个旗县（1980 - 2015年）的白灾进行了风险评估， 评估效果理想。因此， 可以通过数值预报产品、 气候预测产品获取相关评价因子， 采用BP方法形成白灾风险预评估产品， 进而应用于雪灾风险评估业务中， 为相关部门提供决策依据。
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| 关 键 词： | 白灾 锡林郭勒盟 内蒙古 BP神经网络 层次分析法 综合风险评价 |
| 收稿时间： | 2018-05-12 |
| 修稿时间： | 2019-04-12 |
Study of the risk evaluation of snow disaster in pastoral areas of Xilingol League， Inner Mongolia |
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| Delegerima,Yiping LI,Xuefeng MENG,Ying TIAN,Yanxia JI,Morgen ZHANG.Study of the risk evaluation of snow disaster in pastoral areas of Xilingol League， Inner Mongolia[J].Journal of Glaciology and Geocryology,2020,42(4):1353-1362. |
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| Authors: | Delegerima Yiping LI Xuefeng MENG Ying TIAN Yanxia JI Morgen ZHANG |
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| Institution: | 1.Nanjing University of Information Science & Technology，Nanjing 210044，China;2.Inner Mongolia Meteorological Observatory，Hohhot 010051，China;3.Inner Mongolia Meteorological Training Center，Hohhot 010051，China |
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| Abstract: | In this study， a model has developed for risk assessment of snow disaster in the pastoral area of Xilingol League based on BP （back propagation artificial neural network）， AHP （analytic hierarchy process） and fuzzy comprehensive evaluation method by using MATLAB， ArcGIS and SPSS. The indicator system of the snow disaster risk assessment is composed of disaster inducing indicators related with the snow depth； the disaster pregnant environment meteorological indicators are mainly constitute of temperature and wind speed indexes； disaster pregnant environment underlying surface indicators are formed by slope and vegetation coverage； vulnerability indicators of disaster bearing bodies are constituted by population density， herdsmen’s net income， GDP per capita， overload rate of livestock. The curve of the predicted hazard level and actual hazard level fits perfectly. Therefore， in this paper， using BP to do the risk assessment of the snow disaster by monthly from November to March of the following year from 1980 to 2015 for each county. Snow hazard is climatic disaster which is highly related with snow cover； It is the result of long-term effects of snow cover， low temperature and strong wind. Except the index that the rainfall during grass growth period， the other indexes are monthly scale， so it can enhance the accuracy of hazard assessment. The effect of risk assessment is comparably ideal， since it is possible to form product of the risk grade of white dzud based on BP method through gaining numerical prediction products and climate prediction products. Consequently， these products will be gradually applied to daily business and provided decision-making basis for party committee and government. |
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| Keywords: | white dzud Xilingol League Inner Mongolia BP neural network analytic hierarchy process comprehensive risk assessment |
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