内蒙古草原牧区旱灾监测与风险评价、预警研究——以锡林郭勒盟为例

项目名称： 内蒙古草原牧区旱灾监测与风险评价、预警研究——以锡林郭勒盟为例

项目编号： No.41261099

项目类型： 地区科学基金项目

立项/批准年度： 2013

项目学科： 天文学、地球科学

项目作者： 阿拉腾图娅

作者单位： 内蒙古师范大学

项目金额： 48万元

中文摘要： 内蒙古草原是国际草原科学界关注的重点地区之一。旱灾在世界上被列为第二大自然灾害，内蒙古地区最主要的自然灾害。本研究以内蒙古牧区为研究区，通过野外考察采样、遥感反演、搜集统计数据，①从牧区旱灾发生的驱动因子和表征因子两个角度出发，构建基于驱动-表征的旱灾监测模型系统；②采用数学模型法，构建旱灾灾情、风险孕灾环境、致灾因子和承灾体的风险识别模型群及其分级体系。评价出牧区旱灾致灾因子危险度、孕灾环境敏感度、承灾体脆弱度、灾情损失及综合风险度，系统地表达其空间分布总体规律。进一步诊断每个评价单元- - 草牧场的旱灾风险类型与程度；③采用旱灾监测模型及GIS空间分析、系统模拟，预测旱灾发生强度和范围，预警可能产生的风险。本研究对完善牧区旱灾风险评价指标体系、科学界定评价单元、构建灾害风险系统模型、发展旱灾风险评价与预警技术、方法及灾害学和风险学的发展具有理论意义；可为牧区防灾、减灾提供科学决策依据。

中文关键词： 草原牧区；旱灾风险；干旱监测；风险评价；旱情监测

英文摘要： Inner Mongolian grassland is one of the most important regions which get the scientific community's attentions. And the drought considered widely as the second natural disaster, is also the leading natural calamity in Inner Mongolia. In this study, we obtained the research data by means of field sampling, remote sensing inversion and statistical data collecting in Inner Mongolia grazing district. Based on this, firstly, the driving- characterization drought monitoring model was established considering the respects of driving forces and characterization factor. And then, the Recognition Model of droughts, hazard inducing environment, and hazard factors and the hazard bearing body was built by adopting mathematical model method. The purpose of this model is to assess the risks of drought hazard factors, sensitivity of hazard inducing environment, vulnerable degree of hazard bearing body, loss of disaster situation and the comprehensive risk, and then to show the spatial distribution systematically. And furthermore, is also to diagnose the type and degree of drought risk for each unit. Thirdly, predict the intensity, range, and possible risk by using the monitoring model, spatial analysis of GIS and system simulation. This study has a theoretical significance to perfect the evaluation index system of drought risk

英文关键词： grassland pasturing area；drought risk；drought monitoring；risk assessment；drought severity monitoring