利用降水资料、地形资料与社会经济数据,建立楚雄彝族自治州(以下简称楚雄州)洪涝风险评估体系及评估模型.运用层次分析法计算出各个洪涝指标的权重值,再用加权综合评价法建立各影响因子模型,并用GIS(Geographic Information System)软...利用降水资料、地形资料与社会经济数据,建立楚雄彝族自治州(以下简称楚雄州)洪涝风险评估体系及评估模型.运用层次分析法计算出各个洪涝指标的权重值,再用加权综合评价法建立各影响因子模型,并用GIS(Geographic Information System)软件对数据结果制图,对致涝因子危险性、孕涝因子敏感性和承涝因子脆弱性3个指标进行分析,得到楚雄州洪涝风险的危险性、敏感性、脆弱性和综合风险评估指数.结果表明:楚雄州致涝因子危险性最高的是双柏县,危险性值是0.575,危险性最低的区域是元谋县,危险性值是0.067;楚雄州孕涝因子敏感性较高的是元谋县,敏感性值是0.392,敏感性最低的是双柏县,敏感性值是0.074;楚雄州承涝因子脆弱性最高的区域是双柏县,脆弱性值是0.194,脆弱性最低的区域是楚雄市,脆弱性值是0.011.洪涝风险综合评估的最高风险区域主要是双柏县,风险指数是0.437,最低风险的区域主要是元谋县,风险指数是0.137.展开更多
Methods of rainstorm disaster risk monitoring(RDRM)based on retrieved satellite rainfall data are studied.Due to significant regional differences,the global rainstorm disasters are not only affected by geography(such ...Methods of rainstorm disaster risk monitoring(RDRM)based on retrieved satellite rainfall data are studied.Due to significant regional differences,the global rainstorm disasters are not only affected by geography(such as topography and surface properties),but also by climate events.It is necessary to study rainstorm disaster-causing factors,hazard-formative environments,and hazard-affected incidents based on the climate distribution of precipitation and rainstorms worldwide.According to a global flood disaster dataset for the last 20 years,the top four flood disaster causes(accounting for 96.8%in total)related to rainstorms,from most to least influential,are heavy rain(accounting for 61.6%),brief torrential rain(16.7%),monsoonal rain(9.4%),and tropical cyclone/storm rain(9.1%).A dynamic global rainstorm disaster threshold is identified by using global climate data based on 3319 rainstorm-induced floods and rainfall data retrieved by satellites in the last 20 years.Taking the 7-day accumulated rainfall,3-and 12-h maximum rainfall,24-h rainfall,rainstorm threshold,and others as the main parameters,a rainstorm intensity index is constructed.Calculation and global mapping of hazard-formative environmental factor and hazard-affected body factor of rainstorm disasters are performed based on terrain and river data,population data,and economic data.Finally,a satellite remote sensing RDRM model is developed,incorporating the above three factors(rainstorm intensity index,hazard-formative environment factor,and hazard-affected body factor).The results show that the model can well capture the rainstorm disasters that happened in the middle and lower reaches of the Yangtze River in China and in South Asia in 2020.展开更多
文摘利用降水资料、地形资料与社会经济数据,建立楚雄彝族自治州(以下简称楚雄州)洪涝风险评估体系及评估模型.运用层次分析法计算出各个洪涝指标的权重值,再用加权综合评价法建立各影响因子模型,并用GIS(Geographic Information System)软件对数据结果制图,对致涝因子危险性、孕涝因子敏感性和承涝因子脆弱性3个指标进行分析,得到楚雄州洪涝风险的危险性、敏感性、脆弱性和综合风险评估指数.结果表明:楚雄州致涝因子危险性最高的是双柏县,危险性值是0.575,危险性最低的区域是元谋县,危险性值是0.067;楚雄州孕涝因子敏感性较高的是元谋县,敏感性值是0.392,敏感性最低的是双柏县,敏感性值是0.074;楚雄州承涝因子脆弱性最高的区域是双柏县,脆弱性值是0.194,脆弱性最低的区域是楚雄市,脆弱性值是0.011.洪涝风险综合评估的最高风险区域主要是双柏县,风险指数是0.437,最低风险的区域主要是元谋县,风险指数是0.137.
基金Supported by the National Key Research and Development Program of China(2018YFC1506500)Open Research Fund of Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province(SZKT2016001)。
文摘Methods of rainstorm disaster risk monitoring(RDRM)based on retrieved satellite rainfall data are studied.Due to significant regional differences,the global rainstorm disasters are not only affected by geography(such as topography and surface properties),but also by climate events.It is necessary to study rainstorm disaster-causing factors,hazard-formative environments,and hazard-affected incidents based on the climate distribution of precipitation and rainstorms worldwide.According to a global flood disaster dataset for the last 20 years,the top four flood disaster causes(accounting for 96.8%in total)related to rainstorms,from most to least influential,are heavy rain(accounting for 61.6%),brief torrential rain(16.7%),monsoonal rain(9.4%),and tropical cyclone/storm rain(9.1%).A dynamic global rainstorm disaster threshold is identified by using global climate data based on 3319 rainstorm-induced floods and rainfall data retrieved by satellites in the last 20 years.Taking the 7-day accumulated rainfall,3-and 12-h maximum rainfall,24-h rainfall,rainstorm threshold,and others as the main parameters,a rainstorm intensity index is constructed.Calculation and global mapping of hazard-formative environmental factor and hazard-affected body factor of rainstorm disasters are performed based on terrain and river data,population data,and economic data.Finally,a satellite remote sensing RDRM model is developed,incorporating the above three factors(rainstorm intensity index,hazard-formative environment factor,and hazard-affected body factor).The results show that the model can well capture the rainstorm disasters that happened in the middle and lower reaches of the Yangtze River in China and in South Asia in 2020.