基于改进熵权法和云模型的安徽省淮河流域防洪减灾能力评估
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摘要
[目的]科学评估防洪减灾能力,为地区制定出科学有效的防洪减灾政策提供参考。[方法]由监测预警能力、防洪除涝能力、抢险救灾能力、灾害管理能力构成防洪减灾能力评估的指标模型,并采用最小相对信息熵原理和秩比法对传统熵权法进行改进,各指标权重由改进的熵权法来计算,然后用改进熵权法以及云模型来建立评估模型,并用来评估安徽省淮河流域的防洪减灾能力。[结果]淮河流域内的防洪减灾能力处于中下等水平;空间差异分布比较明显,流域北部相对高于南部,流域东部相对高于西部;市辖区的防洪减灾能力相对较高,县域防洪减灾能力相对较低;其中肥西县和淮北、蚌埠、淮南、滁州市防洪减灾能力处于高水平;长丰、五河、凤台、萧县和天长、阜阳、六安市属于相对较高水平;肥东、濉溪、砀山、泗县和宿州、界首、明光市为中等水平;其余市县则为相对较低水平。[结论]通过防洪减灾能力评估结果,可以找出流域内各城市防洪减灾能力的差异及存在的薄弱环节,提高流域内整体防洪减灾能力。
[Objective]To evaluate the capacity in flood disaster prevention and reduction in order to provide effective references for the regional government to make scientific and effective policies in flood disaster prevention and reduction.[Methods]The index system for flood disaster prevention and reduction capacity was composed of flood monitoring and warning,flood disaster prevention and waterlogging control,rescuing and rehabilitation as well as disaster management.The traditional entropy weight method was improved based on the minimum relative entropy principle and the rank ration method,and the weight of each index was calculated by the improved entropy method.The improved entropy method and cloud model was used to establish the evaluation model,and the capacity of flood disaster prevention and reduction of the Huaihe River basin in Anhui Province was then assessed.[Results]The flood disaster prevention and reduction capacity was at middle and lower leve land the spatial difference was obvious.Flood disaster prevention capacity in the northern part of the basin was higher than the south,and the eastern part of the basin was higher than the west.The flood disaster and reduction capacity was relatively high in the urban area,and relatively low in the rural area.Feixi County,Huaibei City,Bengbu City,Huainan City,Chuzhou City were at the high level.Changfeng County,Wuhe County,Fengtai County,Xiaoxian County,and Tianchang City,Fuyang City,Luan City was at a relatively high level.Feidong County,Suixi County,Dangshan County,Sixian County,and Suzhou City,Jieshou City,Mingguang City were at a middle level,while the others were at a relatively low and even lower capacity of flood disaster prevention and reduction.[Conclusion]Based on the evaluation results of flood disaster prevention and reduction capacity,the vulnerable spots in flood disaster prevention and reduction in the area can be identified,and the overall capacity in flood prevention can be improved.
[Objective]To evaluate the capacity in flood disaster prevention and reduction in order to provide effective references for the regional government to make scientific and effective policies in flood disaster prevention and reduction.[Methods]The index system for flood disaster prevention and reduction capacity was composed of flood monitoring and warning,flood disaster prevention and waterlogging control,rescuing and rehabilitation as well as disaster management.The traditional entropy weight method was improved based on the minimum relative entropy principle and the rank ration method,and the weight of each index was calculated by the improved entropy method.The improved entropy method and cloud model was used to establish the evaluation model,and the capacity of flood disaster prevention and reduction of the Huaihe River basin in Anhui Province was then assessed.[Results]The flood disaster prevention and reduction capacity was at middle and lower leve land the spatial difference was obvious.Flood disaster prevention capacity in the northern part of the basin was higher than the south,and the eastern part of the basin was higher than the west.The flood disaster and reduction capacity was relatively high in the urban area,and relatively low in the rural area.Feixi County,Huaibei City,Bengbu City,Huainan City,Chuzhou City were at the high level.Changfeng County,Wuhe County,Fengtai County,Xiaoxian County,and Tianchang City,Fuyang City,Luan City was at a relatively high level.Feidong County,Suixi County,Dangshan County,Sixian County,and Suzhou City,Jieshou City,Mingguang City were at a middle level,while the others were at a relatively low and even lower capacity of flood disaster prevention and reduction.[Conclusion]Based on the evaluation results of flood disaster prevention and reduction capacity,the vulnerable spots in flood disaster prevention and reduction in the area can be identified,and the overall capacity in flood prevention can be improved.
引文
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[17]黄大鹏,郑伟,张人和,等.安徽淮河流域灾害防灾减灾能力评估[J].地理研究,2011,30(3):524-530.
[2]王一新,苑希民.基于主成分分析的城市防洪减灾能力综合评价[J].自然灾害学报,2016,25(6):1-8.
[3]孙湖鸿,程先富,倪玲,等.基于云模型和熵权法的巢湖流域防洪减灾能力评估[J].灾害学,2015,30(1):222-227.
[4]顾留碗,王春,李伟涛,等.安徽省淮河流域水灾脆弱性特征及影响因素[J].水土保持通报,2012,32(5):70-75.
[5]李燕,夏广义.淮河中游易涝洼地涝灾特性及成因研究[J].水利水电技术,2012,6(43):93-96.
[6]安徽省统计局.安徽统计年鉴-2013[M].北京:中国统计出版社,2016.
[7]宋丽婧,魏探,宋玲梅.五元系数法-改进熵权法在水质评价中的应用[J].南北水调与水利科技,2015,13(2):268-273.
[8]王正选,王静,杨婷婷,等.基于改进熵权法的水资源承载力评价[J].水资源与水工程学报,2017,28(4):82-87.
[9]吴开业,金菊良.区域生态安全评价的熵组合权重属性识别模型[J].地理科学,2008,28(6):754-758.
[10]Li Deyi.Knowledge representation in KDD based on linguisticatons[J].Journal of Computer Science and Technology,1997,12(6):481-496.
[11]李德毅,杜鹢.不确定性人工智能[M].北京:国防工业出版社,2005.
[12]胡石元,李德仁,刘耀林,等.基于云模型和关联度分析法的土地评价因素权重挖掘[J].武汉大学学报,2006,31(5):432-427.
[13]万昔超,殷伟量,孙鹏,等.基于云模型的暴雨洪涝灾害风险分区评价[J].自然灾害学报,2017,26(4):77-83.
[14]刘常昱,李德毅,杜鹢,等.正太云模型的统计分析[J].信息与空间,2005,34(2):236-252.
[15]李德仁,王树量,李德毅.空间数据挖掘理论与应用[M].北京:科学出版社,2006.
[16]龚艳冰.基于正态云模型和熵权的河西走廊城市化生态风险综合评价[J].干旱区资源与环境,2012,26(5):170-174.
[17]黄大鹏,郑伟,张人和,等.安徽淮河流域灾害防灾减灾能力评估[J].地理研究,2011,30(3):524-530.