耦合激励机制下多灾种综合风险评估方法
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摘要
为解决区域多灾种综合风险评估中忽略多灾种间相互作用、对城市用地规划指导缺乏的问题,建立基于耦合激励机制的多灾种综合风险评估模型。以石家庄中心城区为研究对象,首先,利用地理信息系统(GIS)获取中心城区的地质、地震、火灾、洪水、内涝等典型灾害信息;然后,制定各单灾种之间的空间耦合激励规则;最后,利用有序分位加权集结算子评价多灾种的综合风险。结果表明:极高、高、中等、低、极低危险区的面积分别占26%、19%、31%、21%、3%;综合灾害危险性高的区域主要集中在滹沱河沿岸、重大危险源周边及石家庄断裂带区域,呈集群式分布特点;所得研究结果与实际情况高度吻合,激励模型能精确融合各灾种信息并克服众多不确定性问题,有效实现快速、灵活化的城市综合灾害风险的评估。
In order to solve the problems of neglecting the interaction between multiple disasters and lacking guidance for urban land use planning in regional comprehensive risk assessment of multiple disasters,a comprehensive risk assessment model was built for multiple disasters based on coupling incentive mechanism. The central area of Shijiazhuang city was taken as the research object. Firstly,GIS was used to obtain typical disaster information such as geology,earthquake,fire,flood,and waterlogging. Then,the spatial coupling incentive rules between disasters were constructed. Finally,the integrated risk assessment of multi-hazards was carried out by using the ordered weighted set of settlements. The results show that the areas of extremely high,high,medium,low and extremely low risk areas account for 26%,19%,31%,21% and 3% respectively. Among them,the areas with high comprehensive disaster risks are mainly concentrated along Hutuo River,the periphery of major hazard sources and Shijiazhuang fault zone,which are distributed in clusters. The obtained research results are highly consistent with the actual situation,indicating that the incentive model can accurately integrate various disaster information and overcome many uncertain problems,thus effectively realizing rapid and flexible comprehensive disaster risk assessment for cities.
In order to solve the problems of neglecting the interaction between multiple disasters and lacking guidance for urban land use planning in regional comprehensive risk assessment of multiple disasters,a comprehensive risk assessment model was built for multiple disasters based on coupling incentive mechanism. The central area of Shijiazhuang city was taken as the research object. Firstly,GIS was used to obtain typical disaster information such as geology,earthquake,fire,flood,and waterlogging. Then,the spatial coupling incentive rules between disasters were constructed. Finally,the integrated risk assessment of multi-hazards was carried out by using the ordered weighted set of settlements. The results show that the areas of extremely high,high,medium,low and extremely low risk areas account for 26%,19%,31%,21% and 3% respectively. Among them,the areas with high comprehensive disaster risks are mainly concentrated along Hutuo River,the periphery of major hazard sources and Shijiazhuang fault zone,which are distributed in clusters. The obtained research results are highly consistent with the actual situation,indicating that the incentive model can accurately integrate various disaster information and overcome many uncertain problems,thus effectively realizing rapid and flexible comprehensive disaster risk assessment for cities.
引文
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[14]王述红,张泽,侯文帅,等.综合管廊多灾种耦合致灾风险评价方法[J].东北大学学报:自然科学版,2018,39(6):902-906.WANG Shuhong,ZHANG Ze,HOU Wenshuai,et al. Risk assessment method on multi-disaster coupled hazard for urban utility tunnel[J]. Journal of Northeastern University:Natural Science,2018,39(6):902-906.
[15]李伟伟,易平涛,郭亚军.有序分位加权集结算子及在激励评价中的应用[J].系统工程理论与实践,2017,37(2):452-459.LI Weiwei,YI Pingtao,GUO Yajun. Ordered fractile weighted aggregation operators and the application in incentive evaluation[J]. Systems Engineering-Theory&Practice,2017,37(2):452-459.
[2] International Council of Scientific Unions. A science plan for integrated research on disaster risk:addressing the challenge of natural and human-induced environmental hazards[R],2008.
[3]王威,田杰,王志涛,等.城市综合承灾能力评价的分形模型[J].中国安全科学学报,2011,21(5):171-176.WANG Wei,TIAN Jie,WANG Zhitao,et al. Fractal model for evaluating urban comprehensive disaster-carrying capability[J]. China Safety Science Journal,2011,21(5):171-176.
[4] ARMENAKIS C,NIRUPAMA N. Prioritization of disaster risk in a community using GIS[J]. Natural Hazards,2013,66(1):15-29.
[5] REMO JONATHAN W F,PINTER R N. Hazus-MH earthquake modeling in the central USA[J]. Natural Hazards,2012,63(2):1 055-1 081.
[6] THIERRY P,STIELTJES L,KOUOKAM E,et al. Multi-hazard risk mapping and assessment on an active volcano:the GRINP project at mount cameroon[J]. Natural Hazards,2008,45(3):429-456.
[7]高庆华.中国自然灾害风险与区域安全性分析[M].北京:气象出版社,2005:80-171.
[8]倪晓娇,南颖,朱卫红,等.基于多灾种自然灾害风险的长白山地区生态安全综合评价[J].地理研究,2014,33(7):1 348-1 360.NI Xiaojiao,NAN Ying,ZHU Weihong,et al. Study on comprehensive assessment of ecological security in Changbai mountain region based on multi-hazard natural disasters risk[J]. Geographical Research,2014,33(7):1 348-1 360.
[9]冯浩,张方,戴慎志.综合防灾规划灾害风险评估方法体系研究[J].现代城市研究,2017(8):93-98.FENG Hao,ZHANG Fang,DAI Shenzhi. The research on the method system of risk assessment in multi-hazard mitigation plan[J]. Modern Urban Research,2017(8):93-98.
[10] DELUCA C,BALAJI V. The earth system modeling framework[J]. Springerbriefs in Earth System Sciences,2013,6(1):43-54.
[11] WESTEN V C,KAPPES M S,LUNA B Q,et al. Medium-scale multi-hazard risk assessment of gravitational processes[J].Natural Hazards,2013,34(1):201-231.
[12]卢颖,郭良杰,侯云玥,等.多灾种耦合综合风险评估方法在城市用地规划中的应用[J].浙江大学学报:工学版,2015,49(3):538-546.LU Ying,GUO Liangjie,HOU Yunyue,et al. Comprehensive multi-disaster risk assessment method applicated in urban land-use planning[J]. Journal of Zhejiang University:Engineering Science,2015,49(3):538-546.
[13]盖程程,翁文国,袁宏永.基于GIS的多灾种耦合综合风险评估[J].清华大学学报:自然科学版,2011,51(5):627-631.GAI Chengcheng,WENG Wenguo,YUAN Hongyong. Multi-hazard risk assessment using GIS in urban areas[J].Journal of Tsinghua University:Science and Technology,2011,51(5):627-631.
[14]王述红,张泽,侯文帅,等.综合管廊多灾种耦合致灾风险评价方法[J].东北大学学报:自然科学版,2018,39(6):902-906.WANG Shuhong,ZHANG Ze,HOU Wenshuai,et al. Risk assessment method on multi-disaster coupled hazard for urban utility tunnel[J]. Journal of Northeastern University:Natural Science,2018,39(6):902-906.
[15]李伟伟,易平涛,郭亚军.有序分位加权集结算子及在激励评价中的应用[J].系统工程理论与实践,2017,37(2):452-459.LI Weiwei,YI Pingtao,GUO Yajun. Ordered fractile weighted aggregation operators and the application in incentive evaluation[J]. Systems Engineering-Theory&Practice,2017,37(2):452-459.