中国地震灾害损失评估:超概率曲线方法与经验数据
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摘要
我国是地震灾害频发的国家,曾遭受重大的人员伤亡和财产损失。地震灾害损失曲线能够反映地震灾害损失分布情况,对于在事前评估中国地震灾害风险,更好地开展防灾减灾工作有非常重要的意义。本文根据超概率曲线理论,提出一种在有限经验数据的基础上,通过计算机模拟生成长时期大样本的模拟灾害事件,以此构建年度地震灾害损失超概率曲线的方法;并且运用1990年-2011年间中国大陆地区历次地震灾害事件的经验数据,分别建立单起地震灾害损失分布模型和年度成灾地震发生次数分布模型,并通过随机循环抽样模拟生成1000年的中国地震损失事件,构建出中国年度地震灾害损失超概率曲线。
China is a country suffering from frequent earthquake disasters,which have caused serious casualties and losses.The earthquake loss curve,which can reflect the distribution of losses brought by earthquake disasters, is very useful in the ex-ante evaluation of China' s earthquake risk,and is very important in improving disaster prevention and reduction.Based on the exceedance probability theory and taking into account limited empirical data, this article developed a method that used computer simulation to generate a long period,large sample simulated earthquake loss sequence,which could be used in constructing the exceedace probability curve of annual earthquake losses.Then,this method was applied to the empirical data of all the earthquake loss events occurred during 1990 to 2011 in mainland China,and the loss distribution model of single earthquake loss event and the frequency distribution model of annual earthquake loss event occurred were built.Based on these two models,a simulated 1000 year earthquake loss sequence was generated through the random circular sampling.Using the simulated sequence,the exceedance probability curve of China' s annual earthquake losses was finally constructed.
China is a country suffering from frequent earthquake disasters,which have caused serious casualties and losses.The earthquake loss curve,which can reflect the distribution of losses brought by earthquake disasters, is very useful in the ex-ante evaluation of China' s earthquake risk,and is very important in improving disaster prevention and reduction.Based on the exceedance probability theory and taking into account limited empirical data, this article developed a method that used computer simulation to generate a long period,large sample simulated earthquake loss sequence,which could be used in constructing the exceedace probability curve of annual earthquake losses.Then,this method was applied to the empirical data of all the earthquake loss events occurred during 1990 to 2011 in mainland China,and the loss distribution model of single earthquake loss event and the frequency distribution model of annual earthquake loss event occurred were built.Based on these two models,a simulated 1000 year earthquake loss sequence was generated through the random circular sampling.Using the simulated sequence,the exceedance probability curve of China' s annual earthquake losses was finally constructed.
引文
[1]Grossi,Patricia,and Howard Kunreuther,eds.Catastrophe modeling:A new approach to managing risk.Vol.25.Springer,2005.
[2]Banks,Erik.Catastrophic risk:analysis and management.Wiley,2005.
[3]Kozlowski,Ronald T.,and Stuart B.Mathewson.Measuring and managing catastrophe risk.National Emergency Training Center,1995.
[4]Ordaz,Mario,and Emilio Rosenblueth."Earthquake magnitude exceedance rate and self-similarity."Earthquake engineering&structural dynamics 18.7(1989):1017-1023.
[5]Burr,Irving W."Cumulative frequency functions."The Annals of Mathematical Statistics 13.2(1942):215-232.
[6]Van Dantzig,David."Economic decision problems for flood prevention."Econometrica:Journal of the Econometric Society(1956):276-287.
[7]Shaw,Daigee,et al."A probabilistic risk analysis for Taipei seismic hazards:an application of HAZ-Taiwan with its pre-processor and post-processor."Proceedings of Asia Oceania Geosciences Society Annual Meeting.2004.
[8]Dong,Weimin."Building a More Profitable Portfolio.Modern Portfolio Theory with Application to Catastrophe Insurance."Reactions Publication(2001).
[9]Cochrane,Harold C."Predicting the economic impact of earthquakes."Social Science Perspectives on the Coming San Francisco Earthquake,Natural Hazards Research Paper 25(1974).
[10]Cochrane,Harold C.,and C.Harold."Knowledge of private loss and the efficiency of protection."Conference on the Economics of Natural Hazards and their Mitigation.1984.
[11]Cole,Sam,Enrique Pantoja Lozano,and V.Razak."Social accounting for disaster preparedness and recovery planning."Technical report NCEER 93(1993).
[12]Munich,R.E.Topics geo:natural catastrophes 2010:analyses,assessments,positions.Munchener Ruck,2010.
[13]Okuyama,Yasuhide."Modeling spatial economic impacts of an earthquake:Input-output approaches."Disaster Prevention and Management 13.4(2004):297-306.
[14]Lin,Jeng Hsiang."Exceedance probability of extensive damage limit for general buildings in Taiwan."Disaster Prevention and Management 21.3(2012):386-397.
[15]Peskin,Henry M.Protecting Industrial Resources Against Nuclear Attack:Interim Report of an Economic Analysis.No.IDA HQ-65-3550.INSTITUTE FOR DEFENSE ANALYSES ARLINGTON VA ECONOMIC AND POLITICAL STUDIES DIV,1965.
[16]REMI Ine,The REMI EDFS-53 Forecasting&Simulation Model,Volume 1,Model Documentation,Chapter4.Amherst,MA:Regional Economic Modeling,1997.
[17]Rose,Adam,and Shu-Yi Liao."Modeling regional economic resilience to disasters:A computable general equilibrium analysis of water service disruptions*."Journal of Regional Science 45.1(2005):75-112.
[18]Rose,Adam,and Shu-Yi Liao."Modeling regional economic resilience to disasters:A computable general equilibrium analysis of water service disruptions."Journal of Regional Science 45.1(2005):75-112.
[19]Tirasirichai,Chakkaphan,and David Enke."Case study:Applying a regional CGE model for estimation of indirect economic losses due to damaged highway bridges."The Engineering Economist 52.4(2007):367-401.
[20]Wetzler,Elliot.The Structure of the IDA Civil Defense Economic Model.No.RP-P-674.INSTITUTE FOR DEFENSE ANALYSES ARLINGTON VA PROGRAM ANALYSIS DIV,1970.
[21]Jang,Jing-Jong,and Jeng-Ru Lee."ANALYSIS OF DESIGN WIND SPEED DISTRIBUTION OF TAIWAN AREA."Journal of Manne Science and Technology 5.1(1997).
[22]Benson,Manuel A.Characteristics of frequency curves based on a theoretical 1,000-year record.US Department of the Interior.Geological Survey,Water Resources Division.1952.
[23]李俊.以Google Earth为平台,基于GDP,人口与场地效应的全球大震损失评估模型[D].合肥:中国科学技术大学,2009.
[24]林均岐,钟江荣.地震灾害产业关联损失评估[J].世界地震工程,2007,23(2):37-40.
[25]刘希林,赵源.地貌灾害间接经济损失评估:以泥石流灾害为例[J].地理科学进展,2008,27(3):7-12.
[26]王慧彦,黄敏,梁瑞莲,武守春.地震灾害损失经济统计学评估方法初步研究[J].自然灾害学报,2009,18(3):105-110.
[27]徐嵩龄.灾害经济损失概念及产业关联型间接经济损失计量[J].自然灾害学报,1998,7(4):7-15.
[28]都吉夔,张勤,宋立军,侯建盛,丁香,袁志祥,黄敏,卢永坤.四川汶川8.0级地震间接经济损失评估方法[J].灾害学,2008,23(4):130-133.
[29]陶正如,等.基于工程地震风险评估的地震保险费率厘定[J].自然灾害学报,2004,13(2):112-118.
[30]刘欢,等.基于GIs的中国地震灾害人口风险性分析[J].地理科学进展,2012,3l(3).
[31]中国地震局.中国地震年鉴[M].北京:中国地震出版社,1990-2007.
[32]中华人民共和国国家统计局.中国统计年鉴[M].北京:中国统计出版社,2012.
[33]郑通彦,等.2008年中国大陆地震灾害损失述评[J].灾害学,2010,25(002):112-118.
[34]郑通彦,等.2009年中国大陆地震灾害损失述评[J].灾害学,2010,25(004):96-101.
[35]郑通彦,等.2010年中国大陆地震灾害损失述评[J].自然灾害学报,2011,20(4):107-113.
[36]郑通彦,等.2011年中国大陆地震灾害损失述评[J].自然灾害学报,2012,21(005):88-97.
[37]袁荫靶概率论与数理统计[M].北京:中国人民大学出版社,1990.
①20世纪全球地震死亡人数为120万,其中中国占59万。
①陶正如和陶夏新(2004)提出了通过工程地震风险评估得出超概率曲线,进而实现地震保险费率厘定;刘欢等(2012)借助地理信息系统分析了中国地震灾害造成人员伤亡的风险,并得出了地震灾害人口灾损曲线。
②实际上,随着经济社会的发展,一个地区的财富积累会越来越多。在其他条件不变的情况下,同样破坏程度的地震造成的损失应该是越来越大的。再加上通货膨胀因素的影响,严格来说,在长时间跨度中,地震损失的分布会有一定变化。
③目前对地震的形成机理及不同地震事件之间的相互作用科学界仍然没有明确结论,现实中不同地震事件之间的确可能有一定的因果关系,并不一定是完全独立的。
①财富积累也对地震有放大效应。有文献(Banks,2005)使用GDP作为衡量财富积累的指标,但是财富积累是存量,而GDP是增量,因此将GDP作为衡量财富积累的指标并不合适。本文因此仅考虑通货膨胀的影响。
①在上千年的时间段上,汶川地震级别的地震损失事件足很有可能多次发生的,并不能被忽略,但是从本文所采用的22年247起地震损失数据来看,若根据Bernoulli大数定律而赋予汶川地震1/247的发生概率,则未免过高。由于汶川地震的直接经济损失远大于其他地震之和,任何对其发生概率的猜测,如千分之一或千分之二,在模拟中都会对总期望损失造成非常显著的影响。在无法确切确定汶川地震级别极端地震损失事件发生慨率情况下,本文在计算饥模拟中剔除了汶川地震。
[2]Banks,Erik.Catastrophic risk:analysis and management.Wiley,2005.
[3]Kozlowski,Ronald T.,and Stuart B.Mathewson.Measuring and managing catastrophe risk.National Emergency Training Center,1995.
[4]Ordaz,Mario,and Emilio Rosenblueth."Earthquake magnitude exceedance rate and self-similarity."Earthquake engineering&structural dynamics 18.7(1989):1017-1023.
[5]Burr,Irving W."Cumulative frequency functions."The Annals of Mathematical Statistics 13.2(1942):215-232.
[6]Van Dantzig,David."Economic decision problems for flood prevention."Econometrica:Journal of the Econometric Society(1956):276-287.
[7]Shaw,Daigee,et al."A probabilistic risk analysis for Taipei seismic hazards:an application of HAZ-Taiwan with its pre-processor and post-processor."Proceedings of Asia Oceania Geosciences Society Annual Meeting.2004.
[8]Dong,Weimin."Building a More Profitable Portfolio.Modern Portfolio Theory with Application to Catastrophe Insurance."Reactions Publication(2001).
[9]Cochrane,Harold C."Predicting the economic impact of earthquakes."Social Science Perspectives on the Coming San Francisco Earthquake,Natural Hazards Research Paper 25(1974).
[10]Cochrane,Harold C.,and C.Harold."Knowledge of private loss and the efficiency of protection."Conference on the Economics of Natural Hazards and their Mitigation.1984.
[11]Cole,Sam,Enrique Pantoja Lozano,and V.Razak."Social accounting for disaster preparedness and recovery planning."Technical report NCEER 93(1993).
[12]Munich,R.E.Topics geo:natural catastrophes 2010:analyses,assessments,positions.Munchener Ruck,2010.
[13]Okuyama,Yasuhide."Modeling spatial economic impacts of an earthquake:Input-output approaches."Disaster Prevention and Management 13.4(2004):297-306.
[14]Lin,Jeng Hsiang."Exceedance probability of extensive damage limit for general buildings in Taiwan."Disaster Prevention and Management 21.3(2012):386-397.
[15]Peskin,Henry M.Protecting Industrial Resources Against Nuclear Attack:Interim Report of an Economic Analysis.No.IDA HQ-65-3550.INSTITUTE FOR DEFENSE ANALYSES ARLINGTON VA ECONOMIC AND POLITICAL STUDIES DIV,1965.
[16]REMI Ine,The REMI EDFS-53 Forecasting&Simulation Model,Volume 1,Model Documentation,Chapter4.Amherst,MA:Regional Economic Modeling,1997.
[17]Rose,Adam,and Shu-Yi Liao."Modeling regional economic resilience to disasters:A computable general equilibrium analysis of water service disruptions*."Journal of Regional Science 45.1(2005):75-112.
[18]Rose,Adam,and Shu-Yi Liao."Modeling regional economic resilience to disasters:A computable general equilibrium analysis of water service disruptions."Journal of Regional Science 45.1(2005):75-112.
[19]Tirasirichai,Chakkaphan,and David Enke."Case study:Applying a regional CGE model for estimation of indirect economic losses due to damaged highway bridges."The Engineering Economist 52.4(2007):367-401.
[20]Wetzler,Elliot.The Structure of the IDA Civil Defense Economic Model.No.RP-P-674.INSTITUTE FOR DEFENSE ANALYSES ARLINGTON VA PROGRAM ANALYSIS DIV,1970.
[21]Jang,Jing-Jong,and Jeng-Ru Lee."ANALYSIS OF DESIGN WIND SPEED DISTRIBUTION OF TAIWAN AREA."Journal of Manne Science and Technology 5.1(1997).
[22]Benson,Manuel A.Characteristics of frequency curves based on a theoretical 1,000-year record.US Department of the Interior.Geological Survey,Water Resources Division.1952.
[23]李俊.以Google Earth为平台,基于GDP,人口与场地效应的全球大震损失评估模型[D].合肥:中国科学技术大学,2009.
[24]林均岐,钟江荣.地震灾害产业关联损失评估[J].世界地震工程,2007,23(2):37-40.
[25]刘希林,赵源.地貌灾害间接经济损失评估:以泥石流灾害为例[J].地理科学进展,2008,27(3):7-12.
[26]王慧彦,黄敏,梁瑞莲,武守春.地震灾害损失经济统计学评估方法初步研究[J].自然灾害学报,2009,18(3):105-110.
[27]徐嵩龄.灾害经济损失概念及产业关联型间接经济损失计量[J].自然灾害学报,1998,7(4):7-15.
[28]都吉夔,张勤,宋立军,侯建盛,丁香,袁志祥,黄敏,卢永坤.四川汶川8.0级地震间接经济损失评估方法[J].灾害学,2008,23(4):130-133.
[29]陶正如,等.基于工程地震风险评估的地震保险费率厘定[J].自然灾害学报,2004,13(2):112-118.
[30]刘欢,等.基于GIs的中国地震灾害人口风险性分析[J].地理科学进展,2012,3l(3).
[31]中国地震局.中国地震年鉴[M].北京:中国地震出版社,1990-2007.
[32]中华人民共和国国家统计局.中国统计年鉴[M].北京:中国统计出版社,2012.
[33]郑通彦,等.2008年中国大陆地震灾害损失述评[J].灾害学,2010,25(002):112-118.
[34]郑通彦,等.2009年中国大陆地震灾害损失述评[J].灾害学,2010,25(004):96-101.
[35]郑通彦,等.2010年中国大陆地震灾害损失述评[J].自然灾害学报,2011,20(4):107-113.
[36]郑通彦,等.2011年中国大陆地震灾害损失述评[J].自然灾害学报,2012,21(005):88-97.
[37]袁荫靶概率论与数理统计[M].北京:中国人民大学出版社,1990.
①20世纪全球地震死亡人数为120万,其中中国占59万。
①陶正如和陶夏新(2004)提出了通过工程地震风险评估得出超概率曲线,进而实现地震保险费率厘定;刘欢等(2012)借助地理信息系统分析了中国地震灾害造成人员伤亡的风险,并得出了地震灾害人口灾损曲线。
②实际上,随着经济社会的发展,一个地区的财富积累会越来越多。在其他条件不变的情况下,同样破坏程度的地震造成的损失应该是越来越大的。再加上通货膨胀因素的影响,严格来说,在长时间跨度中,地震损失的分布会有一定变化。
③目前对地震的形成机理及不同地震事件之间的相互作用科学界仍然没有明确结论,现实中不同地震事件之间的确可能有一定的因果关系,并不一定是完全独立的。
①财富积累也对地震有放大效应。有文献(Banks,2005)使用GDP作为衡量财富积累的指标,但是财富积累是存量,而GDP是增量,因此将GDP作为衡量财富积累的指标并不合适。本文因此仅考虑通货膨胀的影响。
①在上千年的时间段上,汶川地震级别的地震损失事件足很有可能多次发生的,并不能被忽略,但是从本文所采用的22年247起地震损失数据来看,若根据Bernoulli大数定律而赋予汶川地震1/247的发生概率,则未免过高。由于汶川地震的直接经济损失远大于其他地震之和,任何对其发生概率的猜测,如千分之一或千分之二,在模拟中都会对总期望损失造成非常显著的影响。在无法确切确定汶川地震级别极端地震损失事件发生慨率情况下,本文在计算饥模拟中剔除了汶川地震。
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