To estimate human loss in an earthquake-prone area, it is necessary to analyze the role played by the spatiotemporal distribution of the area’s resident population. In order to evaluate earthquake impact, this articl...To estimate human loss in an earthquake-prone area, it is necessary to analyze the role played by the spatiotemporal distribution of the area’s resident population. In order to evaluate earthquake impact, this article focuses on the spatiotemporal distribution of population and five scenario earthquakes that form the basis for loss estimation in the city of Sylhet, Bangladesh. Four temporal contexts(weekday, weekly holiday, the 30 days of Ramadan, and strike days) expand the more typical daytime and nighttime settings in which to examine hazard risk. The population distribution for every 2 hour interval in a day is developed for each type of day. A relationship between the occupancy classes and average space(persons per 100 m^2)is used to distribute people in each building regardless of building locations. A total daytime and nighttime population is obtained for each building and the estimated nighttime population is used to model the population for four temporal scenarios in a year based on different factors and weights. The resulting data are employed to estimate population loss for each of the temporal and earthquake scenarios. This study used building-specific human vulnerability curves developed by the Central American Probabilistic Risk Assessment(CAPRA) to obtain possible loss of life estimates. The results reveal that there is a high positive correlation between the spatiotemporal distribution of population and the potential number of casualties.展开更多
In this study, loss estimation models were developed for reasonably accurate assessment of economic and human losses from seismic events in the Mediterranean region, based on damage assessment at an urban scale.Data w...In this study, loss estimation models were developed for reasonably accurate assessment of economic and human losses from seismic events in the Mediterranean region, based on damage assessment at an urban scale.Data were compiled from existing worldwide databases,and completed with earthquake information from regional studies. Economic data were converted to a single common currency unit(2015 USD value) and the wealth of the areas affected by 65 earthquakes of the region from 1900 to 2015 was assessed. Reduced-form models were used to determine economic and human losses, with earthquake magnitude and intensity as hazard-related variables, and gross domestic product of the affected area and the affected population as exposure-related variables. Damage to buildings was also used as a hazard-related variable to predict economic and human losses. Finally, site-specific regression models were proposed for economic and human losses due to earthquakes in the Mediterranean region, and more specifically, in Algeria. We show that by introducing the damage variable into the models, prediction error can be reduced, and that accuracy of loss model estimation is site dependent and requires regional data on earthquake losses to improve. A case study for Constantine, Algeria shows the improvements needed for increased accuracy.展开更多
文摘To estimate human loss in an earthquake-prone area, it is necessary to analyze the role played by the spatiotemporal distribution of the area’s resident population. In order to evaluate earthquake impact, this article focuses on the spatiotemporal distribution of population and five scenario earthquakes that form the basis for loss estimation in the city of Sylhet, Bangladesh. Four temporal contexts(weekday, weekly holiday, the 30 days of Ramadan, and strike days) expand the more typical daytime and nighttime settings in which to examine hazard risk. The population distribution for every 2 hour interval in a day is developed for each type of day. A relationship between the occupancy classes and average space(persons per 100 m^2)is used to distribute people in each building regardless of building locations. A total daytime and nighttime population is obtained for each building and the estimated nighttime population is used to model the population for four temporal scenarios in a year based on different factors and weights. The resulting data are employed to estimate population loss for each of the temporal and earthquake scenarios. This study used building-specific human vulnerability curves developed by the Central American Probabilistic Risk Assessment(CAPRA) to obtain possible loss of life estimates. The results reveal that there is a high positive correlation between the spatiotemporal distribution of population and the potential number of casualties.
基金The MAIF Foundationsponsored by the Urban Seismology project at the Institute of Earth Science ISTerre of the University of Grenoble-Alpes Observatoire des Sciences de Univers de Grenoble (The Grenoble Observatory for Sciences of the Universe-Labex OSUG@2020) (Investissements d’avenir, ANR10LABX56)
文摘In this study, loss estimation models were developed for reasonably accurate assessment of economic and human losses from seismic events in the Mediterranean region, based on damage assessment at an urban scale.Data were compiled from existing worldwide databases,and completed with earthquake information from regional studies. Economic data were converted to a single common currency unit(2015 USD value) and the wealth of the areas affected by 65 earthquakes of the region from 1900 to 2015 was assessed. Reduced-form models were used to determine economic and human losses, with earthquake magnitude and intensity as hazard-related variables, and gross domestic product of the affected area and the affected population as exposure-related variables. Damage to buildings was also used as a hazard-related variable to predict economic and human losses. Finally, site-specific regression models were proposed for economic and human losses due to earthquakes in the Mediterranean region, and more specifically, in Algeria. We show that by introducing the damage variable into the models, prediction error can be reduced, and that accuracy of loss model estimation is site dependent and requires regional data on earthquake losses to improve. A case study for Constantine, Algeria shows the improvements needed for increased accuracy.
文摘极值理论关注风险损失分布的尾部特征,通常用来分析概率罕见的事件,它可以依靠少量样本数据,在总体分布未知的情况下,得到总体分布中极值的变化情况,具有超越样本数据的估计能力。因此,基于GPD(generalized pareto distribution)分布的POT(peak over threshold)模型可更有效地利用有限的巨灾损失数据信息,从而成为极值理论当前的主流技术(以下简称,POT-GPD模型)。针对地震巨灾发生频率低、损失高、数据不足且具有厚尾性等特点,利用POT-GPD模型对我国1969年至2013年间的地震直接经济损失数据进行了统计建模;采用样本Hill图及区间筛选算法选取阈值,并对形状参数及尺度参数进行了估计。模型检验表明,POT-GPD模型对巨灾风险厚尾特点具有较好的拟合效果和拟合精度,为地震巨灾风险估计的建模及巨灾债券的定价提供了理论依据。
