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Seismic hazard and risk assessment based on Unified Scaling Law for Earthquakes: thirteen principal urban agglomerations of India

机译:基于统一地震统一规定法的地震危害和风险评估:印度的十三个主要城市集群

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The deterministic seismic hazard map of India with spatially distributed peak ground acceleration was used to estimate seismic risk using two data sets of the Indian population-the model population data set and the data set based on India's Census 2011. Four series of the earthquake risk maps of the region based on these two population density sets were cross-compared. The discrepancy of the population data and seismic risks estimation were illuminated for the thirteen principal urban agglomerations of India. The confirmed fractal nature of earthquakes and their distribution in space implies that traditional probabilistic estimations of seismic hazard and risks of cities and urban agglomerations are usually underestimated. The evident patterns of distributed seismic activity follow the Unified Scaling Law for Earthquakes, USLE, which generalizes Gutenberg-Richter recurrence relation. The results of the systematic global analysis imply that the occurrence of earthquakes in a region is characterized with USLE: log(10) N (M, L) = A + B x (5 - M) + C x log(10) L, where N(M, L)-expected annual number of earthquakes of magnitude M within an area of liner size L, A determines seismic static rate, B-balance between magnitude ranges, and C-fractal dimension of seismic loci. We apply the seismic hazard and risk assessment methodology developed recently based on USLE, pattern recognition of earthquake-prone geomorphic nodes, and neo-deterministic scenarios of destructive ground shaking. Objects of risk are individuals (1) as reported in the 2011 National Census data and (2) as predicted for 2010 by Gridded Population of the World (model GPWv3); vulnerability depends nonlinearly on population density. The resulting maps of seismic hazard and different risk estimates based on population density are cross-compared. To avoid misleading interpretations, we emphasize that risk estimates presented here for academic purposes only. In the matter of fact, they confirm that estimations addressing more realistic and practical kinds of seismic risks should involve experts in distribution of objects of risk of different vulnerability, i.e., specialists in earthquake engineering, social sciences, and economics.
机译:印度的确定性地震危险地图具有空间分布峰接地加速度,用于使用印度人口的两个数据集 - 模型群体数据集和基于印度人口普查的数据集的地震风险估算地震风险。四次地震风险地图基于这两种人口密度集的区域是交叉的。印度的十三个主要城市集聚,估计人口数据和地震风险估计的差异。地震的确认分形性质及其在太空中分配意味着传统的地震危害和城市凝聚风险的概率估计通常低估。分布式地震活动的明显模式遵循统一地震的统一缩放法,USLE,概括了古腾堡 - 里希特复发关系。系统全局分析的结果意味着区域中地震发生的发生特征是:LOG(10)n(m,l)= a + b x(5-m)+ c x log(10)l,其中n(m,l)在衬里大小L区域内 - 在衬垫区域内的幅度m的幅度次数,a确定地震静态速率,幅度范围之间的b平衡,以及地震基因座的C型分形尺寸。我们应用了近期开发的地震危险和风险评估方法,基于USLE,模式识别的地震 - 易受地貌节点,以及破坏性地面震动的新确定情景。风险对象是个人(1),如2011年国家人口普查数据所报告的(2),按照世界网格人口预测到2010年(模型GPWV3);脆弱性取决于人口密度的非线性。基于人口密度的地震危害和不同风险估计的所得到的地图是交叉的。为避免误导性解释,我们强调的是,仅用于学术目的的风险估计。事实上,他们证实,解决更现实和实用的地震风险的估计应涉及分布不同漏洞风险的专家,即地震工程,社会科学和经济学中的专家。

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