印度东北部米佐拉姆邦地震危险性及风险评估

C. Lallawmawma, M.L. Sharma, J.D. Das
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引用次数: 3

摘要

本文在经典概率地震灾害分析和基于事件的概率地震风险分析的基础上,对米佐拉姆邦进行了地震灾害和风险评估。在地震危险性估计方面,分别考虑了面震源模型、断裂带多边形模型和平滑网格地震活动性模型。这些震源带和平滑网格地震活动性震源的地震活动率是通过均匀化和分散化的地震目录估计出来的。在震源模型和地震动预测方程(GMPEs)中应用逻辑树框架来解释认知不确定性。在参考岩石条件下(Vs30 = 760 m/s),分别用5个新生代衰减(NGA) GMPEs和3个印缅俯冲带GMPEs评价了地震危险性。在米佐拉姆邦的每八个区总部,估计在0.2秒和15秒的峰值地面加速度(PGA)和频谱加速度(SA)在50年内超过2%和10%的可能性。给出了危害曲线和均匀危害谱(UHS)。对于地震风险分析,建筑暴露数据基于数字化建筑足迹和2011年印度住房普查数据。将所有建筑物分为三类,并对每一类建筑物分配地震易损性函数。每个建筑类别的面积是根据数字化足迹分配的。每平方米的建筑重置成本是根据专家的意见和从过去的研究中确定的价值来选择的。最后,本研究利用Open Quake-engine基于概率事件的方法进行了地震风险分析,以估计地区一级的风险指标,如平均年损失和损失超出的概率曲线。这项研究的发现为米佐拉姆邦的高风险地区、最容易受到地震活动影响的建筑类型以及预期的经济损失提供了有价值的见解。这些结果可作为地方政府当局制定未来城市规划和实施减轻地震风险战略的指南。
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Probabilistic seismic hazard and risk assessment of Mizoram, North East India

This paper presents seismic hazard and risk assessment for the state of Mizoram based on a classical probabilistic seismic hazard analysis and event-based probabilistic seismic risk analysis. For the seismic hazard estimation, analysis has been performed considering the areal source model, fault zone polygon, and smoothed gridded seismicity model. The earthquake activity rates for these source zones and smoothed gridded seismicity sources are estimated from the homogenized and declustered earthquake catalogue. The logic tree framework is applied in the seismic source models and Ground Motion Prediction equations (GMPEs) to account for the epistemic uncertainties. Five Next-generation attenuation (NGA) GMPEs for the active shallow region and three GMPEs for the Indo-Burma subduction zone have been used to evaluate the hazard at the reference rock condition (Vs30 ​= ​760 ​m/s). Peak Ground Acceleration (PGA) and Spectral Acceleration (SA) at 0.2 s and 1s are estimated for each eight districts headquarters of Mizoram for a 2% and 10% probability of exceedance in 50 years. The hazard curves and Uniform Hazard Spectra (UHS) are also presented. For seismic risk analysis, building exposure data are based on digitized building footprint and 2011 Housing Census data of India. All the buildings are classified into three classes, and seismic vulnerability functions are assigned to each building class. The area per building class is assigned from the digitized footprint. Building replacement costs per square meter have been chosen based on expert input and values identified from past study. Lastly, the study conducted a seismic risk analysis using the Open Quake-engine's probabilistic event-based methodology to estimate risk metrics at the district level, such as average annual losses and probability curves for loss exceedance. The study's findings provide valuable insights into the most high-risk areas, the building construction types that are most vulnerable to seismic activity, and the anticipated economic losses in the state of Mizoram. These results can serve as a guide for local government authorities in developing future city plans and implementing earthquake risk mitigation strategies.

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