Cite this article: Zhao D, Wang Z, Wang J, et al. A Rapid Estimation Method for Post-earthquake Building Losses. International Journal of Disaster Risk Science, 14, 428–439 (2023). https://doi.org/10.1007/s13753-023-00491-0
A Rapid Estimation Method for Post-Earthquake Building Losses
Dengke Zhao, Zifa Wang*, Jianming Wang, Dongliang Wei, Yang Zhou, Zhaoyan Li
Corresponding author: Zifa Wang
Dengke Zhao, Institute of Engineering Mechanics, China Earthquake Administration, Key Laboratory of Earthquake Engineering and Engineering Vibration, No. 29 Xuefu Road, Harbin, Heilongjiang, People’s Republic of China, 150080, denco666@163.com
Zifa Wang, Institute of Engineering Mechanics, China Earthquake Administration, Key Laboratory of Earthquake Engineering and Engineering Vibration, No. 29 Xuefu Road, Harbin, Heilongjiang, People’s Republic of China, 150080; CEAKJ ADPRHexa Inc., Shaoguan, Guangdong 512000, China, zifa@iem.ac.cn
Jianming Wang, CEAKJ ADPRHexa Inc., Shaoguan, Guangdong 512000, China, jwang780@gmail.com
Dongliang Wei, CEAKJ ADPRHexa Inc., Shaoguan, Guangdong 512000, China, wei_dl1921@163.com
Yang Zhou, CEAKJ ADPRHexa Inc., Shaoguan, Guangdong 512000, China, 649581267@qq.com
Zhaoyan Li, Institute of Engineering Mechanics, China Earthquake Administration, Key Laboratory of Earthquake Engineering and Engineering Vibration, No. 29 Xuefu Road, Harbin, Heilongjiang, People’s Republic of China, 150080, hkjlizhaoyan@163.com
Abstract:
Rapid estimation of post-earthquake building damage and loss is very important in urgent response efforts. The current approach leaves much room for improvement in estimating ground motion and correctly incorporating the uncertainty and spatial correlation of the loss. This study proposed a new approach for rapidly estimating post-earthquake building loss with reasonable accuracy. The proposed method interpolates ground motion based on the observed ground motion using the Ground Motion Prediction Equation (GMPE) as the weight. It samples the building seismic loss quantile considering the spatial loss correlation that is expressed by Gaussian copula, and kriging is applied to reduce the dimension of direct sampling for estimation speed. The proposed approach was validated using three historical earthquake events in Japan with actual loss reports, and was then applied to predict the building loss amount for the March 2022 Fukushima Mw7.3 earthquake. The proposed method has high potential in future emergency efforts such as search, rescue, and evacuation planning.
Keywords: Earthquake building loss estimation; Fukushima earthquake 2022; Gaussian copula sampling; Japan; Spatial correlation of earthquake losses; Spatial interpolation of ground motion
Fig.1 A variable resolution grid for Japan. The grid size for level 1, 2, 3,
and 4 is 5 × 5 km, 1 × 1 km, 0.5 × 0.5 km, and 0.25 × 0.25 km, respectively.
Fig.2 Random loss number sampling based on Gaussian copula
Fig.3 A framework for post-earthquake building loss estimation based on observed
ground motion considering various types of uncertainty and spatial loss correlation
Fig.4 Building inventory distribution for the Zenkyoren insurance dataset.
RC = reinforced concrete.
Fig.5 Schematic vulnerability for a typical type of building with varying uncertainty distribution.
PDF = Probability density function; PGA = Peak ground acceleration.
Fig.6 Building loss estimate for the February 2021 earthquake event in Japan
Fig.7 Building loss estimate for the May 2021 earthquake event in Japan
Fig.8 Interpolated peak ground acceleration (PGA) within the earthquake impact
area for the March 2022 Fukushima earthquake event in Japan
Fig.9 Building loss estimate distribution for the March 2022 Fukushima
earthquake event in Japan
Fig.10 Comparison of peak ground acceleration (PGA) by Ground Motion Prediction
Equations (GMPE), observed and spatially interpolated for the March 2022
Fukushima earthquake event in Japan. (a) Site class II; (b) Site class III.
Fig.11 The distribution of matching number of stations for the
March 2022 Fukushima earthquake event in Japan
Fig.12 Station weight distribution when there are two matching stations for
the March 2022 Fukushima earthquake event in Japan
Fig.13 Estimate mean and coefficient of variation (CV) at prefecture level for
the March 2022 Fukushima earthquake event in Japan
Supported by：
This work was supported by the Scientific Research Fund of Institute of Engineering Mechanics, China Earthquake Administration (Grant No. 2021B09) and National Natural Science Foundation of China (51978634).