Disaster preparedness is critical for reducing potential impact. This paper contributes to current knowledge of disaster preparedness using representative national sample data from China, which faces high earthquake risks in many areas of the country. The adoption of earthquake preparedness activities by the general public, including five indicators of material preparedness and five indicators of awareness preparedness, were surveyed and 3245 respondents from all 31 provinces of Mainland China participated in the survey. Linear regression models and logit regression models were used to analyze the effects of potential influencing factors. Overall, the preparedness levels are not satisfied, with a material preparation score of 3.02 (1-5), and awareness preparation score of 2.79 (1-5), nationally. Meanwhile, residents from western China, which has higher earthquake risk, have higher degrees of preparedness. The concern for disaster risk reduction (DRR) and the concern for building safety and participation in public affairs are consistent positive predictors of both material and awareness preparedness. The demographic and socioeconomic variables' effects, such as gender, age, education, income, urban/rural division, and building size, vary according to different preparedness activities. Finally, the paper concludes with a discussion of the theoretical contribution and potential implementation.
Earthquakes are among the most devastating natural disasters in China, causing serious casualties and property losses. To effectively reduce catastrophic risk, it is important to establish an earthquake catastrophe insurance system based on the earthquake catastrophe model, of which seismic hazard analysis is a main module. Probabilistic seismic-hazard analysis uses the potential source model, seismicity model, and ground-motion attenuation model, as well as the probability method to obtain the seismic hazard value of a given point. However, because the influence of a single seismic event is required when the earthquake catastrophe model is used for risk analysis, a series of single events needs to be generated according to the potential source model so as to calculate the influence of each event on the given point. In this study, based on the seismicity model (potential sources and their seismicity parameters) used in compiling the fifth generation of Seismic Ground Motion Parameter Zoning Map of China, we use the Monte Carlo method to simulate seismic events conforming to temporal, spatial, and intensity distribution of China’s seismic activities. In the simulation process, we follow the Poisson distribution in occurrence time and the Gutenberg–Richter law in magnitude distribution, and we use potential sources and earthquake occurrence rates to describe spatial distribution. The simulated seismic events include the following parameters: date (year, month, and day), location (longitude and latitude), depth, magnitude, and attitude of seismogenic faults. The simulated seismic event set can support earthquake risk analysis in the earthquake catastrophe model and has been applied in the earthquake catastrophe model of China.
The temporal distribution of earthquakes provides important basis for earthquake prediction and seismic hazard analysis. The relatively limited records of strong earthquakes have often made it di cult to study the temporal distribution models of regional strong earthquakes. However, there are hundreds of years of complete strong earthquake records in North China Seismic Zone, providing abundant basic data for studying temporal distribution models. Using the data of M ≥ 6.5 earthquakes in North China as inputs, this paper estimates the model parameters using the maximum likelihood method with exponential, Gamma, Weibull, Lognormal and Brownian passage time (BPT) distributions as target models. The optimal model for describing the temporal distribution of earthquakes is determined according to Akaike information criterion (AIC), determination coe cient R 2 and Kolmogorov-Smirnov test (K-S test). The results show that Lognormal and BPT models perform better in describing the temporal distribution of strong earthquakes in North China. The mean recurrence periods of strong earthquakes (M ≥ 6.5) calculated based on these two models are 8.1 years and 13.2 years, respectively. In addition, we used the likelihood pro le method to estimate the uncertainty of model parameters. For the BPT model, the mean and 95% con dence interval of recurrence interval µ is 13.2 (8.9-19.1) years, and the mean and 95% con dence interval of α is 1.29 (1.0-1.78). For the Lognormal model, the mean value and 95% con dence interval of v is 2.09 (1.68-2.49), the mean value exp (v) corresponding to earthquake recurrence interval is 8.1 (5.4-12.1) years. In this study, we also calculated the occurrence probability of M ≥ 6.5 earthquakes in North China Seismic Zone in the future, and found that the probability and 95% con dence interval in the next 10 years based on the BPT model is 35.3% (26.8%-44.9%); the mean value and 95% con dence interval of earthquake occurrence probability based on the Lognormal distribution is 35.4% (22.9%-49.7%); the mean probability and 95% con dence interval based on the Poisson model is 53.1% (41.1%-64%). The results of this study may provide important reference for temporal distribution model selection and earthquake recurrence period calculation in future seismic hazard analysis in North China.
Arias intensity (IA), as an important seismic parameter, which contains the information of amplitude, frequencies, and duration of ground motion, plays a crucial role in characterizing seismic hazard such as earthquake-induced landslides. In this article, we conducted probabilistic seismic hazard analysis (PSHA) based on IA in China’s north–south seismic belt. We adopted the seismic sources and seismicity parameters used in the fifth generation of the Seismic Ground Motion Parameter Zoning Map of China, and two ground-motion model of IA. The results show that the values of IA are greater than 0.11 m/s in most regions of the north–south seismic belt. The provincial capital cities and most prefecture-level cities in the seismic zone are located in the region with IA-values greater than 0.32 m/s. The values of IA are above 0.54 m/s in the region around the main fault zone. This means that the north–south seismic belt is prone to extremely high-seismic hazard, particularly earthquake-induced landslides. Therefore, it is important to strengthen the evaluation and prevention of earthquake-induced landslides in this area. As we have found significant differences in the values of IA calculated from different ground-motion model, it is necessary to study the ground-motion model of IA for the western geological environment of China. In addition, the PSHA based on IA gives more consideration to the influence of large earthquakes than that based on peak ground acceleration. Therefore, IA plays an important role in seismic design of major engineering projects. The results of this article are of great scientific significance for understanding the seismic hazard of the north–south seismic belt.
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