Seismic Hazard and Risk Assessments for Beijing–Tianjin–Tangshan, China, Area
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- Xie, F., Wang, Z. & Liu, J. Pure Appl. Geophys. (2011) 168: 731. doi:10.1007/s00024-010-0115-z
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Seismic hazard and risk in the Beijing–Tianjin–Tangshan, China, area were estimated from 500-year intensity observations. First, we digitized the intensity observations (maps) using ArcGIS with a cell size of 0.1 × 0.1°. Second, we performed a statistical analysis on the digitized intensity data, determined an average b value (0.39), and derived the intensity–frequency relationship (hazard curve) for each cell. Finally, based on a Poisson model for earthquake occurrence, we calculated seismic risk in terms of a probability of I ≥ 7, 8, or 9 in 50 years. We also calculated the corresponding 10 percent probability of exceedance of these intensities in 50 years. The advantages of assessing seismic hazard and risk from intensity records are that (1) fewer assumptions (i.e., earthquake source and ground motion attenuation) are made, and (2) site-effect is included. Our study shows that the area has high seismic hazard and risk. Our study also suggests that current design peak ground acceleration or intensity for the area may not be adequate.
KeywordsSeismic hazardseismic riskseismic hazard analysishazard curve
In this paper, we estimated seismic hazard and risk for the Beijing–Tianjin–Tangshan area from historical intensity observations. First, we digitized the historical intensity records for 0.1° × 0.1° grid cells. Then, we performed analyses on the digitized intensity records and determined the intensity–frequency relationship (hazard curve) for each cell. Finally, we calculated seismic risk for each cell and the area.
2 Intensity Data
3 Hazard Analysis
Return period of different intensity for Beijing, Tianjin, and Tangshan
Number of observations
Return period (years)
I = 7
I = 8
I = 9
4 Risk Estimate
Seismic risk for major cities in the study area
50 year probability of I ≥ 7/%
50 year probability of I ≥ 8/%
50 year probability of I ≥ 9/%
Relationship between intensity and peak ground acceleration (PRCNS, 2001)
Peak ground acceleration (g)
Many methodologies have been used to estimate seismic hazard and its associated uncertainties in time and space, and the estimates have been applied to seismic risk assessment. Among these methodologies, probabilistic seismic hazard analysis (PSHA) and deterministic seismic hazard analysis (DSHA) are the most commonly used worldwide (Cornell, 1968; Reiter, 1990; Krinitzsky, 2002; McGuire, 2004). Although many advantages have been acclaimed, PSHA is not based on valid physics and mathematics (Wang and Zhou, 2007; Wang, 2009b). Thus, the resulting hazard estimate from PSHA does not have a clear physical and statistical meaning and has caused so many problems (Wang, 2005, 2006, 2007, 2009b). For example, PSHA could result in consideration of a PGA of 10 g for engineering design of nuclear repository facilities at Yucca Mountain in Nevada (Steppet al., 2001). Even though DSHA has been labeled as an unreliable approach, it has actually been more widely used for seismic hazard assessment because it has clear physical and statistical bases. For example, Dinget al., (2004), Panet al., (2006), and Wang and Zhou (2007) estimated ground motion hazards from simulations of the 1697 Sanhe-Pinggu and 1976 Tangshan earthquakes. The biggest drawback of DSHA is that the temporal characteristics (i.e., the recurrence interval or frequency of ground motion) are often time neglected. This is one of the areas that must be addressed in DSHA because the frequency is also an important aspect of risk assessment and policy consideration (Wang, 2006, 2007, 2009a).
In this paper, we used about 500 years of intensity observations (records) to estimate seismic hazard and risk for the Beijing–Tianjin–Tangshan area. The advantages of using historical intensity observations are:
they are as free as possible of modeling assumptions; and
inclusion of site-effect.
There are also some limitations of this method, however. One of the limitations is that the period (i.e., 500 years) may not be enough to reflect the recurrence intervals of large earthquakes in the area. Wang (1984) and Liuet al., (1997) estimated that the recurrence interval of the Tangshan earthquake (M = 7.8) is about 1,500–7,500 years. Xianget al., (1988), Qiuet al., (1997) found that the recurrence interval of the Sanhe-Pinggu earthquake (M = 8.0) is about 7,000 years. This limitation may be compensated by the fact that the observed intensities were from all earthquake sources, not from single one. Another limitation is that a large individual intensity, such as those of the Sanhe-Pinggu and Tangshan earthquakes, affect the results. This can be seen clearly in Figs. 5 and 6 in which the higher intensities are concentrated in the Sanhe-Pinggu and Tangshan areas. This limitation may be corrected by using an average b value. As shown in Fig. 2, the b value (0.22) for the Tangshan cell is much lower than the average b value (0.39). This lower b value (0.22) for the Tangshan cell is caused by the high observed intensity (IX) of the 1976 Tangshan earthquake.
Seismic hazard and risk in the Beijing–Tianjin–Tangshan area were estimated from historical intensity observations since 1500. The advantages of using the intensity observations are:
fewer assumptions are made;
site-effect is included; and
intensity is directly related to damage.
If the past seismicity continues into the future, our study shows that the Beijing–Tianjin–Tangshan area has high seismic hazard and risk. Intensity 7 or greater could be expected in the Beijing–Tianjin–Tangshan area in the next 100 years. The probability of experiencing intensity 8 or greater in the area is larger than 10 percent. Our study illustrates that there are large uncertainties involved in seismic hazard and risk assessments. Hence, a specific confidence level should be considered for seismic design code formulation and seismic design of critical facilities. Our study also suggests that current design peak ground acceleration (PRCNS, 2001) for the area may not be adequate.
We thank Yanju Peng and Jinshi Hao for their help in ArcGIS digitization, and Yan Zhao, Xiaoliang Zhang, and Jiyang Ye for their assistance in data analyses. We thank Meg Smath of the Kentucky Geological Survey for editorial help. We also thank two anonymous reviewers for their valuable comments and suggestions that improved this manuscript greatly.