Su-Chin Chang

New Evidence and Perspective to the Poisson Process and Earthquake Temporal Distribution from 55,000 Events around Taiwan since 1900

AbstractEarthquake prediction is by all means controversial and challenging, given the fact that some recent catastrophic earthquakes went unpredicted. Not surprisingly, statistical approaches have been utilized to model earthquake randomness in time or space. One of the suggestions is that the earthquake’s temporal probability distribution should follow the Poisson model, which is suitable for rare events by definition. As a result, the customarily used hypothesis should be largely associated with the prior judgment that earthquakes are rare, but not as a result of abundant quantitative evidence or theoretical derivation. Therefore, this study aims to offer new empirical evidence to the hypothesis based on 110-year-long earthquake data around Taiwan. From the series of statistical tests, the first statistical inference is indeed in line with the model’s proposition: the level of fitting between observation and theory is better for earthquakes with a lower mean rate. To be more specific, it shows that the...

Assessment of seismic hazard associated with the Meishan fault in Central Taiwan

According to the Central Geological Survey Taiwan (CGST), the Meishan fault in Central Taiwan, which induced a catastrophic earthquake in 1906, is considered capable of triggering equivalent events with a return period of 162xa0years. Therefore, as the next event is expected around 2070, the Meishan fault poses a high level of earthquake risk in Central Taiwan, especially for those cities and townships very close to the fault. However, the best-estimate return period (162xa0years) and earthquake magnitude (7.1 ML) reported by the CGST must be subject to some uncertainty, because such an event is very unlikely to recur every 162xa0years. Therefore, this study carried out a series of seismic hazard assessments for three major cities close to the Meishan fault, with the uncertainty of the best-estimate information being determined using the Rosenblueth algorithm. The results show that for Chaiyi city, which the Meishan fault passes through, the probability of the current design value (i.e., PGAxa0=xa00.33xa0g) being exceeded by the earthquake motion induced by the Meishan fault in the next 50xa0years would be as high as 55xa0%. Therefore, further studies should be carried out to obtain a better understanding of the Meishan fault, to develop a robust hazard mitigation plan for nearby cities.

PGA distributions and seismic hazard evaluations in three cities in Taiwan

This study first presents the series of peak ground acceleration (PGA) in the three major cities in Taiwan. The PGAs are back-calculated from an earthquake catalog with the use of ground motion models. The maximums of the 84th percentile (meanxa0+xa0one standard deviation) PGA since 1900 are 1.03, 0.36, and 0.10xa0g, in Taipei, Taichung, and Kaohsiung, respectively. Statistical goodness-of-fit testing shows that the series of PGA follow a double-lognormal distribution. Using the verified probability distribution, a probabilistic analysis was developed in this paper, and used to evaluate probability-based seismic hazard. Accordingly, given a PGA equal to 0.5xa0g, the annual exceedance probabilities are 0.56, 0.46, and 0.23xa0% in Taipei, Taichung, and Kaohsiung, respectively; for PGA equal to 1.0xa0g, the probabilities become 0.18, 0.14, and 0.09xa0%. As a result, this analysis indicates the city in South Taiwan is associated with relatively lower seismic hazard, compared with those in Central and North Taiwan.

On-site earthquake early warning with multiple regression analysis: Featuring two user-friendly applications for Excel

A variety of user-friendly spreadsheet templates have been developed for geoscience studies. However, the use of the built-in matrix functions within spreadsheet programs, such as Excel, is not particularly straightforward, lowering the value of spreadsheet programs for matrix-based computations, such as multiple regression analyses. Therefore, this study first developed two applications for Excel to perform multiple regression analyses in a much more user-friendly manner. Then using earthquake time histories from a reputable database, a series of regression analyses were performed. A new framework for on-site earthquake early warning based on multiple regression analyses is presented as an alternative to conventional models which were developed with single regression analyses.

Best-Estimate Return Period of the Sanchiao Earthquake in Taipei: Bayesian Approach

AbstractIt is believed that the Sanchiao fault in Taipei, the most important city in Taiwan, has caused several major earthquakes. In the literature, one study suggested return periods of the Sanchiao earthquake of 543, 568, and 746xa0years, with another concluding that the active fault should have induced three major earthquakes in a period of 2,600xa0years in the Holocene. Therefore, like many Bayesian applications, this study aims to develop a novel Bayesian algorithm for integrating the different sources of data to develop a new Bayesian estimate for the target problem. From the analysis, a Bayesian inference suggests a return period of the Sanchiao earthquake in Taipei of 634xa0years, which, for example, leads to a best-estimate probability of 7.6% for the recurrence of the Sanchiao earthquake in the next 50xa0years in the most important city in Taiwan.

A new procedure to best-fit earthquake magnitude probability distributions: including an example for Taiwan

Since the year 1973, more than 54,000 Mwxa0≥xa03.0 earthquakes have occurred around Taiwan, and their magnitude–frequency relationship was found following with the Gutenberg–Richter recurrence law with b value equal to 0.923 from the least-square calculation. However, using this b value with the McGuire–Arabasz algorithm results in some disagreement between observations and expectations in magnitude probability. This study introduces a simple approach to optimize the b value for better modeling of the magnitude probability, and its effectiveness is demonstrated in this paper. The result shows that the optimal b value can better model the observed magnitude distribution, compared with two customary methods. For example, given magnitude thresholdxa0=xa05.0 and maximum magnitudexa0=xa08.0, the optimal b value of 0.835 is better than 0.923 from the least-square calculation and 0.913 from maximum likelihood estimation for simulating the earthquake’s magnitude probability distribution around Taiwan.

Deterministic seismic hazard analysis considering non-controlling seismic sources and time factors

Deterministic seismic hazard analysis (DSHA) is an approach for evaluating site-specific seismic hazard that is influenced by the maximum hazard from the controlling sources affecting the specific study site. In its conventional form, DSHA does not consider sources other than the largest controlling source and it does not account for the time factors owing to the uncertainty of earthquakes occurrences in time. Under certain condition, ignoring these factors can lower the conservatism of the hazard estimate, especially when other non-controlling sources generate hazards nearly equivalent to that of the controlling source or when the structures design life is longer than the controlling source earthquakes return period. This study discusses several limitations of conventional DSHA and provides a modified approach for DSHA which we believe should supplement the conventional method. An example is presented to demonstrate how conventional DSHA can be un-conservative for certain problem types.