Lessons and Questions from Thirty Years of Testing the Precursory Swarm Hypothesis

In 1976 Frank Evison identified the first examples of earthquake swarms as long-term precursors of main-shock events, and thereby discovered the predictive scaling relations of long-term seismogenesis. From this time on, forecasting became the main focus of his research. After learning from an early attempt to communicate forecasts confidentially to government, he recognised the importance of hypothesis testing, and the precursory swarm hypothesis was cast in a form similar to a regional likelihood model. Tests of its performance relative to a stationary Poisson model at M ≥ 5.8 in New Zealand were begun in 1977. The initial hypothesis was that of a 1–1 relation between swarms and main-shock events. Following a study of the Japan catalogue, the generalised swarm hypothesis, in which multiple swarms were precursory to multiple main-shock events, was formulated. Tests of this form of the hypothesis at M ≥ 6.8 were initiated in a region of surveillance east of Japan in 1983. Eventually the generalised hypothesis was adopted in New Zealand also. In 1999, tests were begun in a region of Greece. In 1994–1995, several main-shock events favourable to the swarm hypothesis occurred, however four main-shock events near Arthur’s Pass, New Zealand, occurred without precursory swarms. Subsequent analysis showed that events called “quarms”, which were similar to swarms but more protracted in time, had preceded these events. This led to the proposal of a qualitative physical process to account for swarms, quarms and the predictive relations: A three-stage faulting process, in which a major crack induces aftercracks in its neighbourhood, just as a main shock induces aftershocks. An inference from this process was that the most general long-term precursor should be an increase of seismicity at similar magnitudes to the eventual aftershocks. It turned out that such a precursory scale increase nearly always occurs before major earthquakes and conforms to the predictive scaling relations. Setting aside the problem of identifying the scale increase before the major earthquake, the EEPAS (Every Earthquake a Precursor According to Scale) forecasting model was formulated. The success of this relatively weak model in forecasting major events in New Zealand, California, Japan and Greece shows that the predictive scaling relations are ubiquitous in earthquake catalogues. Although none of the formal tests of the swarm hypothesis were successful in their own terms, they were beneficial in identifying shortcomings in its formulation, thereby leading to improved understanding of long-term seismogenesis and a better forecasting model. Some puzzling aspects of the scaling relations are whether they vary regionally, and why the precursor area and aftershock area scale differently with magnitude. A more practical question is whether the EEPAS model can be strengthened, by making use of the clustering of some precursors in swarms and quarms, to bring us nearer to the original goal of forecasting individual major earthquakes.     

Probabilistic Assessment of Tsunami Recurrence in the Indian Ocean

The Indian Ocean is one of the most tsunamigenic regions of the world and recently experienced a mega-tsunami in the Sumatra region on 26 December 2004 (M _W 9.2 earthquake) with tsunami intensity I (Soloviev-Imamura intensity scale) equal to 4.5, causing heavy destruction of lives and property in the Indian Ocean rim countries. In this study, probabilities of occurrences of large tsunamis with tsunami intensities I ≥ 2.0 and I ≥ 3.0 (average wave heights H ≥ 2.83 m and H ≥ 5.66 m, respectively) during a specified time interval were calculated using three stochastic models, namely, Weibull, gamma and lognormal. Tsunami recurrence was calculated for the whole Indian Ocean and the special case of the Andaman-Sumatra-Java (ASJ) region, excluding the 1945 Makran event from the main data set. For this purpose, a reliable, homogeneous and complete tsunami catalogue with I ≥ 2.0 during the period 1797–2006 was used. The tsunami hazard parameters were estimated using the method of maximum likelihood. The logarithm of likelihood function (ln L) was estimated and used to test the suitability of models in the examined region. The Weibull model was observed to be the most suitable model to estimate tsunami recurrence in the region. The sample mean intervals of occurrences of tsunamis with intensity I ≥ 2.0 and I ≥ 3.0 were calculated for the observed data as well as for the Weibull, gamma and lognormal models. The estimated cumulative and conditional probabilities in the whole Indian Ocean region show recurrence periods of about 27–30 years (2033–2036) and 35–36 years (2039–2040) for tsunami intensities I ≥ 2.0 and I ≥ 3.0, respectively, while it is about 31–35 years (2037–2041) and 41–42 years (2045–2046) for a tsunami of intensity I ≥ 2.0 and I ≥ 3.0, respectively, in the ASJ region. A high probability (>0.9) of occurrence of large tsunamis with I ≥ 2.0 in the next 30–40 years in the Indian Ocean region was revealed.     

Probabilistic Assessment of Earthquake Hazard in Gujarat and Adjoining Region of India

The Gujarat and adjoining region falls under all four seismic zones V, IV, III and II of the seismic zoning map of India, and is one of the most seismically prone intracontinental regions of the world. It has experienced two large earthquakes of magnitude M _w 7.8 and 7.7 in 1819 and 2001, respectively and several moderate earthquakes during the past two centuries. In the present study, the probability of occurrence of earthquakes of M ≥ 5.0 has been estimated during a specified time interval for different elapsed times on the basis of observed time intervals between earthquakes using three stochastic models namely, Weibull, Gamma and Lognormal. A complete earthquake catalogue has been used covering the time interval of 1819 to 2006. The whole region has been divided into three major seismic regions (Saurashtra, Mainland Gujarat and Kachchh) on the basis of seismotectonics and geomorphology of the region. The earthquake hazard parameters have been estimated using the method of maximum likelihood. The logarithmic of likelihood function (ln L) is estimated and used to test the suitability of models in three different regions. It was found that the Weibull model fits well with the actual data in Saurashtra and Kachchh regions, whereas Lognormal model fits well in Mainland Gujarat. The mean intervals of occurrence of earthquakes are estimated as 40.455, 20.249 and 13.338 years in the Saurashtra, Mainland Gujarat and Kachchh region, respectively. The estimated cumulative probability (probability that the next earthquake will occur at a time later than some specific time from the last earthquake) for the earthquakes of M ≥ 5.0 reaches 0.9 after about 64 years from the last earthquake (1993) in Saurashtra, about 49 years from the last earthquake (1969) in Mainland Gujarat and about 29 years from the last earthquake (2006) in the Kachchh region. The conditional probability (probability that the next earthquake will occur during some specific time interval after a certain elapsed time from last earthquake) is also estimated and it reaches about 0.8 to 0.9 during the time interval of about 57 to 66 years from the last earthquake (1993) in Saurashtra region, 31 to 51 years from the last earthquake (1969) in Mainland Gujarat and about 21 to 28 years from the last earthquake (2006) in Kachchh region.     

Short- and Long-Term Earthquake Forecasts for California and Nevada

We present estimates of future earthquake rate density (probability per unit area, time, and magnitude) on a 0.1-degree grid for a region including California and Nevada, based only on data from past earthquakes. Our long-term forecast is not explicitly time-dependent, but it can be updated at any time to incorporate information from recent earthquakes. The present version, founded on several decades worth of data, is suitable for testing without updating over a five-year period as part of the experiment conducted by the Collaboratory for Study of Earthquake Predictability  (CSEP). The short-term forecast is meant to be updated daily and tested against similar models by CSEP. The short-term forecast includes a fraction of our long-term one plus time-dependent contributions from all previous earthquakes. Those contributions decrease with time according to the Omori law: proportional to the reciprocal of the elapsed time. Both forecasts estimate rate density using a radially symmetric spatial smoothing kernel decreasing approximately as the reciprocal of the square of epicentral distance, weighted according to the magnitude of each past earthquake. We made two versions of both the long- and short-term forecasts, based on the Advanced National Seismic System  (ANSS) and Preliminary Determinations of Epicenters (PDE) catalogs, respectively. The two versions are quite consistent, but for testing purposes we prefer those based on the ANSS catalog since it covers a longer time interval, is complete to a lower magnitude threshold and has more precise locations. Both forecasts apply to shallow earthquakes only (depth 25 km or less) and assume a tapered Gutenberg-Richter magnitude distribution extending to a lower threshold of 4.0.     

"地震可预测性国际合作研究"——1.0阶段工作理念及成果

20世纪90年代由世界多个国家的地震学家围绕“地震可否预测”问题进行国际讨论后, 人们开始思考适用于地震预测研究的规则应该有哪些, 尤其是地震学家针对地震预测研究中所采取的途径和工作思路开始发生了变化。 2007年开始的“区域地震似然模型”(Regional Earthquake Likelihood Models, RELM)工作组和由此进一步而来的“地震可预测性国际合作研究”(Collaboratory for the Study of Earthquake Predictability, CSEP)计划开始之后, 一大批地震预测模型和与评估其预测效能有关的统计检验方法加入进来, 在设立相同的预测规则和使用统一的数据来源下, 通过全球设立不同测试中心的方式, 共同参与到对地震可预测性问题的系统研究中来。 当前, CSEP计划已由开始的1.0阶段发展至2.0阶段, 为使读者了解与这几项国际合作研究相关的工作主旨和发展历程, 本文总结了与CSEP工作1.0阶段相关的工作理念和工作成果以及存在的问题, 以期为下一步工作的开展提供参考。     

Long-Term RST Analysis of Anomalous TIR Sequences in Relation with Earthquakes Occurred in Greece in the Period 2004–2013

Real-time integration of multi-parametric observations is expected to accelerate the process toward improved, and operationally more effective, systems for time-Dependent Assessment of Seismic Hazard (t-DASH) and earthquake short-term (from days to weeks) forecast. However, a very preliminary step in this direction is the identification of those parameters (chemical, physical, biological, etc.) whose anomalous variations can be, to some extent, associated with the complex process of preparation for major earthquakes. In this paper one of these parameters (the Earth’s emitted radiation in the Thermal InfraRed spectral region) is considered for its possible correlation with M ≥ 4 earthquakes occurred in Greece in between 2004 and 2013. The Robust Satellite Technique (RST) data analysis approach and Robust Estimator of TIR Anomalies (RETIRA) index were used to preliminarily define, and then to identify, significant sequences of TIR anomalies (SSTAs) in 10 years (2004–2013) of daily TIR images acquired by the Spinning Enhanced Visible and Infrared Imager on board the Meteosat Second Generation satellite. Taking into account the physical models proposed for justifying the existence of a correlation among TIR anomalies and earthquake occurrences, specific validation rules (in line with the ones used by the Collaboratory for the Study of Earthquake Predictability—CSEP—Project) have been defined to drive a retrospective correlation analysis process. The analysis shows that more than 93 % of all identified SSTAs occur in the prefixed space–time window around (M ≥ 4) earthquake's time and location of occurrence with a false positive rate smaller than 7 %. Molchan error diagram analysis shows that such a correlation is far to be achievable by chance notwithstanding the huge amount of missed events due to frequent space/time data gaps produced by the presence of clouds over the scene. Achieved results, and particularly the very low rate of false positives registered on a so long testing period, seems already sufficient (at least) to qualify TIR anomalies (identified by RST approach and RETIRA index) among the parameters to be considered in the framework of a multi-parametric approach to t-DASH.     

Test of the EEPAS Forecasting Model on the Japan Earthquake Catalogue

The EEPAS (Every Earthquake a Precursor According to Scale) model is a method of forecasting earthquakes based on the notion that the precursory scale increase () phenomenon occurs at all scales in the seismogenic process. The rate density of future earthquake occurrence is computed directly from past earthquakes in the catalogue. The EEPAS model has previously been fitted to the New Zealand earthquake catalogue and successfully tested on the California catalogue.Here we describe a further test of the EEPAS model in the Japan region spanning 1965–2001, initially on earthquakes with magnitudes exceeding the threshold value 6.75. A baseline model and the Gutenberg-Richter b-value were fitted to the JMA catalogue over the learning period 1926–1964. The performance of EEPAS, with the key parameters unchanged from the New Zealand values, was compared with that of the baseline model over the testing period, using a likelihood ratio criterion. The EEPAS model proved superior. A sensitivity analysis shows that this result is not sensitive to the choice of the learning period or b-value, but that the advantage of EEPAS over the baseline model diminishes as the magnitude threshold is lowered. When key model parameters are optimised for the Japan catalogue, the advantage of EEPAS over the baseline model is consistent for all magnitudes above 6.25, although less than in the New Zealand and California regions.These results add strength to the proposition that the EEPAS model is effective at a variety of scales and in a variety of seismically active regions.     

中长期地震危险性概率预测中的统计检验方法Ⅱ:N-test和L-test方法

本文介绍了国际“地震可预测性合作研究”CSEP计划中, 用于地震概率预测模型检验的N-test和L-test方法的基本原理、 发展动态。 以地震活动平滑模型(smoothed seismicity model)在新疆天山中部地区的中长期预测结果为例, 本文尝试使用N-test和L-test统计检验方法对预测结果进行评价。 结果表明, 上述方法能够较好地评价预测结果, 并有助于构建更为科学合理的地震预测模型及相关参数设置。     

Probabilistic Appraisal of Earthquake Hazard Parameters Deduced from a Bayesian Approach in the Northwest Frontier of the Himalayas

A straightforward Bayesian statistic is applied in five broad seismogenic source zones of the northwest frontier of the Himalayas to estimate the earthquake hazard parameters (maximum regional magnitude M _max, β value of G–R relationship and seismic activity rate or intensity λ). For this purpose, a reliable earthquake catalogue which is homogeneous for M _W ≥ 5.0 and complete during the period 1900 to 2010 is compiled. The Hindukush–Pamir Himalaya zone has been further divided into two seismic zones of shallow (h ≤ 70 km) and intermediate depth (h > 70 km) according to the variation of seismicity with depth in the subduction zone. The estimated earthquake hazard parameters by Bayesian approach are more stable and reliable with low standard deviations than other approaches, but the technique is more time consuming. In this study, quantiles of functions of distributions of true and apparent magnitudes for future time intervals of 5, 10, 20, 50 and 100 years are calculated with confidence limits for probability levels of 50, 70 and 90 % in all seismogenic source zones. The zones of estimated M _max greater than 8.0 are related to the Sulaiman–Kirthar ranges, Hindukush–Pamir Himalaya and Himalayan Frontal Thrusts belt; suggesting more seismically hazardous regions in the examined area. The lowest value of M _max (6.44) has been calculated in Northern-Pakistan and Hazara syntaxis zone which have estimated lowest activity rate 0.0023 events/day as compared to other zones. The Himalayan Frontal Thrusts belt exhibits higher earthquake magnitude (8.01) in next 100-years with 90 % probability level as compared to other zones, which reveals that this zone is more vulnerable to occurrence of a great earthquake. The obtained results in this study are directly useful for the probabilistic seismic hazard assessment in the examined region of Himalaya.     

An evaluation of earthquake hazard parameters in the Iranian Plateau based on the Gumbel III distribution

The Gumbel’s third asymptotic distribution (GIII) of the extreme value method is employed to evaluate the earthquake hazard parameters in the Iranian Plateau. This research quantifies spatial mapping of earthquake hazard parameters like annual and 100-year mode beside their 90 % probability of not being exceeded (NBE) in the Iranian Plateau. Therefore, we used a homogeneous and complete earthquake catalogue during the period 1900–2013 with magnitude M _w ? ≥?4.0, and the Iranian Plateau is separated into equal area mesh of 1° late?×?1° long. The estimated result of annual mode with 90 % probability of NBE is expected to exceed the values of M _w 6.0 in the Eastern part of Makran, most parts of Central and East Iran, Kopeh Dagh, Alborz, Azerbaijan, and SE Zagros. The 100-year mode with 90 % probability of NBE is expected to overpass the value of M _w 7.0 in the Eastern part of Makran, Central and East Iran, Alborz, Kopeh Dagh, and Azerbaijan. The spatial distribution of 100-year mode with 90 % probability of NBE uncovers the high values of earthquake hazard parameters which are frequently connected with the main tectonic regimes of the studied area. It appears that there is a close communication among the seismicity and the tectonics of the region.     

Updated earthquake catalogue for seismic hazard analysis in Pakistan

A reliable and homogenized earthquake catalogue is essential for seismic hazard assessment in any area. This article describes the compilation and processing of an updated earthquake catalogue for Pakistan. The earthquake catalogue compiled in this study for the region (quadrangle bounded by the geographical limits 40–83° N and 20–40° E) includes 36,563 earthquake events, which are reported as 4.0–8.3 moment magnitude (M_W) and span from 25 AD to 2016. Relationships are developed between the moment magnitude and body, and surface wave magnitude scales to unify the catalogue in terms of magnitude M_W. The catalogue includes earthquakes from Pakistan and neighbouring countries to minimize the effects of geopolitical boundaries in seismic hazard assessment studies. Earthquakes reported by local and international agencies as well as individual catalogues are included. The proposed catalogue is further used to obtain magnitude of completeness after removal of dependent events by using four different algorithms. Finally, seismicity parameters of the seismic sources are reported, and recommendations are made for seismic hazard assessment studies in Pakistan.     

Earthquake magnitude estimation using the τ c and P d method for earthquake early warning systems

Earthquake early warning (EEW) systems are one of the most effective ways to reduce earthquake disaster. Earthquake magnitude estimation is one of the most important and also the most difficult parts of the entire EEW system. In this paper, based on 142 earthquake events and 253 seismic records that were recorded by the KiK-net in Japan, and aftershocks of the large Wenchuan earthquake in Sichuan, we obtained earthquake magnitude estimation relationships using the τ _c and P _d methods. The standard variances of magnitude calculation of these two formulas are ±0.65 and ±0.56, respectively. The P _d value can also be used to estimate the peak ground motion of velocity, then warning information can be released to the public rapidly, according to the estimation results. In order to insure the stability and reliability of magnitude estimation results, we propose a compatibility test according to the natures of these two parameters. The reliability of the early warning information is significantly improved though this test.     

From Earthquake Prediction Research to Time-Variable Seismic Hazard Assessment Applications

The first part of the paper defines the terms and classifications common in earthquake prediction research and applications. This is followed by short reviews of major earthquake prediction programs initiated since World War II in several countries, for example the former USSR, China, Japan, the United States, and several European countries. It outlines the underlying expectations, concepts, and hypotheses, introduces the technologies and methodologies applied and some of the results obtained, which include both partial successes and failures. Emphasis is laid on discussing the scientific reasons why earthquake prediction research is so difficult and demanding and why the prospects are still so vague, at least as far as short-term and imminent predictions are concerned. However, classical probabilistic seismic hazard assessments, widely applied during the last few decades, have also clearly revealed their limitations. In their simple form, they are time-independent earthquake rupture forecasts based on the assumption of stable long-term recurrence of earthquakes in the seismotectonic areas under consideration. Therefore, during the last decade, earthquake prediction research and pilot applications have focused mainly on the development and rigorous testing of long and medium-term rupture forecast models in which event probabilities are conditioned by the occurrence of previous earthquakes, and on their integration into neo-deterministic approaches for improved time-variable seismic hazard assessment. The latter uses stress-renewal models that are calibrated for variations in the earthquake cycle as assessed on the basis of historical, paleoseismic, and other data, often complemented by multi-scale seismicity models, the use of pattern-recognition algorithms, and site-dependent strong-motion scenario modeling. International partnerships and a global infrastructure for comparative testing have recently been developed, for example the Collaboratory for the Study of Earthquake Predictability (CSEP) with test regions in California, Italy, Japan, New Zealand, and the Western Pacific. Algorithms and data bases are operated in a permanently learning and upgrading mode. Future perspectives and research requirements and the feasibility and possible problems encountered with the implementation of earthquake predictions in practice are briefly summarized.     

Efficient testing of earthquake forecasting models

Computationally efficient alternatives are proposed to the likelihood-based tests employed by the Collaboratory for the Study of Earthquake Predictability for assessing the performance of earthquake likelihood models in the earthquake forecast testing centers. For the conditional L-test, which tests the consistency of the earthquake catalogue with a model, an exact test using convolutions of distributions is available when the number of earthquakes in the test period is small, and the central limit theorem provides an approximate test when the number of earthquakes is large. Similar methods are available for the R-test, which compares the likelihoods of two competing models. However, the R-test, like the N-test and L-test, is fundamentally a test of consistency of data with a model. We propose an alternative test, based on the classical paired t-test, to more directly compare the likelihoods of two models. Although approximate and predicated on a normality assumption, this new T-test is not computer-intensive, is easier to interpret than the R-test, and becomes increasingly dependable as the number of earthquakes increases.     

Earthquake Source Zones in Northeast India: Seismic Tomography, Fractal Dimension and b Value Mapping

We have imaged earthquake source zones beneath the northeast India region by seismic tomography, fractal dimension and b value mapping. 3D P-wave velocity (Vp) structure is imaged by the Local Earthquake Tomography (LET) method. High precision P-wave (3,494) and S-wave (3,064) travel times of 980 selected earthquakes, m _d ≥ 2.5, are used. The events were recorded by 77 temporary/permanent seismic stations in the region during 1993–1999. By the LET method simultaneous inversion is made for precise location of the events as well as for 3D seismic imaging of the velocity structure. Fractal dimension and seismic b value has been estimated using the 980 LET relocated epicenters. A prominent northwest–southeast low Vp structure is imaged between the Shillong Plateau and Mikir hills; that reflects the Kopili fault. At the fault end, a high-Vp structure is imaged at a depth of 40 km; this is inferred to be the source zone for high seismic activity along this fault. A similar high Vp seismic source zone is imaged beneath the Shillong Plateau at 30 km depth. Both of the source zones have high fractal dimension, from 1.80 to 1.90, indicating that most of the earthquake associated fractures are approaching a 2D space. The spatial fractal dimension variation map has revealed the seismogenic structures and the crustal heterogeneities in the region. The seismic b value in northeast India is found to vary from 0.6 to 1.0. Higher b value contours are obtained along the Kopili fault (~1.0), and in the Shillong Plateau (~0.9) The correlation coefficient between the fractal dimension and b value is found to be 0.79, indicating that the correlation is positive and significant. To the south of Shillong Plateau, a low Vp structure is interpreted as thick (~20 km) sediments in the Bengal basin, with almost no seismic activity in the basin.     

An improved earthquake catalogue (<Emphasis Type="Italic">M</Emphasis> ≥ 4.0) for Turkey and its near vicinity (1900–2012)

Many catalogues, agency reports and research articles have been published on seismicity of Turkey and its surrounding since 1950s. Given existing magnitude heterogeneity, erroneous information on epicentral location, event date and time, this past published data however is far from fulfilling the required standards. Paucity of a standardized format in the available catalogues have reinforced the need for a refined and updated catalogue for earthquake related hazard and risk studies. During this study, ~37,000 earthquakes and related parametric data were evaluated by utilizing more than 41 published studies and, an integrated database was prepared in order to analyse all parameters acquired from the catalogues and references for each event. Within the scope of this study, the epicentral locations of M ≥ 5.0 events were firstly reappraised based on the updated Active Fault Map of Turkey. An improved catalogue of 12.674 events for the period 1900–2012 was as a result recompiled for the region between 32–45N° and 23–48E° by analyzing in detail accuracy of all seismological parameters available for each event. The events consist of M ≥ 4.0 are reported in several magnitude scales (e.g. moment magnitude, M_w; surface wave magnitude, M_S; body-wave magnitude m_b; local magnitude M_L and duration magnitude M_d) whereas the maximum focal depth reaches up to 225-km. In order to provide homogenous data, the improved catalogue is unified in terms of M_w. Fore-and aftershocks were also removed from the catalogue and completeness analyses were performed both separately for various tectonic sources and as a whole for the study region of interest. Thus, the prepared homogenous and declustered catalogue consisting of 6573 events provides the basis for a reliable input to the seismic hazard assessment studies for Turkey and its surrounding areas.     

“Repeating Events” as Estimator of Location Precision: The China National Seismograph Network

“Repeating earthquakes” identified by waveform cross-correlation, with inter-event separation of no more than 1 km, can be used for assessment of location precision. Assuming that the network-measured apparent inter-epicenter distance X of the “repeating doublets” indicates the location precision, we estimated the regionalized location quality of the China National Seismograph Network by comparing the “repeating events” in and around China by Schaff and Richards (Science 303: 1176–1178, 2004; J Geophys Res 116: B03309, 2011) and the monthly catalogue of the China Earthquake Networks Center. The comparison shows that the average X value of the China National Seismograph Network is approximately 10 km. The mis-location is larger for the Tibetan Plateau, west and north of Xinjiang, and east of Inner Mongolia, as indicated by larger X values. Mis-location is correlated with the completeness magnitude of the earthquake catalogue. Using the data from the Beijing Capital Circle Region, the dependence of the mis-location on the distribution of seismic stations can be further confirmed.     

Large Earthquake Hazard of the San Jacinto Fault Zone,CA, from Long Record of Simulated Seismicity Assimilating the Available Instrumental and Paleoseismic Data

We investigate spatio-temporal properties of earthquake patterns in the San Jacinto fault zone (SJFZ), California, between Cajon Pass and the Superstition Hill Fault, using a long record of simulated seismicity constrained by available seismological and geological data. The model provides an effective realization of a large segmented strike-slip fault zone in a 3D elastic half-space, with heterogeneous distribution of static friction chosen to represent several clear step-overs at the surface. The simulated synthetic catalog reproduces well the basic statistical features of the instrumental seismicity recorded at the SJFZ area since 1981. The model also produces events larger than those included in the short instrumental record, consistent with paleo-earthquakes documented at sites along the SJFZ for the last 1,400 years. The general agreement between the synthetic and observed data allows us to address with the long-simulated seismicity questions related to large earthquakes and expected seismic hazard. The interaction between m ≥ 7 events on different sections of the SJFZ is found to be close to random. The hazard associated with m ≥ 7 events on the SJFZ increases significantly if the long record of simulated seismicity is taken into account. The model simulations indicate that the recent increased number of observed intermediate SJFZ earthquakes is a robust statistical feature heralding the occurrence of m ≥ 7 earthquakes. The hypocenters of the m ≥ 5 events in the simulation results move progressively towards the hypocenter of the upcoming m ≥ 7 earthquake.     

PI Forecast for the Sichuan-Yunnan Region: Retrospective Test after the May 12, 2008, Wenchuan Earthquake

The May 12, 2008, Wenchuan M _S 8.0/M _w 7.9 earthquake occurred in the middle part of the north–south seismic zone in central west China, being one of the greatest thrust events on land in recent years. To explore whether there were some indications of the increase of strong earthquake probabilities before the Wenchuan earthquake, we conducted a retrospective forecast test applying the Pattern Informatics (PI) algorithm to the earthquakes in the Sichuan-Yunnan region since 1992. A regional earthquake catalogue complete to M _L 3.0 from 01/01/1977 to 15/06/2008 was used. A 15-year long ‘sliding time window’ was used in the PI calculation, with ‘anomaly training time window’ and ‘forecast time window’ both set to 5 years. With a forecast target magnitude of M _S 5.5, the ROC test shows that the PI forecast outperforms not only random guess but also the simple number-counting approach based on the clustering hypothesis of earthquakes (the RI forecast). ‘Hotspots’ can be seen in the region of the northern Longmenshan fault which is responsible for the Wenchuan earthquake. However, when considering bigger grid size and higher cutoff magnitude, such ‘hotspots’ disappear and there is very little indication of an impending great earthquake.