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Slow slip events (SSEs) at subduction zone plate boundaries sometimes trigger earthquake swarms and megathrust earthquakes. The causal relationship between SSEs and seismicity has been studied worldwide, but the epidemic-type aftershock-sequence (ETAS) model, which is a standard statistical model of seismicity, does not explicitly consider the seismicity-triggering effect of SSEs. Therefore, if an SSE occurs at a plate boundary, probabilistic earthquake forecasts based on the ETAS model fail to predict observed seismicity. Here, we constructed a statistical model named the SSE-modulated ETAS model by incorporating SSE moment rates estimated from observation data from the global navigation satellite system into the original ETAS model. Our model assumes a linear or power-law relationship between the SSE moment rates and seismicity rates and estimates its proportionality constant as a new ETAS parameter. We applied this new model to three SSEs and M 2.5 or greater earthquakes in the shallow part of the Hikurangi Trench, New Zealand. The results show that it is better than the original ETAS model, giving a significant reduction in the Akaike information criterion. In addition, we examined the functional forms (e.g., lag time and power exponent) of the equation relating the moment rate of the SSEs to the seismicity rate. We also examine the influence of SSEs on aftershock productivity. Our model can improve short-term forecasts of seismicity associated with SSEs if the detection and characterization of SSEs can be done in near real time. Our model is also useful for quantifying characteristics of SSE-induced seismicity.

Public Participation (in earthquake monitoring and forecast) and Public Preparedness (for seismic disaster risk reduction), or P4, is one of the interesting, and often underestimated approach to earthquake forecast. In the era of big data, this community/public approach faces new challenges and new opportunities and may contribute to earthquake science. Taking China as an example, and focusing on earthquake forecasts. This article reviews some of the key issues currently under discussion. It seems that new developments make it possible to foster a ‘version 2.0’ of P4, empowered by information technology.

To aid in setting scientific research priorities, we assess the potential value of removing each of the epistemic uncertainties currently represented in the US Geological Survey California seismic-hazard model, using average annual loss (AAL) as the risk metric of interest. Given all the uncertainties, represented with logic-tree branches, we find a mean AAL of $3.94 billion. The modal value is 17.5% lower than the mean, and there is a 78% chance that the true AAL value is more than 10% away from the mean, and a 5% chance that it is a factor 2.1 greater or lower than the mean. We quantify the extent to which resolving each uncertainty improves the AAL estimate. The most influential branch is one that adds additional epistemic uncertainty to ground motion models, but others are found to be influential as well, such as the rate of M ≥ 5 events throughout the region. We discuss the broader implications of our findings, and note that the time dependence caused by spatiotemporal clustering can be much more influential on AAL than the epistemic uncertainties explored here.

Currently, one of the best performing and most popular earthquake forecasting models rely on the working hypothesis that: "locations of past background earthquakes reveal the probable location of future seismicity". As an alternative, we present a class of smoothed seismicity models (SSMs) based on the principles of the Epidemic Type Aftershock Sequence (ETAS) model, which forecast the location, time and magnitude of all future earthquakes using the estimates of the background seismicity rate and the rates of future aftershocks of all generations. Using the Californian earthquake catalog, we formulate six controlled pseudo-prospective experiments with different combination of three target magnitude thresholds: 2.95, 3.95 or 4.95 and two forecasting time horizons: 1 or 5 year. In these experiments, we compare the performance of:(1) ETAS model with spatially homogenous parameters or GETAS (2) ETAS model with spatially variable parameters or SVETAS (3) three declustering based SSMs (4) a simple SSM based on undeclustered data and (5) a model based on strain rate data, in forecasting the location and magnitude of all (undeclustered) target earthquakes during many testing periods. In all conducted experiments, the SVETAS model comes out with consistent superiority compared to all the competing models. Consistently better performance of SVETAS model with respect to declustering based SSMs highlights the importance of forecasting the future aftershocks of all generations for developing better earthquake forecasting models. Among the two ETAS models themselves, accounting for the optimal spatial variation of the parameters leads to strong and statistically significant improvements in forecasting performance.

Have been studied the concentrations of dissolved helium in the water of a artesian well in the Southern Cis-Baikal region. It is established that on the eve of earthquakes they experience certain variations. Based on the obtained data, the correlation function lgτR (the logarithm of the time product of the harbinger of the seismic event at its epicentral distance) is calculated from the energy class of the earthquake. It is proposed to consider variations in the concentration of helium as a short-term precursor of earthquakes.

In seismic hazard studies, simulation techniques are exploited relatively less compared to other statistical methods. The main purposes of their use were merely scientific: either to reduce uncertainty in seismic hazard or to test the consistency of a forecast. Its limited exploitation in the field does not mean that the method could not be exploited further. Given sufficient data and with the right models, a full-scale simulation is possible, which in fact becomes a forecast with future timing, location and magnitude of future events are simulated. Within this context, the main purpose of this study is to layout a method to create a full scale simulation with all the parameters namely the time, location and magnitude of an earthquake is simulated. For that purpose, in addition to the main parameters defining past seismic patterns, namely the temporal, spatial, magnitude distributions, the combined spatio-magnitude distribution is also modeled. As another improvement compared to the current procedures, occurrence date is assigned to the simulated event according to the inter-event time distribution, which enhances the simulation procedure. The eventual temporal distribution and the associated earthquake rates are checked with the original earthquake rate for its consistency. In the end, a simulation procedure, which can also be used as a forecast model is developed to improve the existing procedures further.

Seismic hazard modeling is a multidisciplinary science that aims to forecast earthquake occurrence and its resultant ground shaking. Such models consist of a probabilistic framework that quantifies uncertainty across a complex system; typically, this includes at least two model components developed from Earth science: seismic source and ground motion models. Although there is no scientific prescription for the forecast length, the most common probabilistic seismic hazard analyses consider forecasting windows of 30 to 50 years, which are typically an engineering demand for building code purposes. These types of analyses are the topic of this review paper. Although the core methods and assumptions of seismic hazard modeling have largely remained unchanged for more than 50 years, we review the most recent initiatives, which face the difficult task of meeting both the increasingly sophisticated demands of society and keeping pace with advances in scientific understanding. A need for more accurate and spatially precise hazard forecasting must be balanced with increased quantification of uncertainty and new challenges such as moving from time-independent hazard to forecasts that are time dependent and specific to the time period of interest. Meeting these challenges requires the development of science-driven models, which integrate all information available, the adoption of proper mathematical frameworks to quantify the different types of uncertainties in the hazard model, and the development of a proper testing phase of the model to quantify its consistency and skill. We review the state of the art of the National Seismic Hazard Modeling and how the most innovative approaches try to address future challenges.

Five large earthquakes of M ≥ 7.0 (based on the magnitude scale of the China Earthquake Networks Center) occurred in and near the Tibetan Plateau during 2008–2014, including the Wenchuan M8.0 earthquake on May 12, 2008 (BJT). In this paper, the Tibetan Plateau was chosen to be the study region, and calculating parameters of pattern informatics (PI) method with grid of 1◦ × 1◦ and forecasting time interval of 8 years were employed for the retrospective study according to the previous studies for M7 earthquake forecasting. The sliding step of forecasting interval was 1 year, and the hotspot diagrams of each forecasting interval since 2008 were obtained year by year. The relationships among the hotspots and the M ≥ 7.0 earthquakes that occurred during the forecast intervals were studied. The predictability of PI method was tested by verification of receiveroperating characteristic curve (ROC) and R score. The results show that the successive obvious hotspots occurred during the sliding forecasting intervals before four of the five earthquakes, while hotspots only occurred in one forecasted interval without successive evolution process before one of the five earthquakes, which indicates that four of the five large earthquakes could be forecasted well by PI method. Test results of the predictability of PI method by ROC and R score show that positive prospect of PI method could be expected for long-term earthquake forecast.

We, the ongoing Working Group on California Earthquake Probabilities, present a spatiotemporal clustering model for the Third Uniform California Earthquake Rupture Forecast (UCERF3), with the goal being to represent aftershocks, induced seismicity, and otherwise triggered events as a potential basis for operational earthquake forecasting (OEF). Specifically, we add an epidemic‐type aftershock sequence (ETAS) component to the previously published time‐independent and long‐term time‐dependent forecasts. This combined model, referred to as UCERF3‐ETAS, collectively represents a relaxation of segmentation assumptions, the inclusion of multifault ruptures, an elastic‐rebound model for fault‐based ruptures, and a state‐of‐the‐art spatiotemporal clustering component. It also represents an attempt to merge fault‐based forecasts with statistical seismology models, such that information on fault proximity, activity rate, and time since last event are considered in OEF. We describe several unanticipated challenges that were encountered, including a need for elastic rebound and characteristic magnitude–frequency distributions (MFDs) on faults, both of which are required to get realistic triggering behavior. UCERF3‐ETAS produces synthetic catalogs of M ≥2.5 events, conditioned on any prior M ≥2.5 events that are input to the model. We evaluate results with respect to both long‐term (1000 year) simulations as well as for 10‐year time periods following a variety of hypothetical scenario mainshocks. Although the results are very plausible, they are not always consistent with the simple notion that triggering probabilities should be greater if a mainshock is located near a fault. Important factors include whether the MFD near faults includes a significant characteristic earthquake component, as well as whether large triggered events can nucleate from within the rupture zone of the mainshock. Because UCERF3‐ETAS has many sources of uncertainty, as will any subsequent version or competing model, potential usefulness needs to be considered in the context of actual applications. [Electronic Supplement:][1] Figures showing discretization, verification of the DistanceDecayCubeSampler , average simulated participation rate, and average cumulative magnitude–frequency distributions (MFDs). [1]: http://www.bssaonline.org/lookup/suppl/doi:10.1785/0120160173/-/DC1

We present highlights from the first decade of operation of the New Zealand Earthquake Forecast Testing Center of the Collaboratory for the Study of Earthquake Predictability (CSEP). Most results are based on reprocessing using the best available catalog, because the testing center did not consistently capture the complete real-time catalog. Tests of models with daily updating show that aftershock models incorporating Omori- Utsu decay can outperform long-term smoothed seismicity models with probability gains up to 1000 during major aftershock sequences. Tests of models with 3-month updating show that several models with every earthquake a precursor according to scale (EEPAS) model, incorporating the precursory scale increase phenomenon and without Omori-Utsu decay, and the double-branching model, with both Omori-Utsu and exponential decay in time, outperformed a regularly updated smoothed seismicity model. In tests of 5-yr models over 10 yrs without updating, a smoothed seismicity model outperformed the earthquake source model of the New Zealand National Seismic Hazard Model. The performance of 3-month and 5-yr models was strongly affected by the Canterbury earthquake sequence, which occurred in a region of previously low seismicity. Smoothed seismicity models were shown to perform better with more frequent updating. CSEP models were a useful resource for the development of hybrid time-varying models for practical forecasting after major earthquakes in the Canterbury and Kaikoura regions. © 2018 Seismological Society of America. All rights reserved.

Multiple geophysical parameters including groundwater level, water temperature, water radon, crustal deformation, electromagnetic waves and total electron contents (TEC) in the ionosphere, are examined together to investigate pre-earthquake anomalous phenomena associated with the Mw6.1 Ludian earthquake on August 3, 2014. Cross-parameter comparison eliminates anomalies that are detected in one parameter only and examine earthquake-related phenomena in various fields, simultaneously. Retrieved anomalies show that abnormal decreases of water temperature and radon concentration related to anomalous uplift of groundwater levels appeared about 1–8 days before the earthquake even without contributions from rain. Significant step-like changes are observed from data recorded by strainmeters on July 31 and are consistent with water-related anomalies in timing. No significant anomalies can be found from electromagnetic data through the preliminary observation. In contrast, TEC appeared positive anomalies 1–3 days before the Ludian earthquake. Although causal mechanisms of the TEC anomalies from stressed rocks are not fully understood, multiple-parameter examination can increase credibility of determination regarding pre-earthquake phenomena.

Recent earthquakes, particularly the 2008 Wenchuan (China), 2009 L’Aquila (Italy), 2010 Haiti, 2011 Christchurch (New Zealand), and 2011 Tohoku (Japan), events, have renewed debate among scientists (e.g., Jordan et al. , 2011; Stein et al. , 2011; Peresan et al. , 2012; Stirling, 2012; Jordan, 2013; Jordan et al. , 2014; Wang and Rogers, 2014) on predicting or forecasting earthquakes and their resulting ground‐motion hazards. The main reason for this debate is societal demand for predicting or forecasting. In other words, scientists, seismologists in particular, feel compelled to provide predictions or forecasts to society. The initial sentencing of six years in prison for six Italian scientists following the 2009 L’Aquila earthquake demonstrates this. However, it is well understood that earthquakes and their resulting ground‐motion hazards cannot be predicted or forecasted reliably. Thus, the statement by Jordan et al. (2014, p. 959), “though communicating OEF (operational earthquake forecast) and its uncertainties is a difficult issue, not communicating is hardly an option,” illustrates the dilemma. > Scientists, seismologists in particular, feel compelled to provide earthquake predictions or forecasts to society. The differences between predicting and forecasting have to do with how they quantify and communicate uncertainty. Location, magnitude, and recurrence interval of earthquakes have large uncertainty. For example, the estimated magnitudes for earthquakes in the New Madrid Seismic Zone range from M 6.6 to M 8.0, and estimates of the recurrence interval range from 500 to 50,000 years (Petersen et al. , 2014). Uncertainties of this scale indicate that earthquakes cannot be predicted or forecasted reliably. One such example is Iben Browning’s forecast: a 50% chance of a major earthquake with a magnitude of about 7 in the New Madrid Seismic Zone within a few days of 3 December 1990 (Stein, 2010). Even though the 1975 Haicheng, China, earthquake has been claimed as …

We introduce a method of resolving temporal incidence trends in earthquake sequences. We have developed a catalog partitioning method based on canonical earthquake scaling relationships, and have further developed a metric based on record-breaking interval (RBI) statistics to resolve increasing and decreasing seismicity in time series of earthquakes. We calculated the RBI metric over fixed-length sequences of earthquake intervals and showed that the length of those sequences is related to the magnitude of the earthquake to which the method is sensitive—longer sequences resolve large earthquakes, shorter sequences resolve small-magnitude events. This sequence length effectively constitutes a local temporal catalog constraint, and we show that spatial constraints can be defined from rupture length scaling. We have applied the method to several high-profile earthquakes and have shown that it consistently resolves aftershock sequences after a period of accelerating seismicity before the targeted mainshock. The method also suggests a minimum detectable (forecastable) mainshock magnitude on the basis of the catalog’s minimum completeness magnitude $$m_{\rm c}$$ .

The change of the structure of seismic event sequences in focal area in preparation period of strong earthquakes has been studied. Findings show that weak earthquake clustering in time increases in earlier stage of forming of focal area. However, spatial clustering of seismic events rises at the latest stage.

[1] In order to develop new tools or techniques to detect short-term slow slip events (S-SSEs) along subduction zones, we attempted to detect S-SSEs by conducting groundwater pressure observations. At ANO station, which is a groundwater observation station operated by the Geological Survey of Japan, the National Institute of Advanced Industrial Science and Technology, for earthquake prediction research, groundwater pressures changed due to six S-SSEs that occurred near ANO from June 2011 to April in 2013. The fault models of these S-SSEs, which were estimated mainly by observing the crustal strains and tilts, explained the changes in the groundwater pressures. If the strain sensitivity of the observed groundwater pressure or level is larger than 1 mm/nstrain and the noise level is smaller than 50 mm/day, it is possible to detect S-SSEs that occur in southwest Japan by conducting groundwater pressure or level observations.

Science and Technology (S & T) interventions are considered to be very important in any effort related to earthquake risk reduction. Their three main components are: earthquake forecast, assessment of earthquake hazard, and education and awareness. In India, although the efforts towards earthquake forecast were initiated about two decades ago, systematic studies started recently with the launch of a National Program on Earthquake Precursors. The quantification of seismic hazard, which is imperative in the present scenario, started in India with the establishment of first seismic observatory in 1898 and since then a substantial progress has been made in this direction. A dedicated education and awareness program was initiated about 10 years ago to provide earthquake education and create awareness amongst the students and society at large. The paper highlights significant S & T efforts made in India towards reduction of risk due to future large earthquakes.

Optical observations from a ground-based astrometric instrument provide a unique set of data sensitive to variations of local plumb line, which represent the change of local gravitational field on the ground. The local gravitational change could be caused by density variation or movement of underground mass in addition to tidal action. Earthquake was found to be related with gravitational change. A seismic zone could have abnormal underground material density, causing the variation of plume line on the ground. In this frame, the astrometric telescope can measure the variation of local plumb line by observing the local astronomical longitudes and latitudes from stars in the Hipparcos catalog. In this study, we estimate the deflection angle of the plumb line on a ground site, and give a relation between the angle, abnormal mass and site distance (depth and horizontal distance). Then we derive the abnormality of underground material density using the plumb lines measured at different sites, and study the earthquake gestation, development and occurrence. Using the deflection angles of plumb lines observed at two sites, we give a method to calculate the mass and the center of gravity of underground materials. We also estimate the abnormal masses of latent seismic zones with different energy, using thermodynamic relations, and introduce a new optical astrometric instrument we had developed.

We propose a conversion method from alarm-based to rate-based earthquake forecast models. A differential probability gain g(alarm)(ref) is the absolute value of the local slope of the Molchan trajectory that evaluates the performance of the alarm-based model with respect to the chosen reference model. We consider that this differential probability gain is constant over time. Its value at each point of the testing region depends only on the alarm function value. The rate-based model is the product of the event rate of the reference model at this point multiplied by the corresponding differential probability gain. Thus, we increase or decrease the initial rates of the reference model according to the additional amount of information contained in the alarm-based model. Here, we apply this method to the Early Aftershock STatistics (EAST) model, an alarm-based model in which early aftershocks are used to identify space-time regions with a higher level of stress and, consequently, a higher seismogenic potential. The resulting rate-based model shows similar performance to the original alarm-based model for all ranges of earthquake magnitude in both retrospective and prospective tests. This conversion method offers the opportunity to perform all the standard evaluation tests of the earthquake testing centers on alarm-based models. In addition, we infer that it can also be used to consecutively combine independent forecast models and, with small modifications, seismic hazard maps with short- and medium-term forecasts.

SUMMARY Reliability diagrams are a standard forecast evaluation tool for comparing forecasted probabilities of binary events with their observed frequencies. To make this comparison for rare events, forecasts of similar probability are grouped together. Here, we demonstrate the utility of reliability diagrams for earthquake forecast evaluation with an application to a modified version of the Holliday et al. time-dependent earthquake forecasting method. We quantify reliability with a χ2 statistic and find that the forecasting method is consistent with reliability; that is, forecast probabilities match rates of occurrence to within the expected uncertainties.

Several earthquake forecast experiments in Italy have been initiated within the European testing center of the global Collaboratory for the Study of Earthquake Predictability. In preparation for these experiments, we developed space-rate-magnitude forecasts based on a simple model that incorporates the spatial clustering of the seismicity. This model, which we call the simple smoothed seismicity model (TripleS), has a minimal number of free parameters and is based on very few assumptions; therefore, it can be considered as a model of «least information» with which others can be compared. The fundamental TripleS parameter controls the spatial extent of the smoothing, and we selected its value based on an optimization procedure that was applied to retrospective forecast experiments. In this report, we present the motivation for developing TripleS, and describe the construction of forecasts for Italian seismicity. We also discuss the research questions that remain to be answered with respect to TripleS, and more generally, the smoothed seismicity approach to earthquake forecasting.

The five-year experiment of the Regional Earthquake Likelihood Models (RELM) working group was designed to compare several prospective forecasts of earthquake rates in latitude–longitude–magnitude bins in and around California. This forecast format is being used as a blueprint for many other earthquake predictability experiments around the world, and therefore it is important to consider how to evaluate the performance of such forecasts. Two tests that are currently used are based on the likelihood of the observed distribution of earthquakes given a forecast; one test compares the binned space–rate–magnitude observation and forecast, and the other compares only the rate forecast and the number of observed earthquakes. In this article, we discuss a subtle flaw in the current test of rate forecasts, and we propose two new tests that isolate the spatial and magnitude component, respectively, of a space–rate–magnitude forecast. For illustration, we consider the RELM forecasts and the distribution of earthquakes observed during the first half of the ongoing RELM experiment. We show that a space–rate–magnitude forecast may appear to be consistent with the distribution of observed earthquakes despite the spatial forecast being inconsistent with the spatial distribution of observed earthquakes, and we suggest that these new tests should be used to provide increased detail in earthquake forecast evaluation. We also discuss the statistical power of each of the likelihood-based tests and the stability (with respect to earthquake catalog uncertainties) of results from the likelihood-based tests.

The New Zealand Earthquake Forecast Testing Centre is being established as one of several similar regional testing centres under the umbrella of the Collaboratory for the Study of Earthquake Predictability (CSEP). The Centre aims to encourage the development of testable models of time-varying earthquake occurrence in the New Zealand region, and to conduct verifiable prospective tests of their performance over a period of five or more years. The test region, data-collection region and requirements for testing are described herein. Models must specify in advance the expected number of earthquakes with epicentral depths h ≤ 40 km in bins of time, magnitude and location within the test region. Short-term models will be tested using 24-h time bins at magnitude M ≥ 4. Intermediate-term models and long-term models will be tested at M ≥ 5 using 3-month, 6-month and 5-year bins, respectively. The tests applied will be the same as at other CSEP testing centres: the so-called N test of the total number of earthquakes expected over the test period; the L test of the likelihood of the earthquake catalogue under the model; and the R test of the ratio of the likelihoods under alternative models. Four long-term, three intermediate-term and two short-term models have been installed to date in the testing centre, with tests of these models commencing on the New Zealand earthquake catalogue from the beginning of 2008. Submission of models is open to researchers worldwide. New models can be submitted at any time. The New Zealand testing centre makes extensive use of software produced by the CSEP testing centre in California. It is envisaged that, in time, the scope of the testing centre will be expanded to include new testing methods and differently-specified models, nonetheless that the New Zealand testing centre will develop in parallel with other regional testing centres through the CSEP international collaborative process.

According to S.A. Fedotov’s long-term earthquake forecast, the Middle Kuril Is. has long (since 1965) been a likely location for the next M ≥ 7.7 earthquake, i.e., a seismic gap. The present study integrates seismological, geological, and geophysical data to assess the earthquake potential of the gap prior to November 15, 2006. Seismological data were used to carry out a comparative analysis of 3D seismic energy density for three zones of the Kuril region. The density for the Middle Kuril Is. turned out to be twice as small as that for the North Kuril Is. and nearly six times as small as that for the South Kurils. Various parameters of the seismic process for the Kuril region have been estimated in quantitative terms. It is shown that the rate of completely reported (M ≥ 6) earthquakes occurring down to 70 km depth in the Middle Kuril Is. is approximately three times as small as that for the entire Kuril arc. Increased heat flow was recorded there (up to 100 mW/m2). The top of the high conductivity layer is shallower (at a depth of 100 km). The trends of major faults and other seismotectonic features have been taken into account. Based on these data (prior to November 15, 2006), the previous conclusion about the low seismic activity of the Middle Kuril Is. was corroborated. Two great earthquakes occurred in the region on November 15, 2006 (Mw = 8.3) and January 13, 2007 (Mw = 8.1) with subsequent tsunami waves. The erroneous inference as to low seismic activity was related to the fact that the seismic cycle in the Middle Kuril Is. may be as long as 150–200 years. We come to the conclusion that an analysis of the level of seismic activity for the region should start with the construction of standardized recurrence curves and determining the magnitude of the maximum possible earthquake.

This article summarizes the 1988, 1990, 1995, and 2002 Working Groups on California Earthquake Probabilities (wgceps). Each of these studies used the best available science to make a time-dependent earthquake forecast. All involved applying elastic-rebound-theory–motivated recurrence models to estimate the probability of rupture on discrete fault segments. The focus was necessarily limited to those faults that had sufficient information to make a time-dependent analysis, although the later studies included probabilities for other events as well. This manuscript does not give a point-by-point critique or review of the previous wgceps, both because it would take considerably more text and because such discussions will necessarily be documented by future working groups as they justify changes. One opinion that is emphasized, however, is that future wgceps should resist overcomplexity in certain aspects of the model given basic assumptions that have been made and/or limitations in our understanding of the earthquake system. For example, one might argue that the level of sophistication applied by previous wgceps with respect to recurrence-interval variability and uncertainty was overkill given their basic assumptions that large earthquakes obey segment boundaries, ruptures never jump from one fault to another, and earthquake-clustering effects can be ignored.

We have initially developed a time-independent forecast for southern California by smoothing the locations of magnitude 2 and larger earthquakes. We show that using small m 2 earthquakes gives a reasonably good prediction of m 5 earthquakes. Our forecast outperforms other time-independent models (Kagan and Jackson, 1994; Frankel et al., 1997), mostly because it has higher spatial resolution. We have then developed a method to estimate daily earthquake probabilities in south- ern California by using the Epidemic Type Earthquake Sequence model (Kagan and Knopoff, 1987; Ogata, 1988; Kagan and Jackson, 2000). The forecasted seismicity rate is the sum of a constant background seismicity, proportional to our time- independent model, and of the aftershocks of all past earthquakes. Each earthquake triggers aftershocks with a rate that increases exponentially with its magnitude and decreases with time following Omori's law. We use an isotropic kernel to model the spatial distribution of aftershocks for small (m 5.5) mainshocks. For larger events, we smooth the density of early aftershocks to model the density of future aftershocks. The model also assumes that all earthquake magnitudes follow the Gutenberg-Richter law with a uniform b-value. We use a maximum likelihood method to estimate the model parameters and test the short-term and time-independent forecasts. A retro- spective test using a daily update of the forecasts between 1 January 1985 and 10 March 2004 shows that the short-term model increases the average probability of an earthquake occurrence by a factor 11.5 compared with the time-independent forecast.

There are many earthquake catalogs covering California, but none includes everything one would like to have for constructing and testing hypotheses of earthquake occurrence. Perhaps it is most obvious that focal mechanism estimates are needed in many phases of earthquake forecasting and evaluation. They are needed for estimating the stress increments from past earthquakes, for identifying those earthquakes that have been encouraged by known previous earthquakes, and for testing models that forecast focal mechanisms as well as location and magnitude. Focal mechanisms are available for recent, instrumentally recorded earthquakes, but they are not yet uniformly available for all relevant quakes, and there are often alternate solutions for recent events. Some focal mechanisms are available for large historic (that is, pre-instrumental) earthquakes, but these estimates are generally scattered through the literature rather than systematically cataloged. Instrumentally determined focal mechanisms are clearly best, but estimated ones can still be useful. Measured focal mechanisms show some degree of regularity that can be exploited to estimate unmeasured ones from nearby measured values. Some earthquake forecasts explicitly apply to mainshocks as well as aftershocks, while others, like the source model for the 2002 National Seismic Hazard Map, are meant to apply to mainshocks only. For those reasons it would be convenient to have a catalog in which all known events are included, but which labels aftershocks in a way that they can be removed or down-weighted as needed. Earthquake catalog data, like any other results, are subject to errors. Location errors for historic earthquakes and magnitude errors for all events could well affect the assessment of an earthquake forecast. Statistical tests can and should account for the uncertainties in catalog data. To date, such tests have not been employed for earthquake forecasts, in part because the uncertainties are poorly understood. It is well known that …

The medium-short term forecast for a certain kinds of main earthquake events might be possible with the time-to-failure method presented by Varnes (1989), Bufe and Varnes (1993), which is to simulate an accelerative releasing model of precursory earthquake energy. By fitting the observed data with the theoretical formula, a medium-short term forecast technique for the main shock events could be established, by which the location, time and magnitude of the main shock could be determined. The data used in the paper are obtained from the earthquake catalogue recorded by Yunnan Regional Seismological Network with a time coverage of 1965-2002. The statistical analyses for the past 37 years show that the data ofM≥2.5 earthquakes were fairly complete. In the present paper, 30 main shocks occurred in Yunnan region were simulated. For 25 of them, the forecasting time and magnitude from the simulation of precursory sequence are very close to the actual values with the precision of about ±0.57 (magnitude unit). Suppose that the last event of the precursory sequence is known, then the time error for the forecasting main shock is about ±0.64 year. For the other 5 main shocks, the simulation cannot be made due to the insufficient precursory events for the full determination of energy accelerating curve or disturbance to the energy-release curve. The results in the paper indicate that there is no obviously linear relation in the optimal searching radius for the main shock and the precursory events because Yunnan is an active region with damage earthquakes and moderate and small earthquakes. However, there is a strong correlation between the main shock moment and the coefficientk/m. The “optimal fitting range“ for the forecasting time and magnitude can be further reduced using the relation between the main shock moment lgM 0 and the coefficientlgk/m and the value range of the restricting indexm, by which the forecast precision of the simulated main shock can be improved. The time-to-failure method is used to fit 30 main shocks in the paper and more than 80% of them have acquired better results, indicating that the method is prospective for its ability to forecast the known main shock sequence. Therefore, the prospect is cheerful to make medium-short term forecast for the forthcoming main shocks by the precursory events.

The principle of middle and long-term earthquake forecast model of spatial and temporal synthesized probability gain and the evaluation of forecast efficiency (R-values) of various forecast methods are introduced in this paper. The R-value method, developed by Xu (1989), is further developed here, and can be applied to more complicated cases. Probability gains in spatial and/or temporal domains and the R-values for different forecast methods are estimated in North China. The synthesized probability gain is then estimated as an example.

Calculation by means of the previous indices of the seismic activity can have the matter element analysis possess the forecast function. Readjusting repeatedly the grade limit value of every index can maximize the historical fitting ratio of the calculated and actual grade of the annual maximum magnitude, whose result is relatively ideal.

Gravity changes derived from regional gravity monitoring data in China from 1998 to 2005 exhibited noticeable variations before the occurrence of two large earthquakes in 2008 in China—the 2008 Yutian (Xinjiang)Ms=7.3earthquake and the 2008 Wenchuan (Sichuan)Ms=8.0earthquake. Based on these gravity variations, a group of researchers at the Second Crust Monitoring and Application Center of China Earthquake Administration made a suggestion in December of 2006 that the possibility for the Yutian (Xinjiang) and Wenchuan (Sichuan) areas to experience a large earthquake in either 2007 or 2008 was high. We review the gravity monitoring data and methods upon which the researchers reached these medium-term earthquake forecasts. Experience related to the medium-term forecasts of the Yutian and Wenchuan earthquakes suggests that gravity changes derived from regional gravity monitoring data could potentially be a useful medium-term precursor of large earthquakes, but significant additional research is needed to validate and evaluate this hypothesis.

Results published since the last three years on the observations of the precursor-like anomalies before the May 12, 2008, Wenchuan,Ms8.0 earthquake are collected and analyzed. These retrospective case studies would have provided heuristic clues about the preparation process of this inland great earthquake and the predictability of this destructive event if the standards for the rigorous test of earthquake forecast schemes were strictly observed. At least in some of these studies, however, several issues still need to be further examined to confirm or falsify the connection of the reported observations with the Wenchuan earthquake. Some of the problems are due to the inevitable limitation of observational infrastructure at the recent time, but some of the problems are due to the lack of communication about the test of earthquake forecast schemes. For the interdisciplinary studies on earthquake forecast, reminding of the latter issue seems of special importance for promoting the works and cooperation in this field.

The most used and accepted models for daily forecasts are based on short-term space and time earthquake clustering for occurrence rates and on the Gutenberg-Richter law for the frequency-magnitude. These models have been demonstrated to produce reliable prospective space-time-magnitude forecasts during an aftershock sequence, but their skill in forecasting mainshocks is still under discussion. This paper studies the foreshock statistics of the Italian and Californian seismicity in two ways: i) we compare the foreshock activity observed in real seismic catalogs and in synthetic catalogs derived from a pure Epidemic-Type Aftershock Sequence (ETAS) model; ii) we analyze the triggering capability of earthquakes using different ETAS parameterizations, in order to check whether large events are triggered in the same way as regular earthquakes. The results indicate that the foreshock activity observed in the real catalogs is compatible with what is expected by the ETAS model. Moreover, we find that the empirical foreshock rates have an intrinsic variability due to limited sampling that may explain most of the differences found so far in different seismic catalogs. Copyright © 2011 by the American Geophysical Union.

On 1 August 2009, the global Collaboratory for the Study of Earthquake Predictability (CSEP) launched a prospective and comparative earthquake predictability experiment in Italy. The goal of the CSEP-Italy experiment is to test earthquake occurrence hypotheses that have been formalized as probabilistic earthquake forecasts over temporal scales that range from days to years. In the first round of forecast submissions, members of the CSEP-Italy Working Group presented eighteen five-year and ten-year earthquake forecasts to the European CSEP Testing Center at ETH Zurich. We considered the twelve time-independent earthquake forecasts among this set and evaluated them with respect to past seismicity data from two Italian earthquake catalogs. In this article, we present the results of tests that measure the consistency of the forecasts with the past observations. Besides being an evaluation of the submitted time-independent forecasts, this exercise provided insight into a number of important issues in predictability experiments with regard to the specification of the forecasts, the performance of the tests, and the trade-off between the robustness of results and experiment duration. We conclude with suggestions for the future design of earthquake predictability experiments., 43 pages, 8 figures, 4 tables

We describe the setting up of the first earthquake forecasting experiment for Italy within the Collaboratory for the Study of Earthquake Predictability (CSEP). CSEP conducts rigorous and truly prospective forecast experiments for different tectonic environments in several forecast testing centers around the globe; forecasts are issued for a future period and also tested only against future observations to avoid any possible bias. As such, experiments need to be completely defined. This includes exact definitions of the testing area, of learning data for the forecast models, and of observation data against which forecasts will be tested to evaluate their performance. Here we present the rules, as taken from the Regional Earthquake Likelihood Models experiment and extended or changed for the Italian experiment. We also present characterizations of learning and observational catalogs that describe the completeness of these catalogs and illuminate inhomogeneities of magnitudes between these catalogs. A particular focus lies on the stability of earthquake recordings of the observational network. These catalog investigations provide guidance for CSEP modelers for developing earthquakes forecasts for submission to the forecast experiment in Italy. © 2010 by the Istituto Nazionale di Geofisica e Vulcanologia.

We describe the results of a prospective, real-time earthquake forecast experiment made during a seismic emergency. A Mw 6.3 earthquake struck the city of L'Aquila, Italy on April 6, 2009, causing hundreds of deaths and vast damage. Immediately following this event, we began producing daily earthquake forecasts for the region, and we provided these forecasts to Civil Protection - the agency responsible for managing the emergency. The forecasts are based on a stochastic model that combines the Gutenberg-Richter distribution of earthquake magnitudes and power-law decay in space and time of triggered earthquakes. The results from the first month following the L'Aquila earthquake exhibit a good fit between forecasts and observations, indicating that accurate earthquake forecasting is now a realistic goal. Our experience with this experiment demonstrates an urgent need for a connection between probabilistic forecasts and decision-making in order to establish - before crises - quantitative and transparent protocols for decision support. Copyright 2009 by the American Geophysical Union.

[1] The power law distribution of earthquake magnitudes and frequencies is a fundamental scaling relationship used for forecasting. However, can its slope (b value) be used on individual faults as a stress indicator? Some have concluded that b values drop just before large shocks. Others suggested that temporally stable low b value zones identify future large-earthquake locations. This study assesses the frequency of b value anomalies portending M ≥ 4.0 shocks versus how often they do not. I investigated M ≥ 4.0 Calaveras fault earthquakes because there have been 25 over the 37-year duration of the instrumental catalog on the most active southern half of the fault. With that relatively large sample, I conducted retrospective time and space earthquake forecasts. I calculated temporal b value changes in 5-km-radius cylindrical volumes of crust that were significant at 90% confidence, but these changes were poor forecasters of M ≥ 4.0 earthquakes. M ≥ 4.0 events were as likely to happen at times of high b values as they were at low ones. However, I could not rule out a hypothesis that spatial b value anomalies portend M ≥ 4.0 events; of 20 M ≥ 4 shocks that could be studied, 6 to 8 (depending on calculation method) occurred where b values were significantly less than the spatial mean, 1 to 2 happened above the mean, and 10 to 13 occurred within 90% confidence intervals of the mean and were thus inconclusive. Thus spatial b value variation might be a useful forecast tool, but resolution is poor, even on seismically active faults.

We present a RELM forecast of future earthquakes in California that is primarily based on the pattern informatics (PI) method. This method identifies regions that have systematic fluctuations in seismicity, and it has been demonstrated to be successful. A PI forecast map originally published on 19 February 2002 for southern California successfully forecast the locations of sixteen of eighteen M>5 earthquakes during the past three years. The method has also been successfully applied to Japan and on a worldwide basis. An alternative approach to earthquake forecasting is the relative intensity (RI) method. The RI forecast map is based on recent levels of seismic activity of small earthquakes. Recent advances in the PI method show considerable improvement, particularly when compared with the RI method using relative operating characteristic (ROC) diagrams for binary forecasts. The RELM application requires a probability for each location for a number of magnitude bins over a five year period. We have therefore constructed a hybrid forecast in which we combine the PI method with the RI method to compute a map of probabilities for events occurring at any location, rather than just the most probable locations. These probabilities are further converted, using Gutenberg-Richter scaling laws, to anticipated rates of future earthquakes that can be evaluated using the RELM test., 6 pages, 4 figures (color), 1 table

Pure and Applied Geophysics, 163 (11-12), ISSN:0033-4553, ISSN:1420-9136, ISSN:1557-7368

(1) The Parkfield-Cholame section of the San Andreas fault, site of an unfulfilled earthquake forecast in 1985, is the best monitored section of the world's most closely watched fault. In 1983, the M = 6.5 Coalinga and M = 6.0 Nunez events struck 25 km northeast of Parkfield. Seismicity rates climbed for 18 months along the creeping section of the San Andreas north of Parkfield and dropped for 6 years along the locked section to the south. Right-lateral creep also slowed or reversed from Parkfield south. Here we calculate that the Coalinga sequence increased the shear and Coulomb stress on the creeping section, causing the rate of small shocks to rise until the added stress was shed by additional slip. However, the 1983 events decreased the shear and Coulomb stress on the Parkfield segment, causing surface creep and seismicity rates to drop. We use these observations to cast the likelihood of a Parkfield earthquake into an interaction-based probability, which includes both the renewal of stress following the 1966 Parkfield earthquake and the stress transfer from the 1983 Coalinga events. We calculate that the 1983 shocks dropped the 10-year probability of a M � 6 Parkfield earthquake by 22% (from 54 ± 22% to 42 ± 23%) and that the probability did not recover until about 1991, when seismicity and creep resumed. Our analysis may thus explain why the Parkfield earthquake did not strike in the 1980s, but not why it was absent in the 1990s. We calculate a 58 ± 17% probability of a M � 6 Parkfield earthquake during 2001- 2011. INDEX TERMS: 7223 Seismology: Seismic hazard assessment and prediction; 7230 Seismology: Seismicity and seismotectonics; 7260 Seismology: Theory and modeling; KEYWORDS: Coalinga earthquake, Parkfield, stress change, earthquake probability, seismicity rate

Estimates of the frequency of destructive shocks in California have usually been based on the very imperfect historical record. The present note attempts to revise these estimates by statistical comparison of earthquake frequency in California with that of the world as a whole.

The evaluation of any earthquake forecast hypothesis requires the application of rigorous statistical methods. It implies a univocal definition of the model characterising the concerned anomaly or precursor, so as it can be objectively recognised in any circumstance and by any observer.A valid forecast hypothesis is expected to maximise successes and minimise false alarms. The probability gain associated to a precursor is also a popular way to estimate the quality of the predictions based on such precursor. Some scientists make use of a statistical approach based on the computation of the likelihood of an observed realisation of seismic events, and on the comparison of the likelihood obtained under different hypotheses. This method can be extended to algorithms that allow the computation of the density distribution of the conditional probability of earthquake occurrence in space, time and magnitude. Whatever method is chosen for building up a new hypothesis, the final assessment of its validity should be carried out by a test on a new and independent set of observations. The implementation of this test could, however, be problematic for seismicity characterised by long-term recurrence intervals. Even using the historical record, that may span time windows extremely variable between a few centuries to a few millennia, we have a low probability to catch more than one or two events on the same fault. Extending the record of earthquakes of the past back in time up to several millennia, paleoseismology represents a great opportunity to study how earthquakes recur through time and thus provide innovative contributions to time-dependent seismic hazard assessment. Sets of paleoseimologically dated earthquakes have been established for some faults in the Mediterranean area: the Irpinia fault in Southern Italy, the Fucino fault in Central Italy, the El Asnam fault in Algeria and the Skinos fault in Central Greece. By using the age of the paleoearthquakes with their associated uncertainty we have computed, through a Montecarlo procedure, the probability that the observed inter-event times come from a uniform random distribution (null hypothesis). This probability is estimated approximately equal to 8.4% for the Irpinia fault, 0.5% for the Fucino fault, 49% for the El Asnam fault and 42% for the Skinos fault. So, the null Poisson hypothesis can be rejected with a confidence level of 99.5% for the Fucino fault, but it can be rejected only with a confidence level between 90% and 95% for the Irpinia fault, while it cannot be rejected for the other two cases. As discussed in the last section of this paper, whatever the scientific value of any prediction hypothesis, it should be considered effective only after evaluation of the balance between the costs and benefits introduced by its practical implementation.