Smoothed Seismicity Models Research Articles

Development of smoothed seismicity models for seismic hazard assessment in the Red Sea region

The Red Sea region, situated between the Arabian and African Plates, experiences significant seismic activity due to its tectonic dynamics, with earthquakes ranging from minor to potentially destructive events. This study aims to develop smoothed seismicity models for the region by using an enhanced seismic catalog specific to the Red Sea. This facilitates a detailed spatial and temporal analysis of seismic events, focusing on seismic source characterization essential for probabilistic seismic hazard assessments. A rigorous declustering method excludes foreshocks and aftershocks, focusing on independent seismic events. The analysis uses a spatial grid (0.1∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{\\circ }$$\\end{document} cells in latitude and longitude) to determine seismic event rates, which are then refined using various smoothing techniques. Special attention is given to seismic activity within 0–35 kms of depth, leading to distinct rate models that inform urban development and seismic hazard mitigation strategies in the Red Sea area. These models are crucial for improving resilience, safety, and informed decision-making for urban planning and disaster preparedness, addressing the challenges posed by the region’s tectonic and seismic complexities.

Accounting for the Variability of Earthquake Rates within Low-Seismicity Regions: Application to the 2022 Aotearoa New Zealand National Seismic Hazard Model

ABSTRACT The distribution of earthquakes in time and space is seldom stationary, which could hinder a robust statistical analysis, particularly in low-seismicity regions with limited data. This work investigates the performance of stationary Poisson and spatially precise forecasts, such as smoothed seismicity models (SSMs), in terms of the available training data. Catalog bootstrap experiments are conducted to: (1) identify the number of training data necessary for SSMs to perform spatially better than the least-informative Uniform Rate Zone (URZ) models; and (2) describe the rate temporal variability accounting for the overdispersion and nonstationarity of seismicity. Formally, the strict-stationarity assumption used in traditional forecasts is relaxed into local and incremental stationarity (i.e., a catalog is only stationary in the vicinity of a given time point t) along with self-similar behavior described by a power law. The results reveal rate dispersion up to 10 times higher than predicted by Poisson models and highlight the impact of nonstationarity in assuming a constant mean rate within training-forecast intervals. The temporal rate variability is translated into a reduction of spatial precision by means of URZ models. First, counting processes are devised to capture rate distributions, considering the rate as a random variable. Second, we devise a data-driven method based on geodetic strain rate to spatially delimit the precision of URZs, assuming that strain/stress rate is related to the timescales of earthquake interactions. Finally, rate distributions are inferred from the available data within each URZ. We provide forecasts for the New Zealand National Seismic Hazard Model update, which can exhibit rates up to ten times higher in low-seismicity regions compared with SSMs. This study highlights the need to consider nonstationarity in seismicity models and underscores the importance of appropriate statistical descriptions of rate variability in probabilistic seismic hazard analysis.

A New Smoothed Seismicity Approach to Include Aftershocks and Foreshocks in Spatial Earthquake Forecasting: Application to the Global Mw ≥ 5.5 Seismicity

Seismicity-based earthquake forecasting models have been primarily studied and developed over the past twenty years. These models mainly rely on seismicity catalogs as their data source and provide forecasts in time, space, and magnitude in a quantifiable manner. In this study, we presented a technique to better determine future earthquakes in space based on spatially smoothed seismicity. The improvement’s main objective is to use foreshock and aftershock events together with their mainshocks. Time-independent earthquake forecast models are often developed using declustered catalogs, where smaller-magnitude events regarding their mainshocks are removed from the catalog. Declustered catalogs are required in the probabilistic seismic hazard analysis (PSHA) to hold the Poisson assumption that the events are independent in time and space. However, as highlighted and presented by many recent studies, removing such events from seismic catalogs may lead to underestimating seismicity rates and, consequently, the final seismic hazard in terms of ground shaking. Our study also demonstrated that considering the complete catalog may improve future earthquakes’ spatial forecast. To do so, we adopted two different smoothed seismicity methods: (1) the fixed smoothing method, which uses spatially uniform smoothing parameters, and (2) the adaptive smoothing method, which relates an individual smoothing distance for each earthquake. The smoothed seismicity models are constructed by using the global earthquake catalog with Mw ≥ 5.5 events. We reported progress on comparing smoothed seismicity models developed by calculating and evaluating the joint log-likelihoods. Our resulting forecast shows a significant information gain concerning both fixed and adaptive smoothing model forecasts. Our findings indicate that complete catalogs are a notable feature for increasing the spatial variation skill of seismicity forecasts.

Application of an ensemble earthquake rate model in Italy, considering seismic catalogs and fault moment release

We develop an ensemble earthquake rate model that provides spatially variable time-independent (Poisson) long-term annual occurrence rates of seismic events throughout Italy, for magnitude bin of 0.1 units from Mw ≥ 4.5 in spatial cells of 0.1° × 0.1°. We weighed seismic activity rates of smoothed seismicity and fault-based inputs to build our earthquake rupture forecast model, merging it into a single ensemble model. Both inputs adopt a tapered Gutenberg-Richter relation with a single b-value and a single corner magnitude estimated by earthquakes catalog. The spatial smoothed seismicity was obtained using the classical kernel smoothing method with the inclusion of magnitude dependent completeness periods applied to the Historical (CPTI15) and Instrumental seismic catalogs. For each seismogenic source provided by the Database of the Individual Seismogenic Sources (DISS), we computed the annual rate of the events above Mw 4.5, assuming that the seismic moments of the earthquakes generated by each fault are distributed according to the tapered Gutenberg-Richter relation with the same parameters of the smoothed seismicity models. Comparing seismic annual rates of the catalogs with those of the seismogenic sources, we realized that there is a good agreement between these rates in Central Apennines zones, whereas the seismogenic rates are higher than those of the catalogs in the north east and south of Italy. We also tested our model against the strong Italian earthquakes (Mw 5.5+), in order to check if the total number (N-test) and the spatial distribution (S-test) of these events was compatible with our model, obtaining good results, i.e. high p-values in the test. The final model will be a branch of the new Italian seismic hazard map.

Forecasting the Rates of Future Aftershocks of All Generations Is Essential to Develop Better Earthquake Forecast Models

AbstractCurrently, one of the best performing earthquake forecasting models relies on the working hypothesis that the “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 combinations of three target magnitude thresholds: 2.95, 3.95, or 4.95 and two forecasting time horizons: 1 or 5 years. In these experiments, we compare the performance of (1) the ETAS model with spatially homogenous parameters, or GETAS; (2) the 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 the 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 stronger improvements in forecasting performance.

Probabilistic seismic hazard assessment using spatially smoothed seismicity in North China seismic zone

In this study, we use a spatially smoothed seismicity procedure for seismic hazard analysis in North China seismic zone by establishing four spatially smoothed seismicity models according to the seismic catalogs of North China and calculating peak ground acceleration (PGA) values with 10% probability of exceedance in 50 years. The results show considerable differences between seismic hazards based on different models in certain areas, which is attributable to disparities in the seismicity levels of the four seismic models in those areas. In general, seismic hazard based on different models can be used as reference to evaluate uncertainty. In this paper, we also compare the mean PGA based on four spatially smoothed seismicity models with another PGA calculated using the zoning method based on surface seismic sources adopted for generating the Seismic Ground Motion Parameter Zonation Map of China, and find that the results of the two methods are largely similar, both of which can reflect the seismic hazard level of North China. However, there are differences at certain points, which are because the zoning approach adopts the same earthquake occurrence rate in the seismic source, while the spatially smoothed seismicity approach has different occurrence rates at different points. The discrepancies between the two can be attributed to differences in the principles adopted when potential seismic sources are classified. In particular, the PGA values of Beijing with 10% probability of exceedance in 50 years is 177.0cm/s2, 214.2 cm/s2, 252.8 cm/s2, and 187.5 cm/s2 in four spatial seismicity models, respectively. These PGA values are very important for evaluating the uncertainty of seismic hazard in Beijing. This study is an attempt to perform seismic hazard analysis using spatially smoothed seismicity models in China and recommends using this approach for areas where seismic sources are not clearly identified.

Highlights from the First Ten Years of the New Zealand Earthquake Forecast Testing Center

Research Article| June 13, 2018 Highlights from the First Ten Years of the New Zealand Earthquake Forecast Testing Center David A. Rhoades; David A. Rhoades aGNS Science, 1 Fairway Drive, Avalon, Lower Hutt 5010, New Zealand, d.rhoades@gns.cri.nz Search for other works by this author on: GSW Google Scholar Annemarie Christophersen; Annemarie Christophersen aGNS Science, 1 Fairway Drive, Avalon, Lower Hutt 5010, New Zealand, d.rhoades@gns.cri.nz Search for other works by this author on: GSW Google Scholar Matthew C. Gerstenberger; Matthew C. Gerstenberger aGNS Science, 1 Fairway Drive, Avalon, Lower Hutt 5010, New Zealand, d.rhoades@gns.cri.nz Search for other works by this author on: GSW Google Scholar Maria Liukis; Maria Liukis bJet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, California 91109 U.S.A. Search for other works by this author on: GSW Google Scholar Fabio Silva; Fabio Silva cSouthern California Earthquake Center, University of Southern California, 3651 Trousdale Parkway, Los Angeles, California 90089‐0742 U.S.A. Search for other works by this author on: GSW Google Scholar Warner Marzocchi; Warner Marzocchi dIstituto Nazionale di Geofisica e Vulcanologia, Via di Vigna Murata 605, 00143 Rome, Italy Search for other works by this author on: GSW Google Scholar Maximilian J. Werner; Maximilian J. Werner eUniversity of Bristol, Tyndall Avenue, Bristol BS8 1TH, United Kingdom Search for other works by this author on: GSW Google Scholar Thomas H. Jordan Thomas H. Jordan cSouthern California Earthquake Center, University of Southern California, 3651 Trousdale Parkway, Los Angeles, California 90089‐0742 U.S.A. Search for other works by this author on: GSW Google Scholar Author and Article Information David A. Rhoades aGNS Science, 1 Fairway Drive, Avalon, Lower Hutt 5010, New Zealand, d.rhoades@gns.cri.nz Annemarie Christophersen aGNS Science, 1 Fairway Drive, Avalon, Lower Hutt 5010, New Zealand, d.rhoades@gns.cri.nz Matthew C. Gerstenberger aGNS Science, 1 Fairway Drive, Avalon, Lower Hutt 5010, New Zealand, d.rhoades@gns.cri.nz Maria Liukis bJet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, California 91109 U.S.A. Fabio Silva cSouthern California Earthquake Center, University of Southern California, 3651 Trousdale Parkway, Los Angeles, California 90089‐0742 U.S.A. Warner Marzocchi dIstituto Nazionale di Geofisica e Vulcanologia, Via di Vigna Murata 605, 00143 Rome, Italy Maximilian J. Werner eUniversity of Bristol, Tyndall Avenue, Bristol BS8 1TH, United Kingdom Thomas H. Jordan cSouthern California Earthquake Center, University of Southern California, 3651 Trousdale Parkway, Los Angeles, California 90089‐0742 U.S.A. Publisher: Seismological Society of America First Online: 13 Jun 2018 Online Issn: 1938-2057 Print Issn: 0895-0695 © Seismological Society of America Seismological Research Letters (2018) 89 (4): 1229–1237. https://doi.org/10.1785/0220180032 Article history First Online: 13 Jun 2018 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation David A. Rhoades, Annemarie Christophersen, Matthew C. Gerstenberger, Maria Liukis, Fabio Silva, Warner Marzocchi, Maximilian J. Werner, Thomas H. Jordan; Highlights from the First Ten Years of the New Zealand Earthquake Forecast Testing Center. Seismological Research Letters 2018;; 89 (4): 1229–1237. doi: https://doi.org/10.1785/0220180032 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietySeismological Research Letters Search Advanced Search ABSTRACT 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. 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Ensemble Smoothed Seismicity Models for the New Italian Probabilistic Seismic Hazard Map

Ensemble Smoothed Seismicity Models for the New Italian Probabilistic Seismic Hazard Map

Likelihood testing of seismicity‐based rate forecasts of induced earthquakes in Oklahoma and Kansas

AbstractLikelihood testing of induced earthquakes in Oklahoma and Kansas has identified the parameters that optimize the forecasting ability of smoothed seismicity models and quantified the recent temporal stability of the spatial seismicity patterns. Use of the most recent 1 year period of earthquake data and use of 10–20 km smoothing distances produced the greatest likelihood. The likelihood that the locations of January–June 2015 earthquakes were consistent with optimized forecasts decayed with increasing elapsed time between the catalogs used for model development and testing. Likelihood tests with two additional sets of earthquakes from 2014 exhibit a strong sensitivity of the rate of decay to the smoothing distance. Marked reductions in likelihood are caused by the nonstationarity of the induced earthquake locations. Our results indicate a multiple‐fold benefit from smoothed seismicity models in developing short‐term earthquake rate forecasts for induced earthquakes in Oklahoma and Kansas, relative to the use of seismic source zones.

Seismic Source Characterization for the 2014 Update of the U.S. National Seismic Hazard Model

We present the updated seismic source characterization (SSC) for the 2014 update of the National Seismic Hazard Model (NSHM) for the conterminous United States. Construction of the seismic source models employs the methodology that was developed for the 1996 NSHM but includes new and updated data, data types, source models, and source parameters that reflect the current state of knowledge of earthquake occurrence and state of practice for seismic hazard analyses. We review the SSC parameterization and describe the methods used to estimate earthquake rates, magnitudes, locations, and geometries for all seismic source models, with an emphasis on new source model components. We highlight the effects that two new model components—incorporation of slip rates from combined geodetic-geologic inversions and the incorporation of adaptively smoothed seismicity models—have on probabilistic ground motions, because these sources span multiple regions of the conterminous United States and provide important additional epistemic uncertainty for the 2014 NSHM.

A Long-Term Earthquake Rate Model for the Central and Eastern United States from Smoothed Seismicity

Abstract I present a long-term earthquake rate model for the central and eastern United States from adaptive smoothed seismicity. By employing pseudoprospective likelihood testing (L-test), I examined the effects of fixed and adaptive smoothing methods and the effects of catalog duration and composition on the ability of the models to forecast the spatial distribution of recent earthquakes. To stabilize the adaptive smoothing method for regions of low seismicity, I introduced minor modifications to the way that the adaptive smoothing distances are calculated. Across all smoothed seismicity models, the use of adaptive smoothing and the use of earthquakes from the recent part of the catalog optimizes the likelihood for tests with M ≥2.7 and M ≥4.0 earthquake catalogs. The smoothed seismicity models optimized by likelihood testing with M ≥2.7 catalogs also produce the highest likelihood values for M ≥4.0 likelihood testing, thus substantiating the hypothesis that the locations of moderate-size earthquakes can be forecast by the locations of smaller earthquakes. The likelihood test does not, however, maximize the fraction of earthquakes that are better forecast than a seismicity rate model with uniform rates in all cells. In this regard, fixed smoothing models perform better than adaptive smoothing models. The preferred model of this study is the adaptive smoothed seismicity model, based on its ability to maximize the joint likelihood of predicting the locations of recent small-to-moderate-size earthquakes across eastern North America. The preferred rate model delineates 12 regions where the annual rate of M ≥5 earthquakes exceeds 2×10 −3 . Although these seismic regions have been previously recognized, the preferred forecasts are more spatially concentrated than the rates from fixed smoothed seismicity models, with rate increases of up to a factor of 10 near clusters of high seismic activity. Online Material: Figures of minimum-magnitude determination, b -value estimation, and maps of earthquake rate and forecasts, and tables of optimized neighbor numbers and smoothing distances.

Spatial sensitivity of seismic hazard results to different background seismic activity and temporal earthquake occurrence models

Spatial sensitivity of seismic hazard results to different models with respect to background seismic activity and earthquake occurrence in time is investigated. For the contribution of background seismic activity to seismic hazard, background area source with uniform seismicity and spatially smoothed seismicity models are taken into consideration. For the contribution of faults, through characteristic earthquakes, both the memoryless Poisson and the time dependent renewal models are utilized. A case study, involving the assessment of seismic hazard for the Bursa province in Turkey, is conducted in order to examine quantitatively the influence of these models on seismic hazard results. The spatial variation of the difference in Peak Ground Acceleration ( PGA) values obtained from these different models is presented in the form of difference maps for return periods of 475 and 2475 years. Best estimate seismic hazard maps for PGA and Spectral Accelerations (SA) at 0.2 and 1.0 s are obtained by using the logic tree method.

Earthquake forecast models for Italy based on the RI algorithm

This study provides an overview of relative-intensity (RI)-based earthquake forecast models that have been submitted for the 5-year and 10-year testing classes and the 3-month class of the Italian experiment within the Collaboratory for the Study of Earthquake Predictability (CSEP). The RI algorithm starts as a binary forecast system based on the working assumption that future large earthquakes are considered likely to occur at sites of higher seismic activity in the past. The measure of RI is the simply counting of the number of past earthquakes, which is known as the RI of seismicity. To improve the RI forecast performance, we first expand the RI algorithm to become part of a general class of smoothed seismicity models. We then convert the RI representation from a binary system into a testable CSEP model that forecasts the numbers of earthquakes for the predefined magnitudes. Our parameter tuning for the CSEP models is based on the past seismicity. The final submission is a set of two numerical data files that were created by tuned 5-year and 10-year models and an executable computer code of a tuned 3-month model, to examine which testing class is more meaningful in terms of the RI hypothesis. The main purpose of our participation is to better understand the importance (or lack of importance) of RI of seismicity for earthquake forecastability.