TY - JOUR A1 - Fiedler, Bernhard A1 - Hainzl, Sebastian A1 - Zöller, Gert A1 - Holschneider, Matthias T1 - Detection of Gutenberg-Richter b-Value Changes in Earthquake Time Series JF - Bulletin of the Seismological Society of America N2 - The Gutenberg-Richter relation for earthquake magnitudes is the most famous empirical law in seismology. It states that the frequency of earthquake magnitudes follows an exponential distribution; this has been found to be a robust feature of seismicity above the completeness magnitude, and it is independent of whether global, regional, or local seismicity is analyzed. However, the exponent b of the distribution varies significantly in space and time, which is important for process understanding and seismic hazard assessment; this is particularly true because of the fact that the Gutenberg-Richter b-value acts as a proxy for the stress state and quantifies the ratio of large-to-small earthquakes. In our work, we focus on the automatic detection of statistically significant temporal changes of the b-value in seismicity data. In our approach, we use Bayes factors for model selection and estimate multiple change-points of the frequency-magnitude distribution in time. The method is first applied to synthetic data, showing its capability to detect change-points as function of the size of the sample and the b-value contrast. Finally, we apply this approach to examples of observational data sets for which b-value changes have previously been stated. Our analysis of foreshock and after-shock sequences related to mainshocks, as well as earthquake swarms, shows that only a portion of the b-value changes is statistically significant. Y1 - 2018 U6 - https://doi.org/10.1785/0120180091 SN - 0037-1106 SN - 1943-3573 VL - 108 IS - 5A SP - 2778 EP - 2787 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Salamat, Mona A1 - Zöller, Gert A1 - Zare, Mehdi A1 - Amini, Mortaza T1 - The maximum expected earthquake magnitudes in different future time intervals of six seismotectonic zones of Iran and its surroundings JF - Journal of seismology N2 - One of the crucial components in seismic hazard analysis is the estimation of the maximum earthquake magnitude and associated uncertainty. In the present study, the uncertainty related to the maximum expected magnitude mu is determined in terms of confidence intervals for an imposed level of confidence. Previous work by Salamat et al. (Pure Appl Geophys 174:763-777, 2017) shows the divergence of the confidence interval of the maximum possible magnitude m(max) for high levels of confidence in six seismotectonic zones of Iran. In this work, the maximum expected earthquake magnitude mu is calculated in a predefined finite time interval and imposed level of confidence. For this, we use a conceptual model based on a doubly truncated Gutenberg-Richter law for magnitudes with constant b-value and calculate the posterior distribution of mu for the time interval T-f in future. We assume a stationary Poisson process in time and a Gutenberg-Richter relation for magnitudes. The upper bound of the magnitude confidence interval is calculated for different time intervals of 30, 50, and 100 years and imposed levels of confidence alpha = 0.5, 0.1, 0.05, and 0.01. The posterior distribution of waiting times T-f to the next earthquake with a given magnitude equal to 6.5, 7.0, and7.5 are calculated in each zone. In order to find the influence of declustering, we use the original and declustered version of the catalog. The earthquake catalog of the territory of Iran and surroundings are subdivided into six seismotectonic zones Alborz, Azerbaijan, Central Iran, Zagros, Kopet Dagh, and Makran. We assume the maximum possible magnitude m(max) = 8.5 and calculate the upper bound of the confidence interval of mu in each zone. The results indicate that for short time intervals equal to 30 and 50 years and imposed levels of confidence 1 - alpha = 0.95 and 0.90, the probability distribution of mu is around mu = 7.16-8.23 in all seismic zones. KW - Maximum expected earthquake magnitude KW - Future time interval KW - Level of confidence KW - Iran Y1 - 2018 U6 - https://doi.org/10.1007/s10950-018-9780-7 SN - 1383-4649 SN - 1573-157X VL - 22 IS - 6 SP - 1485 EP - 1498 PB - Springer CY - Dordrecht ER - TY - GEN A1 - Zöller, Gert T1 - Comment on "Estimation of Earthquake Hazard Parameters from Incomplete Data Files. Part III. Incorporation of Uncertainty of Earthquake-Occurrence Model" by Andrzej Kijko, Ansie Smit, and Markvard A. Sellevoll T2 - Bulletin of the Seismological Society of America N2 - Kijko et al. (2016) present various methods to estimate parameters that are relevant for probabilistic seismic-hazard assessment. One of these parameters, although not the most influential, is the maximum possible earthquake magnitude m(max). I show that the proposed estimation of m(max) is based on an erroneous equation related to a misuse of the estimator in Cooke (1979) and leads to unstable results. So far, reported finite estimations of m(max) arise from data selection, because the estimator in Kijko et al. (2016) diverges with finite probability. This finding is independent of the assumed distribution of earthquake magnitudes. For the specific choice of the doubly truncated Gutenberg-Richter distribution, I illustrate the problems by deriving explicit equations. Finally, I conclude that point estimators are generally not a suitable approach to constrain m(max). Y1 - 2017 U6 - https://doi.org/10.1785/0120160193 SN - 0037-1106 SN - 1943-3573 VL - 107 SP - 1975 EP - 1978 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Shcherbakov, Robert A1 - Zhuang, Jiancang A1 - Zöller, Gert A1 - Ogata, Yosihiko T1 - Forecasting the magnitude of the largest expected earthquake JF - Nature Communications N2 - The majority of earthquakes occur unexpectedly and can trigger subsequent sequences of events that can culminate in more powerful earthquakes. This self-exciting nature of seismicity generates complex clustering of earthquakes in space and time. Therefore, the problem of constraining the magnitude of the largest expected earthquake during a future time interval is of critical importance in mitigating earthquake hazard. We address this problem by developing a methodology to compute the probabilities for such extreme earthquakes to be above certain magnitudes. We combine the Bayesian methods with the extreme value theory and assume that the occurrence of earthquakes can be described by the Epidemic Type Aftershock Sequence process. We analyze in detail the application of this methodology to the 2016 Kumamoto, Japan, earthquake sequence. We are able to estimate retrospectively the probabilities of having large subsequent earthquakes during several stages of the evolution of this sequence. Y1 - 2019 U6 - https://doi.org/10.1038/s41467-019-11958-4 SN - 2041-1723 VL - 10 PB - Nature Publishing Group CY - London ER - TY - JOUR A1 - Salamat, Mona A1 - Zöller, Gert A1 - Amini, Morteza T1 - Prediction of the Maximum Expected Earthquake Magnitude in Iran: BT - from a Catalog with Varying Magnitude of Completeness and Uncertain Magnitudes JF - Pure and applied geophysics N2 - This paper concerns the problem of predicting the maximum expected earthquake magnitude μ in a future time interval Tf given a catalog covering a time period T in the past. Different studies show the divergence of the confidence interval of the maximum possible earthquake magnitude m_{ max } for high levels of confidence (Salamat et al. 2017). Therefore, m_{ max } should be better replaced by μ (Holschneider et al. 2011). In a previous study (Salamat et al. 2018), μ is estimated for an instrumental earthquake catalog of Iran from 1900 onwards with a constant level of completeness ( {m0 = 5.5} ). In the current study, the Bayesian methodology developed by Zöller et al. (2014, 2015) is applied for the purpose of predicting μ based on the catalog consisting of both historical and instrumental parts. The catalog is first subdivided into six subcatalogs corresponding to six seismotectonic zones, and each of those zone catalogs is subsequently subdivided according to changes in completeness level and magnitude uncertainty. For this, broad and small error distributions are considered for historical and instrumental earthquakes, respectively. We assume that earthquakes follow a Poisson process in time and Gutenberg-Richter law in the magnitude domain with a priori unknown a and b values which are first estimated by Bayes' theorem and subsequently used to estimate μ. Imposing different values of m_{ max } for different seismotectonic zones namely Alborz, Azerbaijan, Central Iran, Zagros, Kopet Dagh and Makran, the results show considerable probabilities for the occurrence of earthquakes with Mw ≥ 7.5 in short Tf , whereas for long Tf, μ is almost equal to m_{ max } KW - Maximum expected earthquake magnitude KW - completeness levels KW - magnitude errors KW - Bayesian method KW - Iran Y1 - 2019 U6 - https://doi.org/10.1007/s00024-019-02141-3 SN - 0033-4553 SN - 1420-9136 VL - 176 IS - 8 SP - 3425 EP - 3438 PB - Springer CY - Basel ER - TY - JOUR A1 - Hainzl, Sebastian A1 - Zöller, Gert A1 - Main, Ian T1 - Introduction to special issue: Dynamics of seismicity patterns and earthquake triggering - Preface JF - Tectonophysics : international journal of geotectonics and the geology and physics of the interior of the earth Y1 - 2006 U6 - https://doi.org/10.1016/j.tecto.2006.03.034 SN - 0040-1951 SN - 1879-3266 VL - 424 IS - Special issue SP - 135 EP - 138 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Zöller, Gert T1 - A note on the estimation of the maximum possible earthquake magnitude based on extreme value theory for the Groningen Gas Field JF - The bulletin of the Seismological Society of America : BSSA N2 - Extreme value statistics is a popular and frequently used tool to model the occurrence of large earthquakes. The problem of poor statistics arising from rare events is addressed by taking advantage of the validity of general statistical properties in asymptotic regimes. In this note, I argue that the use of extreme value statistics for the purpose of practically modeling the tail of the frequency-magnitude distribution of earthquakes can produce biased and thus misleading results because it is unknown to what degree the tail of the true distribution is sampled by data. Using synthetic data allows to quantify this bias in detail. The implicit assumption that the true M-max is close to the maximum observed magnitude M-max,M-observed restricts the class of the potential models a priori to those with M-max = M-max,M-observed + Delta M with an increment Delta M approximate to 0.5... 1.2. This corresponds to the simple heuristic method suggested by Wheeler (2009) and labeled :M-max equals M-obs plus an increment." The incomplete consideration of the entire model family for the frequency-magnitude distribution neglects, however, the scenario of a large so far unobserved earthquake. Y1 - 2022 U6 - https://doi.org/10.1785/0120210307 SN - 0037-1106 SN - 1943-3573 VL - 112 IS - 4 SP - 1825 EP - 1831 PB - Seismological Society of America CY - El Cerito, Calif. ER - TY - GEN A1 - Zöller, Gert A1 - Holschneider, Matthias T1 - Reply to “Comment on ‘The Maximum Possible and the Maximum Expected Earthquake Magnitude for Production‐Induced Earthquakes at the Gas Field in Groningen, The Netherlands’ by Gert Zöller and Matthias Holschneider” by Mathias Raschke T2 - Bulletin of the Seismological Society of America Y1 - 2018 U6 - https://doi.org/10.1785/0120170131 SN - 0037-1106 SN - 1943-3573 VL - 108 IS - 2 SP - 1029 EP - 1030 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Zoller, Gert A1 - Holschneider, Matthias A1 - Ben-Zion, Yehuda T1 - The role of heterogeneities as a tuning parameter of earthquake dynamics N2 - We investigate the influence of spatial heterogeneities on various aspects of brittle failure and seismicity in a model of a large strike-slip fault. The model dynamics is governed by realistic boundary conditions consisting of constant velocity motion of regions around the fault, static/kinetic friction laws, creep with depth-dependent coefficients, and 3-D elastic stress transfer. The dynamic rupture is approximated on a continuous time scale using a finite stress propagation velocity ("quasidynamic model''). The model produces a "brittle- ductile'' transition at a depth of about 12.5 km, realistic hypocenter distributions, and other features of seismicity compatible with observations. Previous work suggested that the range of size scales in the distribution of strength-stress heterogeneities acts as a tuning parameter of the dynamics. Here we test this hypothesis by performing a systematic parameter-space study with different forms of heterogeneities. In particular, we analyze spatial heterogeneities that can be tuned by a single parameter in two distributions: ( 1) high stress drop barriers in near- vertical directions and ( 2) spatial heterogeneities with fractal properties and variable fractal dimension. The results indicate that the first form of heterogeneities provides an effective means of tuning the behavior while the second does not. In relatively homogeneous cases, the fault self-organizes to large-scale patches and big events are associated with inward failure of individual patches and sequential failures of different patches. The frequency-size event statistics in such cases are compatible with the characteristic earthquake distribution and large events are quasi-periodic in time. In strongly heterogeneous or near-critical cases, the rupture histories are highly discontinuous and consist of complex migration patterns of slip on the fault. In such cases, the frequency-size and temporal statistics follow approximately power-law relations Y1 - 2005 SN - 0033-4553 ER - TY - JOUR A1 - Zoller, Gert A1 - Hainzl, Sebastian A1 - Holschneider, Matthias A1 - Ben-Zion, Yehuda T1 - Aftershocks resulting from creeping sections in a heterogeneous fault N2 - We show that realistic aftershock sequences with space-time characteristics compatible with observations are generated by a model consisting of brittle fault segments separated by creeping zones. The dynamics of the brittle regions is governed by static/kinetic friction, 3D elastic stress transfer and small creep deformation. The creeping parts are characterized by high ongoing creep velocities. These regions store stress during earthquake failures and then release it in the interseismic periods. The resulting postseismic deformation leads to aftershock sequences following the modified Omori law. The ratio of creep coefficients in the brittle and creeping sections determines the duration of the postseismic transients and the exponent p of the modified Omori law Y1 - 2005 SN - 0094-8276 ER - TY - JOUR A1 - Zoller, Gert A1 - Holschneider, Matthias A1 - Ben-Zion, Yehuda T1 - Quasi-static and quasi-dynamic modeling of earthquake failure at intermediate scales N2 - We present a model for earthquake failure at intermediate scales (space: 100 m-100 km, time: 100 m/nu(shear Y1 - 2004 ER - TY - THES A1 - Zöller, Gert T1 - Critical states of seismicity : modeling and data analysis T1 - Kritische Zustände seismischer Dynamik : Modellierung und Datenanalyse N2 - The occurrence of earthquakes is characterized by a high degree of spatiotemporal complexity. Although numerous patterns, e.g. fore- and aftershock sequences, are well-known, the underlying mechanisms are not observable and thus not understood. Because the recurrence times of large earthquakes are usually decades or centuries, the number of such events in corresponding data sets is too small to draw conclusions with reasonable statistical significance. Therefore, the present study combines both, numerical modeling and analysis of real data in order to unveil the relationships between physical mechanisms and observational quantities. The key hypothesis is the validity of the so-called "critical point concept" for earthquakes, which assumes large earthquakes to occur as phase transitions in a spatially extended many-particle system, similar to percolation models. New concepts are developed to detect critical states in simulated and in natural data sets. The results indicate that important features of seismicity like the frequency-size distribution and the temporal clustering of earthquakes depend on frictional and structural fault parameters. In particular, the degree of quenched spatial disorder (the "roughness") of a fault zone determines whether large earthquakes occur quasiperiodically or more clustered. This illustrates the power of numerical models in order to identify regions in parameter space, which are relevant for natural seismicity. The critical point concept is verified for both, synthetic and natural seismicity, in terms of a critical state which precedes a large earthquake: a gradual roughening of the (unobservable) stress field leads to a scale-free (observable) frequency-size distribution. Furthermore, the growth of the spatial correlation length and the acceleration of the seismic energy release prior to large events is found. The predictive power of these precursors is, however, limited. Instead of forecasting time, location, and magnitude of individual events, a contribution to a broad multiparameter approach is encouraging. N2 - Das Auftreten von Erdbeben zeichnet sich durch eine hohe raumzeitliche Komplexität aus. Obwohl zahlreiche Muster, wie Vor- und Nachbeben bekannt sind, weiß man wenig über die zugrundeliegenden Mechanismen, da diese sich direkter Beobachtung entziehen. Die Zeit zwischen zwei starken Erdbeben in einer seismisch aktiven Region beträgt Jahrzehnte bis Jahrhunderte. Folglich ist die Anzahl solcher Ereignisse in einem Datensatz gering und es ist kaum möglich, allein aus Beobachtungsdaten statistisch signifikante Aussagen über deren Eigenschaften abzuleiten. Die vorliegende Arbeit nutzt daher numerische Modellierungen einer Verwerfungszone in Verbindung mit Datenanalyse, um die Beziehung zwischen physikalischen Mechanismen und beobachteter Seismizität zu studieren. Die zentrale Hypothese ist die Gültigkeit des sogenannten "kritischen Punkt Konzeptes" für Seismizität, d.h. starke Erdbeben werden als Phasenübergänge in einem räumlich ausgedehnten Vielteilchensystem betrachtet, ähnlich wie in Modellen aus der statistischen Physik (z.B. Perkolationsmodelle). Es werden praktische Konzepte entwickelt, die es ermöglichen, kritische Zustände in simulierten und in beobachteten Daten sichtbar zu machen. Die Resultate zeigen, dass wesentliche Eigenschaften von Seismizität, etwa die Magnitudenverteilung und das raumzeitliche Clustern von Erdbeben, durch Reibungs- und Bruchparameter bestimmt werden. Insbesondere der Grad räumlicher Unordnung (die "Rauhheit") einer Verwerfungszone hat Einfluss darauf, ob starke Erdbeben quasiperiodisch oder eher zufällig auftreten. Dieser Befund zeigt auf, wie numerische Modelle genutzt werden können, um den Parameterraum für reale Verwerfungen einzugrenzen. Das kritische Punkt Konzept kann in synthetischer und in beobachteter Seismizität verifiziert werden. Dies artikuliert sich auch in Vorläuferphänomenen vor großen Erdbeben: Die Aufrauhung des (unbeobachtbaren) Spannungsfeldes führt zu einer Skalenfreiheit der (beobachtbaren) Größenverteilung; die räumliche Korrelationslänge wächst und die seismische Energiefreisetzung wird beschleunigt. Ein starkes Erdbeben kann in einem zusammenhängenden Bruch oder in einem unterbrochenen Bruch (Vorbeben und Hauptbeben) stattfinden. Die beobachtbaren Vorläufer besitzen eine begrenzte Prognosekraft für die Auftretenswahrscheinlichkeit starker Erdbeben - eine präzise Vorhersage von Ort, Zeit, und Stärke eines nahenden Erdbebens ist allerdings nicht möglich. Die genannten Parameter erscheinen eher vielversprechend als Beitrag zu einem umfassenden Multiparameteransatz für eine verbesserte zeitabhängige Gefährdungsabschätzung. KW - Seismizität KW - Erdbebenvorhersage KW - statistische Physik KW - mathematische Modellierung KW - Datenanalyse KW - seismicity KW - earthquake prediction KW - statistical physics KW - mathematical modeling KW - data analysis Y1 - 2005 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-7427 ER - TY - CHAP A1 - Hainzl, Sebastian A1 - Scherbaum, Frank A1 - Zöller, Gert T1 - Spatiotemporal earthquake patterns N2 - Interdisziplinäres Zentrum für Musterdynamik und Angewandte Fernerkundung Workshop vom 9. - 10. Februar 2006 Y1 - 2006 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-7267 N1 - [Poster] ER - TY - THES A1 - Zöller, Gert T1 - Analyse raumzeitlicher Muster in Erdbebendaten N2 - Die vorliegende Arbeit beschäftigt sich mit der Charakterisierung von Seismizität anhand von Erdbebenkatalogen. Es werden neue Verfahren der Datenanalyse entwickelt, die Aufschluss darüber geben sollen, ob der seismischen Dynamik ein stochastischer oder ein deterministischer Prozess zugrunde liegt und was daraus für die Vorhersagbarkeit starker Erdbeben folgt. Es wird gezeigt, dass seismisch aktive Regionen häufig durch nichtlinearen Determinismus gekennzeichent sind. Dies schließt zumindest die Möglichkeit einer Kurzzeitvorhersage ein. Das Auftreten seismischer Ruhe wird häufig als Vorläuferphaenomen für starke Erdbeben gedeutet. Es wird eine neue Methode präsentiert, die eine systematische raumzeitliche Kartierung seismischer Ruhephasen ermöglicht. Die statistische Signifikanz wird mit Hilfe des Konzeptes der Ersatzdaten bestimmt. Als Resultat erhält man deutliche Korrelationen zwischen seismischen Ruheperioden und starken Erdbeben. Gleichwohl ist die Signifikanz dafür nicht hoch genug, um eine Vorhersage im Sinne einer Aussage über den Ort, die Zeit und die Stärke eines zu erwartenden Hauptbebens zu ermöglichen. KW - Erdbeben KW - nichtlineare Dynamik Y1 - 1999 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-0000122 ER - TY - JOUR A1 - Salamat, Mona A1 - Zare, Mehdi A1 - Holschneider, Matthias A1 - Zöller, Gert T1 - Calculation of Confidence Intervals for the Maximum Magnitude of Earthquakes in Different Seismotectonic Zones of Iran JF - Pure and applied geophysics N2 - The problem of estimating the maximum possible earthquake magnitude m(max) has attracted growing attention in recent years. Due to sparse data, the role of uncertainties becomes crucial. In this work, we determine the uncertainties related to the maximum magnitude in terms of confidence intervals. Using an earthquake catalog of Iran, m(max) is estimated for different predefined levels of confidence in six seismotectonic zones. Assuming the doubly truncated Gutenberg-Richter distribution as a statistical model for earthquake magnitudes, confidence intervals for the maximum possible magnitude of earthquakes are calculated in each zone. While the lower limit of the confidence interval is the magnitude of the maximum observed event, the upper limit is calculated from the catalog and the statistical model. For this aim, we use the original catalog which no declustering methods applied on as well as a declustered version of the catalog. Based on the study by Holschneider et al. (Bull Seismol Soc Am 101(4): 1649-1659, 2011), the confidence interval for m(max) is frequently unbounded, especially if high levels of confidence are required. In this case, no information is gained from the data. Therefore, we elaborate for which settings finite confidence levels are obtained. In this work, Iran is divided into six seismotectonic zones, namely Alborz, Azerbaijan, Zagros, Makran, Kopet Dagh, Central Iran. Although calculations of the confidence interval in Central Iran and Zagros seismotectonic zones are relatively acceptable for meaningful levels of confidence, results in Kopet Dagh, Alborz, Azerbaijan and Makran are not that much promising. The results indicate that estimating mmax from an earthquake catalog for reasonable levels of confidence alone is almost impossible. KW - Maximum magnitude of earthquake KW - Level of confidence KW - Confidence interval Y1 - 2016 U6 - https://doi.org/10.1007/s00024-016-1418-5 SN - 0033-4553 SN - 1420-9136 VL - 174 SP - 763 EP - 777 PB - Springer CY - Basel ER - TY - JOUR A1 - Zöller, Gert T1 - A statistical model for earthquake recurrence based on the assimilation of paleoseismicity, historic seismicity, and instrumental seismicity JF - Journal of geophysical research : Solid earth N2 - Paleoearthquakes and historic earthquakes are the most important source of information for the estimation of long-term earthquake recurrence intervals in fault zones, because corresponding sequences cover more than one seismic cycle. However, these events are often rare, dating uncertainties are enormous, and missing or misinterpreted events lead to additional problems. In the present study, I assume that the time to the next major earthquake depends on the rate of small and intermediate events between the large ones in terms of a clock change model. Mathematically, this leads to a Brownian passage time distribution for recurrence intervals. I take advantage of an earlier finding that under certain assumptions the aperiodicity of this distribution can be related to the Gutenberg-Richter b value, which can be estimated easily from instrumental seismicity in the region under consideration. In this way, both parameters of the Brownian passage time distribution can be attributed with accessible seismological quantities. This allows to reduce the uncertainties in the estimation of the mean recurrence interval, especially for short paleoearthquake sequences and high dating errors. Using a Bayesian framework for parameter estimation results in a statistical model for earthquake recurrence intervals that assimilates in a simple way paleoearthquake sequences and instrumental data. I present illustrative case studies from Southern California and compare the method with the commonly used approach of exponentially distributed recurrence times based on a stationary Poisson process. KW - statistical seismology KW - paleoearthquakes KW - stochastic models KW - seismic hazard Y1 - 2018 U6 - https://doi.org/10.1029/2017JB015099 SN - 2169-9313 SN - 2169-9356 VL - 123 IS - 6 SP - 4906 EP - 4921 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Fiedler, Bernhard A1 - Zöller, Gert A1 - Holschneider, Matthias A1 - Hainzl, Sebastian T1 - Multiple Change-Point Detection in Spatiotemporal Seismicity Data JF - Bulletin of the Seismological Society of America N2 - Earthquake rates are driven by tectonic stress buildup, earthquake-induced stress changes, and transient aseismic processes. Although the origin of the first two sources is known, transient aseismic processes are more difficult to detect. However, the knowledge of the associated changes of the earthquake activity is of great interest, because it might help identify natural aseismic deformation patterns such as slow-slip events, as well as the occurrence of induced seismicity related to human activities. For this goal, we develop a Bayesian approach to identify change-points in seismicity data automatically. Using the Bayes factor, we select a suitable model, estimate possible change-points, and we additionally use a likelihood ratio test to calculate the significance of the change of the intensity. The approach is extended to spatiotemporal data to detect the area in which the changes occur. The method is first applied to synthetic data showing its capability to detect real change-points. Finally, we apply this approach to observational data from Oklahoma and observe statistical significant changes of seismicity in space and time. Y1 - 2018 U6 - https://doi.org/10.1785/0120170236 SN - 0037-1106 SN - 1943-3573 VL - 108 IS - 3A SP - 1147 EP - 1159 PB - Seismological Society of America CY - Albany ER - TY - GEN A1 - Wang, Lifeng A1 - Zöller, Gert A1 - Hainzl, Sebastian T1 - Joint determination of slip and stress drop in a Bayesian inversion approach: BT - a case study for the 2010 M8.8 Maule earthquake T2 - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe N2 - Stress drop is a key factor in earthquake mechanics and engineering seismology. However, stress drop calculations based on fault slip can be significantly biased, particularly due to subjectively determined smoothing conditions in the traditional least-square slip inversion. In this study, we introduce a mechanically constrained Bayesian approach to simultaneously invert for fault slip and stress drop based on geodetic measurements. A Gaussian distribution for stress drop is implemented in the inversion as a prior. We have done several synthetic tests to evaluate the stability and reliability of the inversion approach, considering different fault discretization, fault geometries, utilized datasets, and variability of the slip direction, respectively. We finally apply the approach to the 2010 M8.8 Maule earthquake and invert for the coseismic slip and stress drop simultaneously. Two fault geometries from the literature are tested. Our results indicate that the derived slip models based on both fault geometries are similar, showing major slip north of the hypocenter and relatively weak slip in the south, as indicated in the slip models of other studies. The derived mean stress drop is 5-6 MPa, which is close to the stress drop of similar to 7 MPa that was independently determined according to force balance in this region Luttrell et al. (J Geophys Res, 2011). These findings indicate that stress drop values can be consistently extracted from geodetic data. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 888 KW - stress drop KW - fault slip KW - Bayesian KW - geodetic measurements Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-435511 SN - 1866-8372 IS - 888 SP - 375 EP - 388 ER - TY - JOUR A1 - Schoppa, Lukas A1 - Sieg, Tobias A1 - Vogel, Kristin A1 - Zöller, Gert A1 - Kreibich, Heidi T1 - Probabilistic flood loss models for companies JF - Water resources research N2 - Flood loss modeling is a central component of flood risk analysis. Conventionally, this involves univariable and deterministic stage-damage functions. Recent advancements in the field promote the use of multivariable and probabilistic loss models, which consider variables beyond inundation depth and account for prediction uncertainty. Although companies contribute significantly to total loss figures, novel modeling approaches for companies are lacking. Scarce data and the heterogeneity among companies impede the development of company flood loss models. We present three multivariable flood loss models for companies from the manufacturing, commercial, financial, and service sector that intrinsically quantify prediction uncertainty. Based on object-level loss data (n = 1,306), we comparatively evaluate the predictive capacity of Bayesian networks, Bayesian regression, and random forest in relation to deterministic and probabilistic stage-damage functions, serving as benchmarks. The company loss data stem from four postevent surveys in Germany between 2002 and 2013 and include information on flood intensity, company characteristics, emergency response, private precaution, and resulting loss to building, equipment, and goods and stock. We find that the multivariable probabilistic models successfully identify and reproduce essential relationships of flood damage processes in the data. The assessment of model skill focuses on the precision of the probabilistic predictions and reveals that the candidate models outperform the stage-damage functions, while differences among the proposed models are negligible. Although the combination of multivariable and probabilistic loss estimation improves predictive accuracy over the entire data set, wide predictive distributions stress the necessity for the quantification of uncertainty. KW - flood loss estimation KW - probabilistic modeling KW - companies KW - multivariable KW - models Y1 - 2020 U6 - https://doi.org/10.1029/2020WR027649 SN - 0043-1397 SN - 1944-7973 VL - 56 IS - 9 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Holschneider, Matthias A1 - Zöller, Gert A1 - Clements, R. A1 - Schorlemmer, Danijel T1 - Can we test for the maximum possible earthquake magnitude? JF - Journal of geophysical research : Solid earth Y1 - 2014 U6 - https://doi.org/10.1002/2013JB010319 SN - 2169-9313 SN - 2169-9356 VL - 119 IS - 3 SP - 2019 EP - 2028 PB - American Geophysical Union CY - Washington ER -