@article{ZhuCottonKawaseetal.2022, author = {Zhu, Chuanbin and Cotton, Fabrice and Kawase, Hiroshi and H{\"a}ndel, Annabel and Pilz, Marco and Nakano, Kenichi}, title = {How well can we predict earthquake site response so far?}, series = {Earthquake spectra : the professional journal of the Earthquake Engineering Research Institute}, volume = {38}, journal = {Earthquake spectra : the professional journal of the Earthquake Engineering Research Institute}, number = {2}, publisher = {Sage Publ.}, address = {Thousand Oaks}, issn = {8755-2930}, doi = {10.1177/87552930211060859}, pages = {1047 -- 1075}, year = {2022}, abstract = {Earthquake site responses or site effects are the modifications of surface geology to seismic waves. How well can we predict the site effects (average over many earthquakes) at individual sites so far? To address this question, we tested and compared the effectiveness of different estimation techniques in predicting the outcrop Fourier site responses separated using the general inversion technique (GIT) from recordings. Techniques being evaluated are (a) the empirical correction to the horizontal-to-vertical spectral ratio of earthquakes (c-HVSR), (b) one-dimensional ground response analysis (GRA), and (c) the square-root-impedance (SRI) method (also called the quarter-wavelength approach). Our results show that c-HVSR can capture significantly more site-specific features in site responses than both GRA and SRI in the aggregate, especially at relatively high frequencies. c-HVSR achieves a "good match" in spectral shape at similar to 80\%-90\% of 145 testing sites, whereas GRA and SRI fail at most sites. GRA and SRI results have a high level of parametric and/or modeling errors which can be constrained, to some extent, by collecting on-site recordings.}, language = {en} } @article{ZaliOhrnbergerScherbaumetal.2021, author = {Zali, Zahra and Ohrnberger, Matthias and Scherbaum, Frank and Cotton, Fabrice and Eibl, Eva P. S.}, title = {Volcanic tremor extraction and earthquake detection using music information retrieval algorithms}, series = {Seismological research letters}, volume = {92}, journal = {Seismological research letters}, number = {6}, publisher = {Seismological Society of America}, address = {Boulder, Colo.}, issn = {0895-0695}, doi = {10.1785/0220210016}, pages = {3668 -- 3681}, year = {2021}, abstract = {Volcanic tremor signals are usually observed before or during volcanic eruptions and must be monitored to evaluate the volcanic activity. A challenge in studying seismic signals of volcanic origin is the coexistence of transient signal swarms and long-lasting volcanic tremor signals. Separating transient events from volcanic tremors can, therefore, contrib-ute to improving upon our understanding of the underlying physical processes. Exploiting the idea of harmonic-percussive separation in musical signal processing, we develop a method to extract the harmonic volcanic tremor signals and to detect tran-sient events from seismic recordings. Based on the similarity properties of spectrogram frames in the time-frequency domain, we decompose the signal into two separate spec-trograms representing repeating (harmonic) and nonrepeating (transient) patterns, which correspond to volcanic tremor signals and earthquake signals, respectively. We reconstruct the harmonic tremor signal in the time domain from the complex spectrogram of the repeating pattern by only considering the phase components for the frequency range in which the tremor amplitude spectrum is significantly contribut-ing to the energy of the signal. The reconstructed signal is, therefore, clean tremor signal without transient events. Furthermore, we derive a characteristic function suitable for the detection of tran-sient events (e.g., earthquakes) by integrating amplitudes of the nonrepeating spectro-gram over frequency at each time frame. Considering transient events like earthquakes, 78\% of the events are detected for signal-to-noise ratio = 0.1 in our semisynthetic tests. In addition, we compared the number of detected earthquakes using our method for one month of continuous data recorded during the Holuhraun 2014-2015 eruption in Iceland with the bulletin presented in Agustsdottir et al. (2019). Our single station event detection algorithm identified 84\% of the bulletin events. Moreover, we detected a total of 12,619 events, which is more than twice the number of the bulletin events.}, language = {en} } @article{WeatherillKothaCotton2020, author = {Weatherill, Graeme and Kotha, Sreeram Reddy and Cotton, Fabrice Pierre}, title = {Re-thinking site amplification in regional seismic risk assessment}, series = {Earthquake spectra : the professional journal of the Earthquake Engineering Research Institute}, volume = {36}, journal = {Earthquake spectra : the professional journal of the Earthquake Engineering Research Institute}, number = {1_SUPPL}, publisher = {Sage Publishing}, address = {Thousand Oaks, CA}, issn = {8755-2930}, doi = {10.1177/8755293019899956}, pages = {274 -- 297}, year = {2020}, abstract = {Probabilistic assessment of seismic hazard and risk over a geographical region presents the modeler with challenges in the characterization of the site amplification that are not present in site-specific assessment. Using site-to-site residuals from a ground motion model fit to observations from the Japanese KiK-net database, correlations between measured local amplifications and mappable proxies such as topographic slope and geology are explored. These are used subsequently to develop empirical models describing amplification as a direct function of slope, conditional upon geological period. These correlations also demonstrate the limitations of inferring 30-m shearwave velocity from slope and applying them directly into ground motion models. Instead, they illustrate the feasibility of deriving spectral acceleration amplification factors directly from sets of observed records, which are calibrated to parameters that can be mapped uniformly on a regional scale. The result is a geologically calibrated amplification model that can be incorporated into national and regional seismic hazard and risk assessment, ensuring that the corresponding total aleatory variability reflects the predictive capability of the mapped site proxy.}, language = {en} } @article{TuerkerCottonPilzetal.2022, author = {T{\"u}rker, Elif and Cotton, Fabrice and Pilz, Marco and Weatherill, Graeme}, title = {Analysis of the 2019 Mw 5.8 Silivri earthquake ground motions}, series = {Seismological research letters}, volume = {93}, journal = {Seismological research letters}, number = {2A}, publisher = {Seismological Society of America}, address = {Boulder, Colo.}, issn = {0895-0695}, doi = {10.1785/0220210168}, pages = {693 -- 705}, year = {2022}, abstract = {The main Marmara fault (MMF) extends for 150 km through the Sea of Marmara and forms the only portion of the North Anatolian fault zone that has not ruptured in a large event (Mw >7) for the last 250 yr. Accordingly, this portion is potentially a major source contributing to the seismic hazard of the Istanbul region. On 26 September 2019, a sequence of moderate-sized events started along the MMF only 20 km south of Istanbul and were widely felt by the population. The largest three events, 26 September Mw 5.8 (10:59 UTC), 26 September 2019 Mw 4.1 (11:26 UTC), and 20 January 2020 Mw 4.7 were recorded by numerous strong-motion seismic stations and the resulting ground motions were compared to the predicted means resulting from a set of the most recent ground-motion prediction equations (GMPEs). The estimated residuals were used to investigate the spatial variation of ground motion across the Marmara region. Our results show a strong azimuthal trend in ground-motion residuals, which might indicate systematically repeating directivity effects toward the eastern Marmara region.}, language = {en} } @article{NievasPilzPrehnetal.2022, author = {Nievas, Cecilia and Pilz, Marco and Prehn, Karsten and Schorlemmer, Danijel and Weatherill, Graeme and Cotton, Fabrice}, title = {Calculating earthquake damage building by building}, series = {Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering}, volume = {20}, journal = {Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering}, number = {3}, publisher = {Springer}, address = {Dordrecht}, issn = {1570-761X}, doi = {10.1007/s10518-021-01303-w}, pages = {1519 -- 1565}, year = {2022}, abstract = {The creation of building exposure models for seismic risk assessment is frequently challenging due to the lack of availability of detailed information on building structures. Different strategies have been developed in recent years to overcome this, including the use of census data, remote sensing imagery and volunteered graphic information (VGI). This paper presents the development of a building-by-building exposure model based exclusively on openly available datasets, including both VGI and census statistics, which are defined at different levels of spatial resolution and for different moments in time. The initial model stemming purely from building-level data is enriched with statistics aggregated at the neighbourhood and city level by means of a Monte Carlo simulation that enables the generation of full realisations of damage estimates when using the exposure model in the context of an earthquake scenario calculation. Though applicable to any other region of interest where analogous datasets are available, the workflow and approach followed are explained by focusing on the case of the German city of Cologne, for which a scenario earthquake is defined and the potential damage is calculated. The resulting exposure model and damage estimates are presented, and it is shown that the latter are broadly consistent with damage data from the 1978 Albstadt earthquake, notwithstanding the differences in the scenario. Through this real-world application we demonstrate the potential of VGI and open data to be used for exposure modelling for natural risk assessment, when combined with suitable knowledge on building fragility and accounting for the inherent uncertainties.}, language = {en} } @article{LilienkampvonSpechtWeatherilletal.2022, author = {Lilienkamp, Henning and von Specht, Sebastian and Weatherill, Graeme and Caire, Giuseppe and Cotton, Fabrice}, title = {Ground-Motion modeling as an image processing task}, series = {Bulletin of the Seismological Society of America}, volume = {112}, journal = {Bulletin of the Seismological Society of America}, number = {3}, publisher = {Seismological Society of America}, address = {Albany}, issn = {0037-1106}, doi = {10.1785/0120220008}, pages = {1565 -- 1582}, year = {2022}, abstract = {We construct and examine the prototype of a deep learning-based ground-motion model (GMM) that is both fully data driven and nonergodic. We formulate ground-motion modeling as an image processing task, in which a specific type of neural network, the U-Net, relates continuous, horizontal maps of earthquake predictive parameters to sparse observations of a ground-motion intensity measure (IM). The processing of map-shaped data allows the natural incorporation of absolute earthquake source and observation site coordinates, and is, therefore, well suited to include site-, source-, and path-specific amplification effects in a nonergodic GMM. Data-driven interpolation of the IM between observation points is an inherent feature of the U-Net and requires no a priori assumptions. We evaluate our model using both a synthetic dataset and a subset of observations from the KiK-net strong motion network in the Kanto basin in Japan. We find that the U-Net model is capable of learning the magnitude???distance scaling, as well as site-, source-, and path-specific amplification effects from a strong motion dataset. The interpolation scheme is evaluated using a fivefold cross validation and is found to provide on average unbiased predictions. The magnitude???distance scaling as well as the site amplification of response spectral acceleration at a period of 1 s obtained for the Kanto basin are comparable to previous regional studies.}, language = {en} }