TY - JOUR A1 - Gomez-Zapata, Juan Camilo A1 - Pittore, Massimiliano A1 - Cotton, Fabrice A1 - Lilienkamp, Henning A1 - Shinde, Simantini A1 - Aguirre, Paula A1 - Santa Maria, Hernan T1 - Epistemic uncertainty of probabilistic building exposure compositions in scenario-based earthquake loss models JF - Bulletin of Earthquake Engineering N2 - In seismic risk assessment, the sources of uncertainty associated with building exposure modelling have not received as much attention as other components related to hazard and vulnerability. Conventional practices such as assuming absolute portfolio compositions (i.e., proportions per building class) from expert-based assumptions over aggregated data crudely disregard the contribution of uncertainty of the exposure upon earthquake loss models. In this work, we introduce the concept that the degree of knowledge of a building stock can be described within a Bayesian probabilistic approach that integrates both expert-based prior distributions and data collection on individual buildings. We investigate the impact of the epistemic uncertainty in the portfolio composition on scenario-based earthquake loss models through an exposure-oriented logic tree arrangement based on synthetic building portfolios. For illustrative purposes, we consider the residential building stock of Valparaiso (Chile) subjected to seismic ground-shaking from one subduction earthquake. We have found that building class reconnaissance, either from prior assumptions by desktop studies with aggregated data (top-down approach), or from building-by-building data collection (bottom-up approach), plays a fundamental role in the statistical modelling of exposure. To model the vulnerability of such a heterogeneous building stock, we require that their associated set of structural fragility functions handle multiple spectral periods. Thereby, we also discuss the relevance and specific uncertainty upon generating either uncorrelated or spatially cross-correlated ground motion fields within this framework. We successively show how various epistemic uncertainties embedded within these probabilistic exposure models are differently propagated throughout the computed direct financial losses. This work calls for further efforts to redesign desktop exposure studies, while also highlighting the importance of exposure data collection with standardized and iterative approaches. KW - Epistemic uncertainty KW - Sensitivity analysis KW - Scheme KW - Faceted taxonomy KW - Probabilistic exposure modelling KW - Earthquake scenario KW - Data collection KW - Earthquake loss modelling KW - Spatially cross-correlated ground motion KW - fields Y1 - 2022 U6 - https://doi.org/10.1007/s10518-021-01312-9 SN - 1570-761X SN - 1573-1456 N1 - Update notice Correction to: Epistemic uncertainty of probabilistic building exposure compositions in scenario-based earthquake loss models (Bulletin of Earthquake Engineering, (2022), 20, 5, (2401-2438), https://doi.org/10.1007/s10518-021-01312-9) Bulletin of Earthquake Engineering, Volume 20, Issue 5, Pages 2439, March 2022, https://doi.org/10.1007/s10518-022-01340-z VL - 20 IS - 5 SP - 2401 EP - 2438 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Kotha, Sreeram Reddy A1 - Weatherill, Graeme A1 - Bindi, Dino A1 - Cotton, Fabrice T1 - Near-source magnitude scaling of spectral accelerations BT - analysis and update of Kotha et al. (2020) model JF - Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering N2 - Ground-motion models (GMMs) are often used to predict the random distribution of Spectral accelerations (SAs) at a site due to a nearby earthquake. In probabilistic seismic hazard and risk assessment, large earthquakes occurring close to a site are considered as critical scenarios. GMMs are expected to predict realistic SAs with low within-model uncertainty (sigma(mu)) for such rare scenarios. However, the datasets used to regress GMMs are usually deficient of data from critical scenarios. The (Kotha et al., A Regionally Adaptable Ground-Motion Model for Shallow Crustal Earthquakes in Europe Bulletin of Earthquake Engineering 18:4091-4125, 2020) GMM developed from the Engineering strong motion (ESM) dataset was found to predict decreasing short-period SAs with increasing M-W >= M-h = 6.2, and with large sigma(mu) at near-source distances <= 30km. In this study, we updated the parametrisation of the GMM based on analyses of ESM and the Near source strong motion (NESS) datasets. With M-h = 5.7, we could rectify the M-W scaling issue, while also reducing sigma(mu). at M-W >= M-h. We then evaluated the GMM against NESS data, and found that the SAs from a few large, thrust-faulting events in California, New Zealand, Japan, and Mexico are significantly higher than GMM median predictions. However, recordings from these events were mostly made on soft-soil geology, and contain anisotropic pulse-like effects. A more thorough non-ergodic treatment of NESS was not possible because most sites sampled unique events in very diverse tectonic environments. We provide an updated set of GMM coefficients,sigma(mu), and heteroscedastic variance models; while also cautioning against its application for M-W <= 4 in low-moderate seismicity regions without evaluating the homogeneity of M-W estimates between pan-European ESM and regional datasets. KW - Ground-motion model KW - Spectral accelerations KW - Magnitude scalin KW - Near-source saturation KW - Within-model uncertainty KW - Heteroscedastic KW - variability Y1 - 2022 U6 - https://doi.org/10.1007/s10518-021-01308-5 SN - 1570-761X SN - 1573-1456 VL - 20 IS - 3 SP - 1343 EP - 1370 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Lilienkamp, Henning A1 - von Specht, Sebastian A1 - Weatherill, Graeme A1 - Caire, Giuseppe A1 - Cotton, Fabrice T1 - Ground-Motion modeling as an image processing task BT - introducing a neural network based, fully data-driven, and nonergodic JF - Bulletin of the Seismological Society of America N2 - 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. Y1 - 2022 U6 - https://doi.org/10.1785/0120220008 SN - 0037-1106 SN - 1943-3573 VL - 112 IS - 3 SP - 1565 EP - 1582 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Nievas, Cecilia A1 - Pilz, Marco A1 - Prehn, Karsten A1 - Schorlemmer, Danijel A1 - Weatherill, Graeme A1 - Cotton, Fabrice T1 - Calculating earthquake damage building by building BT - the case of the city of Cologne, Germany JF - Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering N2 - 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. KW - Building exposure modelling KW - Seismic damage assessment KW - Scenario KW - earthquake KW - Seismic risk KW - Cologne Y1 - 2022 U6 - https://doi.org/10.1007/s10518-021-01303-w SN - 1570-761X SN - 1573-1456 VL - 20 IS - 3 SP - 1519 EP - 1565 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Peña, Carlos A1 - Metzger, Sabrina A1 - Heidbach, Oliver A1 - Bedford, Jonathan A1 - Bookhagen, Bodo A1 - Moreno, Marcos A1 - Oncken, Onno A1 - Cotton, Fabrice T1 - Role of poroelasticity during the early postseismic deformation of the 2010 Maule megathrust earthquake JF - Geophysical research letters N2 - Megathrust earthquakes impose changes of differential stress and pore pressure in the lithosphere-asthenosphere system that are transiently relaxed during the postseismic period primarily due to afterslip, viscoelastic and poroelastic processes. Especially during the early postseismic phase, however, the relative contribution of these processes to the observed surface deformation is unclear. To investigate this, we use geodetic data collected in the first 48 days following the 2010 Maule earthquake and a poro-viscoelastic forward model combined with an afterslip inversion. This model approach fits the geodetic data 14% better than a pure elastic model. Particularly near the region of maximum coseismic slip, the predicted surface poroelastic uplift pattern explains well the observations. If poroelasticity is neglected, the spatial afterslip distribution is locally altered by up to +/- 40%. Moreover, we find that shallow crustal aftershocks mostly occur in regions of increased postseismic pore-pressure changes, indicating that both processes might be mechanically coupled. KW - Chilean subduction zone KW - poroelasticity KW - power-law rheology KW - afterslip inversion KW - InSAR KW - GNSS Y1 - 2022 U6 - https://doi.org/10.1029/2022GL098144 SN - 0094-8276 SN - 1944-8007 VL - 49 IS - 9 PB - Wiley CY - Hoboken, NJ ER - TY - JOUR A1 - Türker, Elif A1 - Cotton, Fabrice A1 - Pilz, Marco A1 - Weatherill, Graeme T1 - Analysis of the 2019 Mw 5.8 Silivri earthquake ground motions BT - evidence of systematic azimuthal variations associated with directivity effects JF - Seismological research letters N2 - 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. Y1 - 2022 U6 - https://doi.org/10.1785/0220210168 SN - 0895-0695 SN - 1938-2057 VL - 93 IS - 2A SP - 693 EP - 705 PB - Seismological Society of America CY - Boulder, Colo. ER - TY - JOUR A1 - Yen, Ming-Hsuan A1 - von Specht, Sebastian A1 - Lin, Yen-Yu A1 - Cotton, Fabrice A1 - Ma, Kuo-Fong T1 - Within- and between-event variabilities of strong-velocity pulses of moderate earthquakes within dense seismic arrays JF - Bulletin of the Seismological Society of America N2 - Ground motion with strong-velocity pulses can cause significant damage to buildings and structures at certain periods; hence, knowing the period and velocity amplitude of such pulses is critical for earthquake structural engineering. However, the physical factors relating the scaling of pulse periods with magnitude are poorly understood. In this study, we investigate moderate but damaging earthquakes (M-w 6-7) and characterize ground- motion pulses using the method of Shahi and Baker (2014) while considering the potential static-offset effects. We confirm that the within-event variability of the pulses is large. The identified pulses in this study are mostly from strike-slip-like earthquakes. We further perform simulations using the freq uency-wavenumber algorithm to investigate the causes of the variability of the pulse periods within and between events for moderate strike-slip earthquakes. We test the effect of fault dips, and the impact of the asperity locations and sizes. The simulations reveal that the asperity properties have a high impact on the pulse periods and amplitudes at nearby stations. Our results emphasize the importance of asperity characteristics, in addition to earthquake magnitudes for the occurrence and properties of pulses produced by the forward directivity effect. We finally quantify and discuss within- and between-event variabilities of pulse properties at short distances. Y1 - 2021 U6 - https://doi.org/10.1785/0120200376 SN - 0037-1106 SN - 1943-3573 VL - 112 IS - 1 SP - 361 EP - 380 PB - Seismological Society of America CY - El Cerito, Calif. ER - TY - JOUR A1 - Zhu, Chuanbin A1 - Cotton, Fabrice A1 - Kawase, Hiroshi A1 - Händel, Annabel A1 - Pilz, Marco A1 - Nakano, Kenichi T1 - How well can we predict earthquake site response so far? BT - site-specific approaches JF - Earthquake spectra : the professional journal of the Earthquake Engineering Research Institute N2 - 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. KW - Site response KW - site effects KW - HVSR KW - ground response analysis KW - square-root-impedance KW - earthquake Y1 - 2022 U6 - https://doi.org/10.1177/87552930211060859 SN - 8755-2930 SN - 1944-8201 VL - 38 IS - 2 SP - 1047 EP - 1075 PB - Sage Publ. CY - Thousand Oaks ER -