NH4.2

EDI
Physical and data-driven models for seismic risk assessments toward disaster reduction

Earthquake disaster mitigation involves different elements, ranging from analysis of hazards (e.g. physical description of ground shaking) to its impact on built and natural environment, from vulnerability and exposure to hazards to capacity building and resilience, from long-term preparedness to post-event response. The scientific base of this process involves various seismic hazard/risk models, developed at different time scales and by different methods, as well as the use of heterogeneous observations and multi-disciplinary information. Accordingly, we welcome contributions about different types of seismic hazards research and assessments, both methodological and practical, and their applications to disaster risk reduction in terms of physical and social vulnerability, capacity and resilience.
This session aims to tackle theoretical and implementation issues, as well as aspects of communication and science policy, which are all essential elements towards effective disasters mitigation, and include:
⇒ development of physical/statistical models for the different earthquake risk components (hazard, exposure, vulnerability), including novel methods for data collection and processing (e.g. statistical machine learning analysis)
⇒ earthquake hazard and risk estimation at different time and space scales, including their performance verification against observations (including unconventional seismological observations);
⇒ time-dependent seismic hazard and risk assessments (including contribution of aftershocks), and post-event information (early warning, alerts) for emergency management;
⇒ earthquake-induced cascading effects (e.g. landslides, tsunamis, etc) and multi-risk assessment (e.g. earthquake plus flooding).
The interdisciplinary session will provide an opportunity to share best practices and experience gained with different methods, providing opportunities to advance our understanding of disaster risk in "all its dimensions of vulnerability, capacity, exposure of persons and assets, hazard characteristics and the environment", while simultaneously highlighting existing gaps and future research directions.

Co-organized by SM7
Convener: Antonella Peresan | Co-conveners: Alik Ismail-Zadeh, Katerina Orfanogiannaki, Katalin Gribovszki, Elisa Varini
Presentations
| Fri, 27 May, 14:05–16:40 (CEST)
 
Room M2

Presentations: Fri, 27 May | Room M2

Chairpersons: Antonella Peresan, Katalin Gribovszki
14:05–14:07
Statistical and physical models of earthquakes occurrence
14:07–14:12
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EGU22-4746
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Virtual presentation
Sergey Pulinets, Blaž Vičič, Pavel Budnikov, Jure Žalohar, Matic Potočnik, Marco Komac, and Matej Dolenec

Over the last 30 years, the Cosserat continuum has gained an importance in the description of physical properties of tectonic faulting. Using the sine-Gordon equation we show that kink and antikink solitary wave solutions can be used to describe propagation of the couple-stresses through the faulted medium of the Earth’s crust. Recently it was established that the shear-traction exerted on the tectonic faults by the couple-stresses correlates with radon degassing. Degassing is estimated through atmospheric effects due to air ionization expressed in the form of the atmospheric chemical potential (ACP), thus providing a direct and measurable proof for the existence propagating couple-stresses in the Earth’s crust. The positive and negative correlation corresponds to different faulting mechanism and thickness of the Earth’s crust. Positive correlation is observed in the regions characterized by thin crust, as well as in the normal and strike-slip faulting regimes. The negative correlation is observed in the regions characterized by thick crust as well as in the reverse faulting regimes, and along very long transform faults. Using together the shear-traction modeling and ACP measurements, we can identify critical zones prone to the earthquake triggering and calculate the time-dependent probability for the future earthquakes.

How to cite: Pulinets, S., Vičič, B., Budnikov, P., Žalohar, J., Potočnik, M., Komac, M., and Dolenec, M.: Real-time global shear-traction model verification using atmospheric effects of radon activity, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4746, https://doi.org/10.5194/egusphere-egu22-4746, 2022.

14:12–14:17
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EGU22-9041
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ECS
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Virtual presentation
Edlira Xhafaj, Chung-Han Chan, and Kuo-Fong Ma

Abstract
We proposed an earthquake forecasting model for Albania, one of the most seismic
regions in Europe, to give an overview of seismic activity by implementing area
source and smoothing approaches. The earthquake catalogue was firstly declustered
to evaluate the completeness time window and magnitude of completeness for shallow
events. Considering catalogue completeness, the events with M≥4.0 during the period
of time 1960 – 2006 were implemented for forecasting seismicity in 20 area sources
covering the region of study and each grid cell with a size of 0.2 x 0.2 degrees. Our
results from both models show a high seismic rate along the western coastline and
south part of the study area, consistent with previous studies and currently active
regions. To further evaluate the seismicity results from the models, we introduced a
Molchan diagram to investigate the correlation between a model and observations of
earthquake events. The catalogue from 1960 to 2006 is regarded as the “learning
period” for model construction, and the catalogue data covering the period of time
2018-2020 is the “testing period” for comparing and validating the results. The
Molchan diagram suggests that both models are significantly better than random
distributed, confirming their forecasting abilities. Our results could provide crucial
information for subsequent probabilistic seismic hazard assessment.


Keywords: area sources, declustering, earthquake catalogue, Molchan diagram,
probabilistic seismic hazard assessment, smoothing model,.

How to cite: Xhafaj, E., Chan, C.-H., and Ma, K.-F.: Earthquake forecasting model in Albania, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9041, https://doi.org/10.5194/egusphere-egu22-9041, 2022.

14:17–14:22
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EGU22-2700
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Virtual presentation
Elisa Varini and Antonella Peresan

Complex network theory has been recently applied to get new insights and a different perspective in the study of earthquake patterns. Several studies (see for instance Daskalaki et al., J Seismol, 2016; Telesca, Phys. Chem. Earth, 2015; Varini et al., J Geophys Res, 2020; Ebrahimi et al., Chaos Solitons Fractals, 2021, and references therein) were based on the preliminary mapping of the time series of earthquakes into networks, by applying visibility graph method or other clustering algorithms. In a second step, the topological properties of the obtained networks were analyze by exploiting tools of complex network theory with the aim of discovering possible precursory signatures of strong earthquakes or other features relevant to hazard assessment.

In this study we investigated the earthquake clusters extracted by two data-driven declustering algorithms: the nearest-neighbor, which classifies the earthquakes on the basis of a nearest-neighbor distance between events in the space-time-energy domain (Zaliapin and Ben-Zion, J Geophys Res, 2013), and the stochastic declustering, which is based on the space-time ETAS point process model (Zhuang et al., J Geophys Res, 2004). Case studies from selected sequences, occurred in Central Italy from 1985 to 2021, are examined in some detail.

The earthquake clusters extracted by the two declustering algorithms are compared by different tools, so as to assess the similarities and differences in their classification and characterization (Varini et al., J Geophys Res, 2020). The connections between events forming a cluster, as defined by the considered declustering method, allow us representing its hierarchical structure by means of a tree graph. The topological structure of the clusters is then investigated by means of centrality measures in the frame of Network analysis.

How to cite: Varini, E. and Peresan, A.: Investigating earthquake clusters complexity in Central Italy by network theory tools, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2700, https://doi.org/10.5194/egusphere-egu22-2700, 2022.

14:22–14:27
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EGU22-4035
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ECS
Katerina Orfanogiannaki and Dimitris Karlis

Over the years numerous attempts have been made to obtain the distribution of earthquake numbers. The most popular distribution that has been widely used to describe earthquake numbers is the Poisson distribution due to its simplicity and relative ease of application. Another distribution that has been used to approximate the earthquake number distribution is the Negative Binomial. However, for small-time intervals, both the Poisson and Negative binomial distributions fail to fit observed earthquake frequencies. We propose an extension of mixture models that is Hidden Markov Models (HMMs) with Poisson and Negative Binomial state-specific probability distributions and thus derive Poisson (P-HMMs) and Negative Binomial Hidden Markov Models (NB-HMMs), respectively. We use the parametrization of the Negative Binomial distribution in which the probability density function is expressed in terms of the mean and the shape parameter. In this parametrization, a variance is a quadratic form of the mean and the Negative Binomial distribution tends to the Poisson distribution when the shape parameter tends to infinity. Three-time units have been selected to count the number of earthquakes, namely 1-day, 5-day, and 10-days counting intervals resulting in daily, 5-day, and 10-day time series.

The region of Killini, Western Greece has been selected to apply the proposed methodology. All earthquakes with Local Magnitude ML 3:2 have been selected in the time interval from 1990 to 2007, inclusive. This time interval is divided into two sub-intervals that correspond to the learning and the testing periods. In the learning period from 1990 to 2004, inclusive the parameters of the models are estimated while in the testing period from 2005 to 2007, inclusive the ability of the models is tested to extrapolate past states of seismicity into the future. We applied both models with a different number of states to the daily, 5-day and 10-day time series of earthquakes that occurred in the Killini region during the learning period. Based on the Bayesian Information Criterion (BIC) for all three counting intervals the NB-HMMs model with three components was selected. The best-fitting model was used to estimate through simulations the number of earthquakes expected to occur in the study area during 1-day, 5-day, and 10-day intervals for the testing period. From the results obtained it appears that regardless of the selected time unit the models are able to capture the future variations
of seismic activity.

How to cite: Orfanogiannaki, K. and Karlis, D.: Using Negative Binomial Hidden Markov models to extrapolate past states of seismicity into the future, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4035, https://doi.org/10.5194/egusphere-egu22-4035, 2022.

14:27–14:32
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EGU22-2378
Giuliana Rossi, Gianni Bressan, Antonella Peresan, and Carla Barnaba

A multi-parametric approach, based on five different parameters quantifying seismicity, is proposed for investigating the space-time evolution of earthquakes occurrence in areas characterized by complex tectonics, namely by the interference of differently oriented faults and by the heterogeneous mechanical strength of the rocks. Specifically, the variations of entropy, the b-value from the Gutenberg-Richter law, the changes in fractal dimension, and the Nearest Neighbour distance (η) are used for assessing changes in the temporal patterns of seismicity. In parallel, the Principal Component Analysis (PCA) in 4D (space and time) is used to define the hypocentres distribution geometry and the propagation directions.

In particular, we applied the methods mentioned above in a multi-parametric study of the seismicity space-time evolution from 2015 to the beginning of 2020 in a well-focused area. The study area, centred on the town of Tolmezzo, in Northeastern Italy, between the Alps and the Prealps, is characterized by a complex tectonic pattern resulting from the interference of differently oriented fault systems and involving mechanically heterogeneous rocks. After a long period of low seismic activity, lasting about 15 years, in 2018–2019, the area experienced a significant increase of radiated seismic energy, spatially clustered, with four sequences induced by earthquakes with MD (coda-duration magnitude) from 3.7 to 4.0 (http://www.crs.inogs.it/bollettino/RSFVG). Notably, the most energetic events are located in correspondence with the sharp transitions from zones of low damage to zones of intermediate damage. Two distinct periods of the seismic activity are identified, as revealed by the b-value and the fractal dimension, which show relevant fluctuations since the beginning of 2017. The temporal variation of the b-value can be related to crustal stress changes in the medium, which is characterized by different mechanical properties. The fractal dimension time evolution indicates a prevailing clustering of the earthquakes with a tendency to propagate linearly. The temporal variations of the Shannon entropy and η quantify the evolving organization and correlation of seismicity within an area; hence, they reflect a process of damage evolution in heterogeneous rocks that changes with time due to continuous strain energy redistribution. According to this view, the Shannon entropy and η can be considered parameters related to each other that reflect the memory of past deformations. The recovery of Shannon entropy and η to values preceding the crisis of 2018–2019 suggests that the system has reached a temporary new equilibrium.

The solutions provided by the PCA analysis along a cross-section close to Tolmezzo confirm such observations. They reveal mostly vertical and sub-vertical planes changing orientation along the cross-section considered. The fracture propagates within the fracturing plane in the southernmost and northernmost parts of the cross-section. In contrast, the results suggest the activation of parallel planes in the central part of the section, closer to Tolmezzo. The orientation of the planes inferred from PCA analysis agrees with secondary NNE-SSW and E-W trends present in the region considered. 

How to cite: Rossi, G., Bressan, G., Peresan, A., and Barnaba, C.: Anatomy of seismicity clustering from parametric space-time analysis, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2378, https://doi.org/10.5194/egusphere-egu22-2378, 2022.

14:32–14:42
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EGU22-13415
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solicited
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Virtual presentation
Renata Rotondi

Investigation into possible precursors of strong earthquakes constitutes a challenging research topic which is carried out mainly in two directions: the one based on the analysis of physical parameters and the one based on statistical methodologies. In the first, recent studies have shown significant correlation between major earthquakes and anomalies of different physical parameters measured in the atmosphere/ionosphere which cover time intervals of months.

On the contrary in this presentation we focus on the statistical modelling of the parameters that constitute an earthquake record in a catalog (location, time, magnitude) and we show that significant variations are observed in the months/years preceding a strong earthquake. In particular we consider the spatial distribution of a set of earthquakes and its temporal variations by modelling the area of Voronoi cells generated by the epicenters through a generalized Pareto (GP) distribution. Following the Bayesian paradigm we analyze the recent seismicity of the central Italy and we compare the posterior marginal likelihood of the most promising distributions in shifting time windows. We point out that the best fitting distribution varies over time and the trend of the GP distribution and of other distributions among the most studied in the literature converges to that of the exponential distribution a few months before the start of the preparatory phase to the main shock.

How to cite: Rotondi, R.: Statistical methods for middle-term forecast of earthquake occurrences, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13415, https://doi.org/10.5194/egusphere-egu22-13415, 2022.

14:42–14:50
Coffee break
Chairpersons: Alik Ismail-Zadeh, Elisa Varini, Katerina Orfanogiannaki
Seismic source characterisation
15:10–15:15
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EGU22-9029
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ECS
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On-site presentation
Auchitya Kumar Pandey, Prasanta Chingtham, and Paresh Nath Singha Roy

The computation of probable occurrence of future large earthquakes is the prime objective of the present study in the Northeast Himalaya India. For this purpose, the physics based rate-and-state friction law is adopted for forecasting the seismicity rate changes for MW ≥ 5.0 during the period 2016-2020. The coulomb stress changes (ΔCFF) is consider as a principle component which associated with the earthquake ruptured from the receiver’s fault. The reason behind considering the coulomb stress changes lies on the fact that the seismicity rate increases where the stress increase and decrease where the stress decreases. Here, it has been observed that high ΔCFF values are found widespread along the Main Central Thrust. Moreover, highest b-value is found to be in and around the Sikkim Himalaya. However, the highest background seismicity rate is also obtained in the vicinity of Sikkim and Bhutan with values ranging from 0 to 3.6. Finally, we have considered the consecutive fault parameter (Aσ = 0.05 MPa) for computing the forecast model with variable ΔCFF and heterogeneous b-value. The different value of the constitutive parameter (Aσ = 0.01, 0.02, 0.09, and 0.30 MPa) is adopted to understand the contribution of this parameter in a sudden change of seismicity rate due to stress perturbations. Also, various friction coefficient values (μ' = 0.2, 0.5, 0.6 and 0.8) are considered to find out the variation of seismicity rate changes. Then, CSEP model have been explored to check the consistency between the observed earthquakes and forecasted seismicity rates. The result from the CSEP model approves that the observed earthquakes matches well with the forecasted seismicity rates, thereby showing the consistency and efficiency of our forecast model.

How to cite: Pandey, A. K., Chingtham, P., and Roy, P. N. S.: Physics Based Seismicity Rate Computation For Northeast Himalaya, India, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9029, https://doi.org/10.5194/egusphere-egu22-9029, 2022.

15:15–15:20
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EGU22-9327
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ECS
Sylvain Michel, Romain Jolivet, Chris Rollins, and Jorge Jara

The northern Chile region of the Nazca subduction zone has hosted a Mw 8.5-9.0 earthquake in 1977 which induced a tsunami. The different magnitude estimates of this event are based on the evaluation of seismic intensities, tide gauge information and/or on the event’s inferred length, however, its actual along-strike extent is still under discussion. Based on geodetic data, former studies have also suggested this region awaits a Mw 8.6-8.8. In our study, we propose to revisit the evaluation of the seismic potential of the region, accounting for the fault’s moment deficit rate, earthquake magnitude-frequency distribution and earthquake physics. To do so, we combine an improved probabilistic estimate of moment deficit rate with results from dynamic models of the earthquake cycle, taking into account the influence of a potential barrier which could control the extent and therefore the magnitude of large events.

How to cite: Michel, S., Jolivet, R., Rollins, C., and Jara, J.: Seismic potential of the northern Chile region of the Nazca subduction zone, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9327, https://doi.org/10.5194/egusphere-egu22-9327, 2022.

15:20–15:25
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EGU22-5838
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ECS
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Virtual presentation
Oceane Foix, Stephane Mazzotti, and Herve Jomard

Seismic hazard levels used as reference for the French Lesser Antilles are derived from probabilistic seismic hazard assessment studies performed in 2002. However, our scientific knowledge has greatly increased over the past 20 years in this area. As part of a project linking the French Ministry of Ecological Transition and Solidarity, and the Seismicity Transverse Action of RéSiF (French seismological and geodetic network), we are developing a new seismotectonic model of the Lesser Antilles Subduction Zone (LASZ). The LASZ results from the subduction of the North and South American plates beneath the Caribbean plate since the Eocene. The boundary extends along 850 km in an ENE-WSW convergence direction at 18-20 mm/yr. Significant N-S variations in tectonic, seismic and volcanic activities raise questions on the undergoing geodynamic processes. Fractures and ridges entering into the subduction deform the trench, adding seismotectonic complexities. Several controversial hypothesis remain, such as the origins of the 1839 (Mw 7.5-8) and 1843 (Mw 8-8.5) earthquakes and the long term interseismic coupling, which is currently interpreted as being low. New seismic imageries and more complete seismic catalogs help to better constrain the slab and Moho shapes, as well as the hydrological behavior of the plate interface. In this study, we propose a compilation of existing data and hypothesis, completed by an analysis of focal mechanisms rupture types averaged on grid and strain tensor derived from GPS. For the first time, we add a particular attention in the role and influence of the mantle wedge seismicity, observed in only few subduction zones.

How to cite: Foix, O., Mazzotti, S., and Jomard, H.: A New Seismic Source Zone Model for Lesser Antilles Seismic Hazard Assessment , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5838, https://doi.org/10.5194/egusphere-egu22-5838, 2022.

Assessing SHA models and results
15:25–15:30
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EGU22-604
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ECS
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On-site presentation
Adriana Fatima Ornelas Agrela, Belen Benito Oterino, Rebeca Franco Blanco, Carlos García Lanchares, Miguel Marchamalo Sacristan, Guillermo Alvarado, Alvaro Climent, Walter Montero, and Victor Schmidt

We present here the first results of the KUK-AHPAN Project: INTEGRATED REGIONAL STUDY OF STRUCTURE AND EVOLUTION 4D OF CENTRAL AMERICAN LITHOSPHERE. IMPLICATIONS IN SEISMIC HAZARD AND RISK CALCULATION). One of the main purposes of this project is to improve the knowledge of the seismic hazard in Central American countries, as well as the seismic risk in populations of the region.

An initial phase is addressed to define deterministic scenarios in the capital cities, giving the expected strong motion due to possible ruptures in local faults which may be critical for the risk of the population.

Preliminary results have already been found in the metropolitan area of San Jose (Costa Rica), affected by moderate-high seismicity due to a complex system of faults in the Valle Central in a local frame. In a regional context, the seismicity of the country is explained by the tectonic interaction between the Cocos and Caribbean plates.

We have identified three critical scenarios corresponding to events located in the Belo Horizonte, Rio Azul, and Cipreses faults. The strong motion for these scenarios has been estimated firstly in rock conditions, by application of different Ground Motion Prediction Equations. (GMPEs). In the second place, a microzonation map for San Jose is proposed, derived from data of isoperiods, lithology and other geotechnical information.  The amplification factor for the different soils has been extracted from NEHRP. Finally, we estimated the peak ground acceleration (PGA) and other spectral accelerations SA(T) including the local effects for each rupture scenario defined.

These deterministic scenarios will be compared with other results obtained with probabilistic approaches including modelization of faults in the definition of source models. A final goal is to improve the knowledge of the influence of the source models based on faults, not only in zones, in the hazard estimates.

How to cite: Ornelas Agrela, A. F., Benito Oterino, B., Franco Blanco, R., García Lanchares, C., Marchamalo Sacristan, M., Alvarado, G., Climent, A., Montero, W., and Schmidt, V.: Deterministic scenarios for seismic hazard assessment in the metropolitan area of San Jose, Costa Rica. First results of the Kuk-Ahpan Project., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-604, https://doi.org/10.5194/egusphere-egu22-604, 2022.

15:30–15:35
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EGU22-1472
Chung-Han Chan, Jia-Cian Gao, and Yi-Hsuan Tseng

To confirm the probabilistic hazard assessment proposed by the Taiwan Earthquake Model (TEM), we compared it with the strong ground motion observations. We accessed the Taiwan Strong Motion Instrumentation Program (TSMIP) database and reported the maximum ground shaking of each strong-motion station. Comparing the TSMIP observations and the TEM hazard model reveals similar spatial patterns. However, some records indicate significantly higher shaking levels than the model does due to the occurrence of some large events, for example, the 1999 Mw7.6 Chi-Chi earthquake. Such discrepancies cannot be explained by model parameter uncertainties but by unexpected events in the given short observation period. We have confirmed that although each seismogenic structure in Taiwan is unlikely to rupture within a short period, the summarized earthquake potentials from all the structures are significant. Additionally, we discuss the impacts of some model parameters, including epistemic uncertainties of source parameters, truncation of standard deviation for ground motion prediction equations, the Gutenberg-Richter law for area source, and the time-dependent seismicity rate model. The outcomes of this study provide not only crucial information for urban planning on a city scale and building code legislation on a national scale, but also suggestions for the next generation of probabilistic seismic hazard assessment for Taiwan as well as other regions.

How to cite: Chan, C.-H., Gao, J.-C., and Tseng, Y.-H.: Confirmation of the probabilistic seismic hazard assessment by the Taiwan Earthquake Model through comparison with strong ground motion observations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1472, https://doi.org/10.5194/egusphere-egu22-1472, 2022.

15:35–15:40
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EGU22-12835
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On-site presentation
Karim Tarbali, John McCloskey, Himanshu Agrawal, and Carmine Galasso

This paper investigates the predominant effects of sub-surface geological characteristics on the earthquake-induced ground-motion properties relevant to the design of infrastructure systems in urban environments. By considering ensembles of different earthquake scenarios and conducting numerical simulations to generate surface ground motion realizations, the contributing factors of earthquake source and earth properties in shaping the spatial pattern of ground motion amplitudes are scrutinized. Physics-based ground-motion simulations are conducted for 28 earthquake scenarios with moment magnitudes of 5.0 and 6.0 triggered with different azimuthal and geometrical properties. The earth wave-propagation properties are defined by considering data and empirical relationships that represent a typical geological setting with depth crustal rock and soft sedimentary basin (including a river channel). The spatial pattern of ground motion intensity measures (defined as the geometrical mean of the two horizontal pseudo-spectral accelerations) is used to show the average spatial pattern of ground motion severity. The results demonstrate that, even though the spatial ground motion patterns for a specific scenario earthquake depend on both the sub-surface geology and the source properties, the sub-surface geological characteristics impose a deterministic impact on the average spatial pattern of ground motions regardless of the earthquake location, azimuthal and geometrical properties. This clearly indicates that the regional seismic hazard assessments should allocate further resources for determining the sub-surface earth properties as they can disproportionally alter urban designs in contrast to the conventional concern on determining the location of probable future earthquakes and their small-scale characteristics.

How to cite: Tarbali, K., McCloskey, J., Agrawal, H., and Galasso, C.: The effects of large-scale geological characteristics on the average spatial pattern of earthquake-induced ground motions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12835, https://doi.org/10.5194/egusphere-egu22-12835, 2022.

15:40–15:45
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EGU22-4093
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On-site presentation
Kris Vanneste and Thierry Camelbeeck

In the area around Belgium, the Hainaut region is one of the most seismically active zones, behind the Roer Valley Graben (where seismicity is linked to known active faults) and the Eastern Ardennes (where the largest historical earthquake in NW Europe occurred). As a result, this comparatively small area stands out on most seismic hazard maps made during the past two decades. However, seismicity only started at the end of the 19th century and seems to decline gradually since the late 20th century. Historical earthquakes are not known in this area. This evolution is very similar to the history of coal mining in the area, which started in the 19th century, culminated in the 20th century and ceased in 1984, suggesting that the Hainaut seismicity may be induced. This seismicity is characterized by low to moderate magnitudes, up to MW= 4.1, but due to their shallow focal depth (< 6 km), many earthquakes caused damage with corresponding maximum intensities up to VII on the EMS-98 scale, as indicated by a recent compilation of all available macroseismic intensity data (Camelbeeck et al., 2021). This reassessment also showed that intensities in this region attenuate much faster with distance than in other parts of Belgium. This highlights the importance of selecting appropriate ground-motion prediction equations (GMPEs) for seismic hazard assessment (SHA), which is the main objective of this study.

The past two decades, several metrics have been proposed to evaluate the goodness of fit between a GMPE and observed ground motion, such as the LH and LLH measures (Scherbaum et al., 2004; 2009) and Euclidean-based Distance Ranking (Kale & Akkar, 2013). Using macroseismic data to rank GMPEs requires an additional conversion of predicted ground motions to intensities using a ground-motion-to-intensity conversion equation (GMICE). Normalized residuals between observed and predicted intensities are then computed using the combined uncertainty of GMPE and GMICE (Villani et al., 2019). We evaluated different GMICEs and selected the relation by Atkinson & Kaka (2007) because it includes magnitude- and distance-dependent terms that result in better consistency between PGA and PGV than with the other relations. We made a selection of 20 recent GMPEs for the analysis, including newer versions of GMPEs used earlier in Belgium, GMPEs applied in recent SHAs in France, Germany and the UK, as well as two GMPEs developed specifically for induced earthquakes. Our preliminary results indicate that the latter GMPEs, in addition to the NGA-East GMPE by Atkinson & Boore (2006), show the best agreement with the data, although it should be noted that none of the tested GMPEs provides a really good match and none of the ranking methods considers the trend of residuals with distance. We also find that the scores based on PGV are significantly better than those based on PGA. The ranking results will be used to guide our selection of GMPEs for the new seismic hazard map of Belgium.

How to cite: Vanneste, K. and Camelbeeck, T.: Testing the applicability of GMPEs for the Hainaut region (Belgium) using macroseismic intensity data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4093, https://doi.org/10.5194/egusphere-egu22-4093, 2022.

15:45–15:50
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EGU22-10280
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ECS
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Virtual presentation
Michail Ravnalis, Charalampos Kkallas, Constantinos Papazachos, and Christos Papaioannou

At 27/09/2021, 06:17 (UTC) a strong ground motion with moment magnitude M6.0 occurred on the island of Crete, approximately 25km SE of the city of Heraklion, near Arkalochori. The highest macroseismic intensity value was observed in the area of the central part of the peripheral unit of Heraklion (i.e., in the area of the Municipality of Minoa Pediada) and had a value of IMM = VII. The earthquake was also felt in the islands of the southern and eastern Aegean up to areas of Attica. We collected macroseismic data from EMSC considering a significant number of macroseismic testimonies and available strong motion information. The main goal was to perform a combined interpretation between observed and synthetic macroseismic data. In order to predict the expected ground motion measurements, for example peak ground acceleration (PGA) and peak ground velocity (PGV), as a function of distance and magnitude we used the stochastic simulation approach. These simulations are performed with the EXSIM code (Motazedian and Atkinson, 2005), as described by Boore (2009) taking into account finite-fault effects in ground-motion modeling. Good knowledge of the detailed rupture process is essential for realistic simulations of strong ground motion. Earthquake relocations for this aftershock sequence suffer from poor knowledge of the local velocity structure, especially for the shallow part of the crust. This was an important factor in the case of this earthquake, as the permanent network is rather sparse in this area. We employed a Monte Carlo parametric search of the velocity model space, realized through an adapted neighborhood algorithm, as included in the Geopsy software, together with a conventional location code. In this approach, the regional 1D velocity model, together with appropriate station corrections, is simultaneously estimated (non-linear optimization) with the relocation of the complete seismic sequence. Finally, a good agreement of the spatial distribution of the initial and modeled simulated macroseismic intensities is observed, showing that can reliably reconstruct the main features of the damage distribution approach for this earthquake.

 

How to cite: Ravnalis, M., Kkallas, C., Papazachos, C., and Papaioannou, C.: Assessment of the macroseismic/strong-ground motion distribution of the 2021 Crete (Arkalochori) earthquake sequence using a finite fault stochastic simulation approach, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10280, https://doi.org/10.5194/egusphere-egu22-10280, 2022.

15:50–15:55
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EGU22-114
Anastasia Nekrasova and Vladimir Kossobokov

We present an original method for determining the seismic impact outside the elliptical focal zone of an earthquake. The technique is based on the research of N.V. Shebalin (1927-1996) and generalizes the work of Russian and foreign seismologists, taking into account anisotropic concentration of seismic impact observed in nature in the direction of the source stretch. The macroseismic intensity is approximated by the function of magnitude, hypocentral distance and direction of the main axis of the focal zone taking into account the existing regional characteristics including information on active faults and earthquake focal mechanisms in the study area. The methodology can be used both in the operational assessment of damage from an earthquake immediately after its occurrence, and for the purposes of long-term general seismic zoning. The study was carried out as part of the Russian Federation State task of Scientific Research Works on "Seismic hazard assessment, development and testing of earthquake prediction methods" (No. 0143-2019-0006).

How to cite: Nekrasova, A. and Kossobokov, V.: Seismic intensity outside the earthquake focal zone, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-114, https://doi.org/10.5194/egusphere-egu22-114, 2022.

Early warning and earthquake relater risks
15:55–16:05
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EGU22-13334
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ECS
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solicited
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Virtual presentation
Yan Zhang, Zhongliang Wu, Fabio Romanelli, Franco Vaccari, Changsheng Jiang, Shanghua Gao, Jiawei Li, Vladimir G. Kossobokov, and Giuliano F. Panza

For the concept of next-generation Early Earthquake Warning (EEW), the core idea is to combine EEW with seismic hazard assessment. In other words, to perform rapidly the computation of seismic hazard after the occurrence of an earthquake is detected and then to issue accurate warning, including lead time and potential seismic hazard level, to different end-users, e.g., railway system, working nuclear power plants and precision surgery in progress. We propose a scenario-based EEW by using the physics- and scenario-based hazard assessment, well known as Neo-deterministic Seismic Hazard Assessment (NDSHA). NDSHA can reliably compute the physically possible maximum ground motion response, including Maximum Credible Earthquakes (MCEs). In the framework of NDSHA, the general unit of processing time ranges from minutes to seconds, depending on the size of the study area and on the amount of computations. When the structural spectral information is available, the processing time significantly drops to a few seconds. Accordingly, a NDSHA scenario-based EEW relies on a hazard database, made by a collection of Modified Mercalli Intensity (MMI) maps, prepared and stored in advance. The establishment of such a hazard database is to consider all possible earthquake scenarios around target source zones based on now-available geophysical knowledge. Taking Xianshuihe (XSH) fault as an example, the six steps of the procedure to build the necessary hazard database could be the following: (1) definition of seismogenic zone; (2) definition of the first scenario source; (3) determination of source parameters; (4) determination of structural models; (5) computation of synthetic seismograms from the first source; (6) repeat (1) ~ (5), to travel all sources. Steps 1 to 6 allows us to obtain final (3264 in our case) results, i.e., the MMI maps for the adopted earthquake scenarios, which should be well representative of the potential earthquakes related to XSH.

As a first-order approximation in the construction of the hazard database, we assigned a characteristic focal mechanism for each cellular scenario earthquake. Once the hazard database is available, effective warning can be quickly issued to different end-users by selecting the suitable MMI map in the hazard database.

How to cite: Zhang, Y., Wu, Z., Romanelli, F., Vaccari, F., Jiang, C., Gao, S., Li, J., Kossobokov, V. G., and Panza, G. F.: Scenario-based Earthquake Early Warning empowered by NDSHA, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13334, https://doi.org/10.5194/egusphere-egu22-13334, 2022.

16:05–16:10
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EGU22-3695
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ECS
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On-site presentation
Sungmyung Bae, Yonggyu Choi, Youngseok Song, Joongmoo Byun, and Soon Jee Seol

Earthquake Early Warning System (EEW) is a technology that calculates earthquake parameter using P-wave that arrives earlier and warns the expected damage area before the arrival of destructive S wave. Therefore, many countries are operating EEW to mitigate damage from earthquake shaking. Especially an on-site EEW is drawn attention as it can reduce blind zones due to using only a single or minimum station. In the on-site EEW, it is important to quickly predict the seismic intensity, which indicates the degree of ground damage, response of structures and ground shaking felt by people at a given location, rather than information on the magnitude or distance of the earthquake.

In this study, we suggest a machine learning (ML) model that can directly estimate the seismic intensity scale from initial P-waveforms of three-component acceleration data measured at a single station. We used 1D-Convolutional Neural Networks (1D-CNN), which have been shown good performance in signal processing of speech and medical data which are similar to earthquake signals. K-Net and KiK-net datasets, recorded at stations in Japan, were used for training the ML model. Since the amount of data is enough and all of data are labeled with Japan Meteorological Agency Seismic Intensity Scale (IJMA), the datasets were used as training data in this study. The developed model produced fast and accurate results using only the three-component acceleration field data at a single station.

In order to test applicability of the trained model to the new dataset acquired from other regions, the trained model was applied to the STEAD data which were recorded at stations distributed globally. When the trained model was applied to STEAD data directly, the prediction results were worse than those of K-Net and KiK-net data. The reason is that the characteristics of the ground and waveforms are different depending on the region. Therefore, to solve this problem, transfer learning was applied, and only the parameters of a fully connected layer of pretrained ML model were fine-tuned using small number of both labeled target dataset and training dataset used for pretraining. Moreover, by considering the imbalance problem of the training data for transfer learning, it was able to obtain better prediction results. Ultimately, this study shows the pretrained model with a specific region dataset can provide reasonable prediction of seismic intensity to new dataset acquired from other regions using transfer learning.

How to cite: Bae, S., Choi, Y., Song, Y., Byun, J., and Seol, S. J.: Seismic Intensity Estimation using Machine Learning for on-site Earthquake Early Warning (EEW), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3695, https://doi.org/10.5194/egusphere-egu22-3695, 2022.

16:10–16:15
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EGU22-2526
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ECS
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Highlight
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On-site presentation
Federica Ghione, Steffen Mæland, Abdelghani Meslem, and Volker Oye

To evaluate potential human and economic losses in a seismic risk assessment, it is important to define an exposure model by defining building materials and characteristics. The common approach to develop an exposure model is to have a first overview of the area with Google Earth and to perform extensive fieldwork in representative areas of the city. This procedure is time and cost consuming, and it is also subject to personal interpretation. To mitigate these costs, a Convolutional Neural Network (CNN) is used to automatically identify the different building typologies in the city of Oslo, Norway, based on facade images taken from in-situ fieldwork and Google Street View.

The present article attempts to categorize Oslo’s building stock in five main building typologies: timber (T), unreinforced masonry (MUR), reinforced concrete (CR), composite (steel reinforced concrete) (SRC) and steel (S). This method shows good results for timber buildings with 91% accuracy score, but only 41% for steel reinforced concrete buildings. These variations can be explained by differences in the number of labelled images for each typology, comprising the training data, and differences in complexity between typologies.

This work is the first tentative to identify Norwegian building typologies: based on experts judgement, the five types observed in Oslo can be applicable at national level. In addition, this study shows that CNNs can significantly contribute in terms of developing a cost-effective exposure model.

How to cite: Ghione, F., Mæland, S., Meslem, A., and Oye, V.: Building typologies for Norway: a case study for Oslo using machine learning, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2526, https://doi.org/10.5194/egusphere-egu22-2526, 2022.

16:15–16:20
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EGU22-11648
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On-site presentation
Katalin Gribovszki, Piotr A. Bońkowski, Marcin A. Jaworski, and Zbigniew Zembaty

Recently, it has been argued that natural, intact stalagmites in caves give important constraints on seismic hazard since they have survived all earthquakes over their (rather long) life span. For this reason, applying detailed modelling methodologies to study the seismic motion of speleothems has special significance. Here we present a stalagmite-based study from the Little Carpathians of Slovakia, Plavecka priepast cave.

The seismic response of stalagmite is computed using a robust, a fully three-dimensional, Finite Element Method model calibrated from free vibration records by Hilbert-Huang modal extraction. It is demonstrated that the stalagmite vibrations consist of pairs of closely coupled flexural natural modes with a negligible role of vertical excitations.

An underground record of a moderate earthquake was applied to excite low intensity seismic vibrations. Particular attention was paid to observing the role of the vertical component of seismic ground motion. It is concluded that the failure mode of the stalagmite is driven by flexural vibrations. The safety margins of this stalagmite were assessed by analysing the tensile stress map from the seismic response computations. The location of the breaking point of the stalagmite is a result of a balance between the overturning bending moment and variations of horizontal cross-sections with height. The ultimate peak velocity of excitations equalling 3.2 mm/s is estimated.

The used input data and the animations are available on these web pages:

https://z.zembaty.po.opole.pl/SupplementaryStalagmite3Dview.html

https://z.zembaty.po.opole.pl/SupplementaryStalagmite.html

How to cite: Gribovszki, K., Bońkowski, P. A., Jaworski, M. A., and Zembaty, Z.: Seismic Vulnerability of a Slender Intact Stalagmite standing in a Karstic Cave, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11648, https://doi.org/10.5194/egusphere-egu22-11648, 2022.

16:20–16:25
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EGU22-2303
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On-site presentation
Antonella Peresan and Hany M. Hassan

During the last two decades, an operational procedure for time-dependent seismic hazard scenarios has been developed, which integrates fully formalized and validated earthquake forecasting information from pattern recognition analysis (e.g. by CN algorithm), with the realistic modelling of earthquake ground motion by the neo-deterministic approach (NDSHA). The proposed methodology permits to define, both at regional and local scale, a set of scenarios of ground motion for the time interval for the time interval in which a strong event is likely to occur within the alerted areas. When dealing with offshore large earthquakes occurrence, this integrated approach can be naturally extended to the definition of time-dependent tsunami scenarios, based on physical scenario models of tsunami waves.

CN forecasts for the Italian territory and its surroundings, as well as the corresponding time-dependent ground motion scenarios associated with the alarmed areas, are regularly updated since about two decades (Peresan, 2018, Geophysical Monograph Series, 234, pp. 149–172 and references therein). We review the results obtained so far by rigorous prospective testing of the developed procedure, including analysis of the statistical significance of issued forecasts. Special emphasis is placed on the recent earthquakes that occurred in the Adriatic region, which support validation of the applied methodologies, and evidence the opportunity of developing time-dependent tsunamis scenarios, by integrating forecast information with the modelling of tsunami waves propagation.

In this study, tsunami modelling is performed by the NAMI DANCE software (Yalciner et al., 2006, Middle East Technical University, Ankara, Turkey), which allows us accounting for seismic source properties, variable bathymetry, and non-linear effects in waves propagation. Urban scale hazard scenarios for selected coastal sites are developed considering different potential tsunamigenic sources of tectonic origin, located in the Central and Southern Adriatic Sea. The results from parametric studies accounting for possible sources related to historical events, as well as for yet unobserved extreme events, are considered for this purpose. Their verification against recent earthquakes, allows us assessing the relevance of space-time information and uncertainties on source parameters, and their possible operational contribution towards effective tsunami warning system for the Adriatic Sea and in the whole Mediterranean area. 

How to cite: Peresan, A. and Hassan, H. M.: Time-dependent earthquake and tsunami hazard scenarios for the Adriatic region, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2303, https://doi.org/10.5194/egusphere-egu22-2303, 2022.

16:25–16:40