Articles | Volume 24, issue 11
https://doi.org/10.5194/nhess-24-4199-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-24-4199-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 Nov 2024
Research article |
| 28 Nov 2024
| 28 Nov 2024
Probabilistic seismic hazard assessment of Sweden
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
Centre of Natural Hazards and Disaster Science, Uppsala University, Uppsala, Sweden
Björn Lund
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
Centre of Natural Hazards and Disaster Science, Uppsala University, Uppsala, Sweden
Roland Roberts
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
Centre of Natural Hazards and Disaster Science, Uppsala University, Uppsala, Sweden
Related authors
No articles found.
Irene DeFelipe, Juan Alcalde, Monika Ivandic, David Martí, Mario Ruiz, Ignacio Marzán, Jordi Diaz, Puy Ayarza, Imma Palomeras, Jose-Luis Fernandez-Turiel, Cecilia Molina, Isabel Bernal, Larry Brown, Roland Roberts, and Ramon Carbonell
Earth Syst. Sci. Data, 13, 1053–1071, https://doi.org/10.5194/essd-13-1053-2021, https://doi.org/10.5194/essd-13-1053-2021, 2021
Short summary
Short summary
Seismic data provide critical information about the structure of the lithosphere, and their preservation is essential for innovative research reusing data. The Seismic DAta REpository (SeisDARE) comprises legacy and recently acquired seismic data in the Iberian Peninsula and Morocco. This database has been built by a network of different institutions that promote multidisciplinary research. We aim to make seismic data easily available to the research, industry, and educational communities.
Alireza Malehmir, Magnus Andersson, Suman Mehta, Bojan Brodic, Raymond Munier, Joachim Place, Georgiana Maries, Colby Smith, Jochen Kamm, Mehrdad Bastani, Henrik Mikko, and Björn Lund
Solid Earth, 7, 509–527, https://doi.org/10.5194/se-7-509-2016, https://doi.org/10.5194/se-7-509-2016, 2016
Short summary
Short summary
Glacially induced intraplate faults are conspicuous and confined to northern parts of Fennoscandia. Here we report a multidisciplinary geophysical investigation delineating the newly inferred lidar imagery data from the Bollnäs post-glacial fault in central Sweden. The geophysical data consistently support the presence of a fault in the crystalline basement associated with an earlier structure, possibly a deformation zone that reactive after the Weichselian deglaciation.
O. Ahmadi, C. Juhlin, M. Ask, and B. Lund
Solid Earth, 6, 621–632, https://doi.org/10.5194/se-6-621-2015, https://doi.org/10.5194/se-6-621-2015, 2015
Short summary
Short summary
The Pärvie fault system extends up to 155km, and its scarps have offsets of tens of meters at the surface in northern Sweden. These fault scarps are inferred to have formed during earthquakes with magnitudes up to 8 at the time of the last deglaciation. In this study, we have mapped the fault system to deeper levels, by a new 22km long 2-D seismic reflection profile. Based on the present and previous seismic data, locations for future boreholes for drilling into the fault system are proposed.
P. Schmidt, B. Lund, J-O. Näslund, and J. Fastook
Solid Earth, 5, 371–388, https://doi.org/10.5194/se-5-371-2014, https://doi.org/10.5194/se-5-371-2014, 2014
Related subject area
Earthquake Hazards
A grid-level fixed-asset model developed for China from 1951 to 2020
Towards a harmonized operational earthquake forecasting model for Europe
Modeling seismic hazard and landslide occurrence probabilities in northwestern Yunnan, China: exploring complex fault systems with multi-segment rupturing in a block rotational tectonic zone
Development of a regional probabilistic seismic hazard model for Central Asia
Computing the time-dependent activity rate using non-declustered and declustered catalogues – a first step towards time-dependent seismic hazard calculations for operational earthquake forecasting
Analysis of borehole strain anomalies before the 2017 Jiuzhaigou Ms 7.0 earthquake based on a graph neural network
Testing the 2020 European Seismic Hazard Model (ESHM20) against observations from Romania
Sedimentary record of historical seismicity in a small, southern Oregon lake
A 2700-year record of Cascadia megathrust and crustal/slab earthquakes from Acorn Woman Lakes, Oregon
Correlation between seismic activity and acoustic emission on the basis of in situ monitoring
The European Fault-Source Model 2020 (EFSM20): geologic input data for the European Seismic Hazard Model 2020
2021 Alaska earthquake: entropy approach to its precursors and aftershock regimes
Strategies for comparison of modern probabilistic seismic hazard models and insights from the Germany and France border region
The Earthquake Risk Model of Switzerland, ERM-CH23
Estimating ground motion intensities using simulation-based estimates of local crustal seismic response
Co- and postseismic subaquatic evidence for prehistoric fault activity near Coyhaique, Aysén Region, Chile
Forearc crustal faults as tsunami sources in the upper plate of the Lesser Antilles subduction zone: the case study of the Morne Piton fault system
The 2020 European Seismic Hazard Model: overview and results
Dynamic Fragility of a Slender Rock Pillar in a Sedimentary Rock Mass – from rock mechanics to seismic hazard
Risk-informed representative earthquake scenarios for Valparaíso and Viña del Mar, Chile
Harmonizing seismicity information in Central Asian countries: earthquake catalogue and active faults
Comparing components for seismic risk modelling using data from the 2019 Le Teil (France) earthquake
Conversion relationships between Modified Mercalli Intensity and Peak Ground Acceleration for historical shallow crustal earthquakes in Mexico
Consistency between the Strain Rate Model and ESHM20 Earthquake Rate Forecast in Europe: insights for seismic hazard
Modelling seismic ground motion and its uncertainty in different tectonic contexts: challenges and application to the 2020 European Seismic Hazard Model (ESHM20)
Scoring and ranking probabilistic seismic hazard models: an application based on macroseismic intensity data
Lesser Antilles Seismotectonic Zoning Model for Seismic Hazard Assessment
A dense micro-electromechanical system (MEMS)-based seismic network in populated areas: rapid estimation of exposure maps in Trentino (NE Italy)
Exploring inferred geomorphological sediment thickness as a new site proxy to predict ground-shaking amplification at regional scale: application to Europe and eastern Türkiye
Surface rupture kinematics of the 2020 Mw 6.6 Masbate (Philippines) earthquake determined from optical and radar data
The influence of aftershocks on seismic hazard analysis: a case study from Xichang and the surrounding areas
Characteristics and mechanisms of near-surface negative atmospheric electric field anomalies preceding the 5 September 2022, Ms 6.8 Luding earthquake in China
Seismogenic depth and seismic coupling estimation in the transition zone between Alps, Dinarides and Pannonian Basin for the new Slovenian seismic hazard model
Towards a dynamic earthquake risk framework for Switzerland
Understanding flow characteristics from tsunami deposits at Odaka, Joban Coast, using a deep neural network (DNN) inverse model
Spring water anomalies before two consecutive earthquakes (Mw 7.7 and Mw 7.6) in Kahramanmaraş (Türkiye) on 6 February 2023
The quest for reference stations at the National Observatory of Athens, Greece
Update on the seismogenic potential of the Upper Rhine Graben southern region
Earthquake forecasting model for Albania: the area source model and the smoothing model
The footprint of a historical paleoearthquake: the sixth-century-CE event in the European western Southern Alps
Seismic background noise levels in the Italian strong-motion network
Testing machine learning models for heuristic building damage assessment applied to the Italian Database of Observed Damage (DaDO)
The seismic hazard from the Lembang Fault, Indonesia, derived from InSAR and GNSS data
Rapid estimation of seismic intensities by analyzing early aftershock sequences using the robust locally weighted regression program (LOWESS)
Towards improving the spatial testability of aftershock forecast models
Accounting for path and site effects in spatial ground-motion correlation models using Bayesian inference
Seismogenic potential and tsunami threat of the strike-slip Carboneras fault in the western Mediterranean from physics-based earthquake simulations
Earthquake hazard characterization by using entropy: application to northern Chilean earthquakes
Seismic risk scenarios for the residential buildings in the Sabana Centro province in Colombia
Looking for undocumented earthquake effects: a probabilistic analysis of Italian macroseismic data
Danhua Xin, James Edward Daniell, Zhenguo Zhang, Friedemann Wenzel, Shaun Shuxun Wang, and Xiaofei Chen
Nat. Hazards Earth Syst. Sci., 25, 1597–1620, https://doi.org/10.5194/nhess-25-1597-2025, https://doi.org/10.5194/nhess-25-1597-2025, 2025
Short summary
Short summary
A high-resolution fixed-asset model can help improve the accuracy of earthquake loss assessment. We develop a grid-level fixed-asset model for China from 1951 to 2020. We first compile the provincial-level fixed asset from yearbook-related statistics. Then, this dataset is disaggregated into 1 km × 1 km grids by using multiple remote sensing data as the weight indicator. We find that the fixed-asset value increased rapidly after the 1980s and reached CNY 589.31 trillion in 2020.
Marta Han, Leila Mizrahi, and Stefan Wiemer
Nat. Hazards Earth Syst. Sci., 25, 991–1012, https://doi.org/10.5194/nhess-25-991-2025, https://doi.org/10.5194/nhess-25-991-2025, 2025
Short summary
Short summary
Relying on recent accomplishments of collecting and harmonizing data by the 2020 European Seismic Hazard Model (ESHM20) and leveraging advancements in state-of-the-art earthquake forecasting methods, we develop a harmonized earthquake forecasting model for Europe. We propose several model variants and test them on training data for consistency and on a 7-year testing period against each other, as well as against both a time-independent benchmark and a global time-dependent benchmark.
Jia Cheng, Chong Xu, Xiwei Xu, Shimin Zhang, and Pengyu Zhu
Nat. Hazards Earth Syst. Sci., 25, 857–877, https://doi.org/10.5194/nhess-25-857-2025, https://doi.org/10.5194/nhess-25-857-2025, 2025
Short summary
Short summary
The northwestern Yunnan region (NWYR), with a complex network of active faults, presents significant seismic hazards such as multi-segment ruptures and landslides. This article introduces a new seismic hazard model which integrates fault slip parameters to assess the risks associated with multi-segment ruptures. The results reveal the intricate relationship between these ruptures and the regional small block rotation induced by regional low-crustal flow and gravitational collapse.
Valerio Poggi, Stefano Parolai, Natalya Silacheva, Anatoly Ischuk, Kanatbek Abdrakhmatov, Zainalobudin Kobuliev, Vakhitkhan Ismailov, Roman Ibragimov, Japar Karaev, Paola Ceresa, Marco Santulin, and Paolo Bazzurro
Nat. Hazards Earth Syst. Sci., 25, 817–842, https://doi.org/10.5194/nhess-25-817-2025, https://doi.org/10.5194/nhess-25-817-2025, 2025
Short summary
Short summary
A regionally consistent probabilistic risk assessment for multiple hazards and assets was developed under the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) programme, supported by the European Union, the World Bank, and the Global Facility for Disaster Reduction and Recovery. This paper outlines the preparation of the source model and presents key results of the probabilistic earthquake hazard analysis for the Central Asian countries.
David Montiel-López, Sergio Molina, Juan José Galiana-Merino, Igor Gómez, Alireza Kharazian, Juan Luis Soler-Llorens, José Antonio Huesca-Tortosa, Arianna Guardiola-Villora, and Gonzalo Ortuño-Sáez
Nat. Hazards Earth Syst. Sci., 25, 515–539, https://doi.org/10.5194/nhess-25-515-2025, https://doi.org/10.5194/nhess-25-515-2025, 2025
Short summary
Short summary
We presents a comparison between different methods of computing the seismic activity rate in the time-dependent annual probability of exceedance (TD-APE) for a given earthquake in two areas: Italy (high seismicity) and Spain (moderate seismicity). Important changes in the TD-APE are seen in Italy before the L'Aquila earthquake, which can be related to foreshocks. In the case of Spain subtle changes are seen before some earthquakes. This approach could enable operational earthquake forecasting.
Chenyang Li, Changfeng Qin, Jie Zhang, Yu Duan, and Chengquan Chi
Nat. Hazards Earth Syst. Sci., 25, 231–245, https://doi.org/10.5194/nhess-25-231-2025, https://doi.org/10.5194/nhess-25-231-2025, 2025
Short summary
Short summary
In this study, we advance the field of earthquake prediction by introducing a pre-seismic anomaly extraction method based on the structure of a graph WaveNet model, which reveals the temporal correlation and spatial correlation of the strain observation data from different boreholes prior to the occurrence of an earthquake event.
Elena F. Manea, Laurentiu Danciu, Carmen O. Cioflan, Dragos Toma-Danila, and Matthew C. Gerstenberger
Nat. Hazards Earth Syst. Sci., 25, 1–12, https://doi.org/10.5194/nhess-25-1-2025, https://doi.org/10.5194/nhess-25-1-2025, 2025
Short summary
Short summary
We test and evaluate the results of the 2020 European Seismic Hazard Model (ESHM20) against observations spanning a few centuries at 12 cities in Romania. The full distributions of the hazard curves at the given locations were considered, and the testing was performed for two relevant peak ground acceleration (PGA) values. Our analysis suggests that the observed exceedance rates for the selected PGA levels are consistent with ESHM20 estimates.
Ann E. Morey, Mark D. Shapley, Daniel G. Gavin, Alan R. Nelson, and Chris Goldfinger
Nat. Hazards Earth Syst. Sci., 24, 4523–4561, https://doi.org/10.5194/nhess-24-4523-2024, https://doi.org/10.5194/nhess-24-4523-2024, 2024
Short summary
Short summary
Disturbance events from historical sediments from a small lake in Oregon were evaluated to determine if Cascadia megathrust earthquakes are uniquely identifiable. Geochemical provenance data identify two likely Cascadia earthquakes, one from 1700 CE and the other from 1873 CE. A crustal earthquake deposit and flood deposits were also uniquely identified, suggesting that small Cascadia lakes are good recorders of megathrust earthquakes and other disturbances.
Ann E. Morey and Chris Goldfinger
Nat. Hazards Earth Syst. Sci., 24, 4563–4584, https://doi.org/10.5194/nhess-24-4563-2024, https://doi.org/10.5194/nhess-24-4563-2024, 2024
Short summary
Short summary
This study uses the characteristics from a deposit attributed to the 1700 CE Cascadia earthquake to identify other subduction-earthquake deposits in sediments from two lakes located near the California–Oregon border. Seven deposits were identified in these records, and an age–depth model suggests that these correlate in time to the largest Cascadia earthquakes preserved in the offshore record, suggesting that inland lakes can be good recorders of Cascadia earthquakes.
Zhiwen Zhu, Zihan Jiang, Federico Accornero, and Alberto Carpinteri
Nat. Hazards Earth Syst. Sci., 24, 4133–4143, https://doi.org/10.5194/nhess-24-4133-2024, https://doi.org/10.5194/nhess-24-4133-2024, 2024
Short summary
Short summary
Since April 2023, an in situ experiment in a granite tunnel in Southeast China has been revealing strong correlations between acoustic emission signals and seismic activity. Acoustic emission bursts precede seismic events by approximately 17 h, with a notable decline in the b value and natural-time variance κ1. This research provides new evidence that acoustic emission can serve as an effective earthquake precursor.
Roberto Basili, Laurentiu Danciu, Céline Beauval, Karin Sesetyan, Susana Pires Vilanova, Shota Adamia, Pierre Arroucau, Jure Atanackov, Stéphane Baize, Carolina Canora, Riccardo Caputo, Michele Matteo Cosimo Carafa, Edward Marc Cushing, Susana Custódio, Mine Betul Demircioglu Tumsa, João C. Duarte, Athanassios Ganas, Julián García-Mayordomo, Laura Gómez de la Peña, Eulàlia Gràcia, Petra Jamšek Rupnik, Hervé Jomard, Vanja Kastelic, Francesco Emanuele Maesano, Raquel Martín-Banda, Sara Martínez-Loriente, Marta Neres, Hector Perea, Barbara Šket Motnikar, Mara Monica Tiberti, Nino Tsereteli, Varvara Tsironi, Roberto Vallone, Kris Vanneste, Polona Zupančič, and Domenico Giardini
Nat. Hazards Earth Syst. Sci., 24, 3945–3976, https://doi.org/10.5194/nhess-24-3945-2024, https://doi.org/10.5194/nhess-24-3945-2024, 2024
Short summary
Short summary
This study presents the European Fault-Source Model 2020 (EFSM20), a dataset of 1248 geologic crustal faults and four subduction systems, each having the necessary parameters to forecast long-term earthquake occurrences in the European continent. This dataset constituted one of the main inputs for the recently released European Seismic Hazard Model 2020, a key instrument to mitigate seismic risk in Europe. EFSM20 adopts recognized open-standard formats, and it is openly accessible and reusable.
Eugenio E. Vogel, Denisse Pastén, Gonzalo Saravia, Michel Aguilera, and Antonio Posadas
Nat. Hazards Earth Syst. Sci., 24, 3895–3906, https://doi.org/10.5194/nhess-24-3895-2024, https://doi.org/10.5194/nhess-24-3895-2024, 2024
Short summary
Short summary
For the first time, an entropy analysis has been performed in Alaska, a seismic-rich region located in a subduction zone that shows non-trivial behavior: the subduction arc changes seismic activity from the eastern zone to the western zone, showing a decrease in this activity along the subduction zone. This study shows how an entropy approach can help us understand seismicity in subduction zones.
Graeme Weatherill, Fabrice Cotton, Guillaume Daniel, Irmela Zentner, Pablo Iturrieta, and Christian Bosse
Nat. Hazards Earth Syst. Sci., 24, 3755–3787, https://doi.org/10.5194/nhess-24-3755-2024, https://doi.org/10.5194/nhess-24-3755-2024, 2024
Short summary
Short summary
New generations of seismic hazard models are developed with sophisticated approaches to quantify uncertainties in our knowledge of earthquake processes. To understand why and how recent state-of-the-art seismic hazard models for France, Germany, and Europe differ despite similar underlying assumptions, we present a systematic approach to investigate model-to-model differences and to quantify and visualise them while accounting for their respective uncertainties.
Athanasios N. Papadopoulos, Philippe Roth, Laurentiu Danciu, Paolo Bergamo, Francesco Panzera, Donat Fäh, Carlo Cauzzi, Blaise Duvernay, Alireza Khodaverdian, Pierino Lestuzzi, Ömer Odabaşi, Ettore Fagà, Paolo Bazzurro, Michèle Marti, Nadja Valenzuela, Irina Dallo, Nicolas Schmid, Philip Kästli, Florian Haslinger, and Stefan Wiemer
Nat. Hazards Earth Syst. Sci., 24, 3561–3578, https://doi.org/10.5194/nhess-24-3561-2024, https://doi.org/10.5194/nhess-24-3561-2024, 2024
Short summary
Short summary
The Earthquake Risk Model of Switzerland (ERM-CH23), released in early 2023, is the culmination of a multidisciplinary effort aiming to achieve, for the first time, a comprehensive assessment of the potential consequences of earthquakes on the Swiss building stock and population. ERM-CH23 provides risk estimates for various impact metrics, ranging from economic loss as a result of damage to buildings and their contents to human losses, such as deaths, injuries, and displaced population.
Himanshu Agrawal and John McCloskey
Nat. Hazards Earth Syst. Sci., 24, 3519–3536, https://doi.org/10.5194/nhess-24-3519-2024, https://doi.org/10.5194/nhess-24-3519-2024, 2024
Short summary
Short summary
Rapidly expanding cities in earthquake-prone regions of the Global South often lack seismic event records, hindering accurate ground motion predictions for hazard assessment. Our study demonstrates that, despite these limitations, reliable predictions can be made using simulation-based methods for small (sub)urban units undergoing rapid development. High-resolution local geological data can reveal spatial variability in ground motions, aiding effective risk mitigation.
Morgan Vervoort, Katleen Wils, Kris Vanneste, Roberto Urrutia, Mario Pino, Catherine Kissel, Marc De Batist, and Maarten Van Daele
Nat. Hazards Earth Syst. Sci., 24, 3401–3421, https://doi.org/10.5194/nhess-24-3401-2024, https://doi.org/10.5194/nhess-24-3401-2024, 2024
Short summary
Short summary
This study identifies a prehistoric earthquake around 4400 years ago near the city of Coyhaique (Aysén Region, Chilean Patagonia) and illustrates the potential seismic hazard in the region. We found deposits in lakes and a fjord that can be related to subaquatic and onshore landslides, all with a similar age, indicating that they were most likely caused by an earthquake. Through modeling we found that this was an earthquake of magnitude 6.3 to 7.0 on a fault near the city of Coyhaique.
Melody Philippon, Jean Roger, Jean-Frédéric Lebrun, Isabelle Thinon, Océane Foix, Stéphane Mazzotti, Marc-André Gutscher, Leny Montheil, and Jean-Jacques Cornée
Nat. Hazards Earth Syst. Sci., 24, 3129–3154, https://doi.org/10.5194/nhess-24-3129-2024, https://doi.org/10.5194/nhess-24-3129-2024, 2024
Short summary
Short summary
Using novel geophysical datasets, we reassess the slip rate of the Morne Piton fault (Lesser Antilles) at 0.2 mm yr−1 by dividing by four previous estimations and thus increasing the earthquake time recurrence and lowering the associated hazard. We evaluate a plausible magnitude for a potential seismic event of Mw 6.5 ± 0.5. Our multi-segment tsunami model representative of the worst-case scenario gives an overview of tsunami generation if all the fault segments ruptured together.
Laurentiu Danciu, Domenico Giardini, Graeme Weatherill, Roberto Basili, Shyam Nandan, Andrea Rovida, Céline Beauval, Pierre-Yves Bard, Marco Pagani, Celso G. Reyes, Karin Sesetyan, Susana Vilanova, Fabrice Cotton, and Stefan Wiemer
Nat. Hazards Earth Syst. Sci., 24, 3049–3073, https://doi.org/10.5194/nhess-24-3049-2024, https://doi.org/10.5194/nhess-24-3049-2024, 2024
Short summary
Short summary
The 2020 European Seismic Hazard Model (ESHM20) is the latest seismic hazard assessment update for the Euro-Mediterranean region. This state-of-the-art model delivers a broad range of hazard results, including hazard curves, maps, and uniform hazard spectra. ESHM20 provides two hazard maps as informative references in the next update of the European Seismic Design Code (CEN EC8), and it also provides a key input to the first earthquake risk model for Europe.
Alaa Jbara and Michael Tsesarsky
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-150, https://doi.org/10.5194/nhess-2024-150, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
Fragile geological features are the only empirical data to validate seismic hazard analysis over prehistoric timescales. We present a fragility analysis of a 42 m high rock pillar. Based on LiDAR scanning and in-situ rock elastic modulus measurements, we developed an accurate finite element model. The model was validated by comparing computational modal analysis with in-situ measurements of natural vibrations. Dynamic fragility analysis was used to challenge regional seismic hazard estimates.
Hugo Rosero-Velásquez, Mauricio Monsalve, Juan Camilo Gómez Zapata, Elisa Ferrario, Alan Poulos, Juan Carlos de la Llera, and Daniel Straub
Nat. Hazards Earth Syst. Sci., 24, 2667–2687, https://doi.org/10.5194/nhess-24-2667-2024, https://doi.org/10.5194/nhess-24-2667-2024, 2024
Short summary
Short summary
Seismic risk management uses reference earthquake scenarios, but the criteria for selecting them do not always consider consequences for exposed assets. Hence, we adopt a definition of representative scenarios associated with a return period and loss level to select such scenarios among a large set of possible earthquakes. We identify the scenarios for the residential-building stock and power supply in Valparaíso and Viña del Mar, Chile. The selected scenarios depend on the exposed assets.
Valerio Poggi, Stefano Parolai, Natalya Silacheva, Anatoly Ischuk, Kanatbek Abdrakhmatov, Zainalobudin Kobuliev, Vakhitkhan Ismailov, Roman Ibragimov, Japar Karaev, Paola Ceresa, and Paolo Bazzurro
Nat. Hazards Earth Syst. Sci., 24, 2597–2613, https://doi.org/10.5194/nhess-24-2597-2024, https://doi.org/10.5194/nhess-24-2597-2024, 2024
Short summary
Short summary
As part of the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) programme, funded by the European Union in collaboration with the World Bank and GFDRR, a regionally consistent probabilistic multi-hazard and multi-asset risk assessment has been developed. This paper describes the preparation of the input datasets (earthquake catalogue and active-fault database) required for the implementation of the probabilistic seismic hazard model.
Konstantinos Trevlopoulos, Pierre Gehl, Caterina Negulescu, Helen Crowley, and Laurentiu Danciu
Nat. Hazards Earth Syst. Sci., 24, 2383–2401, https://doi.org/10.5194/nhess-24-2383-2024, https://doi.org/10.5194/nhess-24-2383-2024, 2024
Short summary
Short summary
The models used to estimate the probability of exceeding a level of earthquake damage are essential to the reduction of disasters. These models consist of components that may be tested individually; however testing these types of models as a whole is challenging. Here, we use observations of damage caused by the 2019 Le Teil earthquake and estimations from other models to test components of seismic risk models.
Quetzalcoatl Rodríguez-Pérez and F. Ramón Zúñiga
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-92, https://doi.org/10.5194/nhess-2024-92, 2024
Preprint withdrawn
Short summary
Short summary
Seismic intensity reflects earthquake damage, although this parameter is often subjective. On the other hand, peak acceleration values are a direct measure of earthquake effects. Seismic intensity was used to describe historical earthquakes, and its use is rare today. For this reason, it is important to have a relationship between these parameters of strong movements in order to predict the acceleration of historical earthquakes.
Bénédicte Donniol Jouve, Anne Socquet, Céline Beauval, Jesús Piña Valdès, and Laurentiu Danciu
EGUsphere, https://doi.org/10.5194/egusphere-2024-787, https://doi.org/10.5194/egusphere-2024-787, 2024
Short summary
Short summary
This research investigates how geodetic monitoring enhances accuracy in seismic hazard assessment. By utilizing geodetic strain rate maps for Europe and the ESHM20 source model, we compare geodetic and seismic moment rates across the continent while addressing associated uncertainties. Our analysis reveals primary compatibility in high-activity zones. In well-constrained regions of lower activity, we also observed an overlap in the distribution of seismic and geodetic moments.
Graeme Weatherill, Sreeram Reddy Kotha, Laurentiu Danciu, Susana Vilanova, and Fabrice Cotton
Nat. Hazards Earth Syst. Sci., 24, 1795–1834, https://doi.org/10.5194/nhess-24-1795-2024, https://doi.org/10.5194/nhess-24-1795-2024, 2024
Short summary
Short summary
The ground motion models (GMMs) selected for the 2020 European Seismic Hazard Model (ESHM20) and their uncertainties require adaptation to different tectonic environments. Using insights from new data, local experts and developments in the scientific literature, we further calibrate the ESHM20 GMM logic tree to capture previously unmodelled regional variation. We also propose a new scaled-backbone logic tree for application to Europe's subduction zones and the Vrancea deep seismic source.
Vera D'Amico, Francesco Visini, Andrea Rovida, Warner Marzocchi, and Carlo Meletti
Nat. Hazards Earth Syst. Sci., 24, 1401–1413, https://doi.org/10.5194/nhess-24-1401-2024, https://doi.org/10.5194/nhess-24-1401-2024, 2024
Short summary
Short summary
We propose a scoring strategy to rank multiple models/branches of a probabilistic seismic hazard analysis (PSHA) model that could be useful to consider specific requests from stakeholders responsible for seismic risk reduction actions. In fact, applications of PSHA often require sampling a few hazard curves from the model. The procedure is introduced through an application aimed to score and rank the branches of a recent Italian PSHA model according to their fit with macroseismic intensity data.
Oceane Foix, Stéphane Mazzotti, Hervé Jomard, Didier Bertil, and the Lesser Antilles Working Group
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-53, https://doi.org/10.5194/nhess-2024-53, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
By analyzing historical and instrumental seismic data, fault knowledge and geodetic measurements, we provide a new understanding of seismic hazard in the Lesser Antilles via seismotectonic zoning. We propose new models that can have a significant impact on seismic hazard assessment, such as the inclusion of mantle wedge seismicity, volcanic seismicity and a complete revision of the subduction interface zoning.
Davide Scafidi, Alfio Viganò, Jacopo Boaga, Valeria Cascone, Simone Barani, Daniele Spallarossa, Gabriele Ferretti, Mauro Carli, and Giancarlo De Marchi
Nat. Hazards Earth Syst. Sci., 24, 1249–1260, https://doi.org/10.5194/nhess-24-1249-2024, https://doi.org/10.5194/nhess-24-1249-2024, 2024
Short summary
Short summary
Our paper concerns the use of a dense network of low-cost seismic accelerometers in populated areas to achieve rapid and reliable estimation of exposure maps in Trentino (northeast Italy). These additional data, in conjunction with the automatic monitoring procedure, allow us to obtain dense measurements which only rely on actual recorded data, avoiding the use of ground motion prediction equations. This leads to a more reliable picture of the actual ground shaking.
Karina Loviknes, Fabrice Cotton, and Graeme Weatherill
Nat. Hazards Earth Syst. Sci., 24, 1223–1247, https://doi.org/10.5194/nhess-24-1223-2024, https://doi.org/10.5194/nhess-24-1223-2024, 2024
Short summary
Short summary
Earthquake ground shaking can be strongly affected by local geology and is often amplified by soft sediments. In this study, we introduce a global geomorphological model for sediment thickness as a protentional parameter for predicting this site amplification. The results show that including geology and geomorphology in site-amplification predictions adds important value and that global or regional models for sediment thickness from fields beyond engineering seismology are worth considering.
Khelly Shan Sta. Rita, Sotiris Valkaniotis, and Alfredo Mahar Francisco Lagmay
Nat. Hazards Earth Syst. Sci., 24, 1135–1161, https://doi.org/10.5194/nhess-24-1135-2024, https://doi.org/10.5194/nhess-24-1135-2024, 2024
Short summary
Short summary
The ground movement and rupture produced by the 2020 Masbate earthquake in the Philippines were studied using satellite data. We highlight the importance of the complementary use of optical and radar datasets. The slip measurements and field observations helped improve our understanding of the seismotectonics of the region, which is critical for seismic hazard studies.
Qing Wu, Guijuan Lai, Jian Wu, and Jinmeng Bi
Nat. Hazards Earth Syst. Sci., 24, 1017–1033, https://doi.org/10.5194/nhess-24-1017-2024, https://doi.org/10.5194/nhess-24-1017-2024, 2024
Short summary
Short summary
Aftershocks are typically ignored for traditional probabilistic seismic hazard analyses, which underestimate the seismic hazard to some extent and may cause potential risks. A probabilistic seismic hazard analysis based on the Monte Carlo method was combined with the Omi–Reasenberg–Jones model to systematically study how aftershocks impact seismic hazard analyses. The influence of aftershocks on probabilistic seismic hazard analysis can exceed 50 %.
Lixin Wu, Xiao Wang, Yuan Qi, Jingchen Lu, and Wenfei Mao
Nat. Hazards Earth Syst. Sci., 24, 773–789, https://doi.org/10.5194/nhess-24-773-2024, https://doi.org/10.5194/nhess-24-773-2024, 2024
Short summary
Short summary
The atmospheric electric field (AEF) is the bridge connecting the surface charges and atmospheric particle changes before an earthquake, which is essential for the study of the coupling process between the coversphere and atmosphere caused by earthquakes. This study discovers AEF anomalies before the Luding earthquake in 2022 and clarifies the relationship between the surface changes and atmosphere changes possibly caused by the earthquake.
Polona Zupančič, Barbara Šket Motnikar, Michele M. C. Carafa, Petra Jamšek Rupnik, Mladen Živčić, Vanja Kastelic, Gregor Rajh, Martina Čarman, Jure Atanackov, and Andrej Gosar
Nat. Hazards Earth Syst. Sci., 24, 651–672, https://doi.org/10.5194/nhess-24-651-2024, https://doi.org/10.5194/nhess-24-651-2024, 2024
Short summary
Short summary
We considered two parameters that affect seismic hazard assessment in Slovenia. The first parameter we determined is the thickness of the lithosphere's section where earthquakes are generated. The second parameter is the activity of each fault, which is expressed by its average displacement per year (slip rate). Since the slip rate can be either seismic or aseismic, we estimated both components. This analysis was based on geological and seismological data and was validated through comparisons.
Maren Böse, Laurentiu Danciu, Athanasios Papadopoulos, John Clinton, Carlo Cauzzi, Irina Dallo, Leila Mizrahi, Tobias Diehl, Paolo Bergamo, Yves Reuland, Andreas Fichtner, Philippe Roth, Florian Haslinger, Frédérick Massin, Nadja Valenzuela, Nikola Blagojević, Lukas Bodenmann, Eleni Chatzi, Donat Fäh, Franziska Glueer, Marta Han, Lukas Heiniger, Paulina Janusz, Dario Jozinović, Philipp Kästli, Federica Lanza, Timothy Lee, Panagiotis Martakis, Michèle Marti, Men-Andrin Meier, Banu Mena Cabrera, Maria Mesimeri, Anne Obermann, Pilar Sanchez-Pastor, Luca Scarabello, Nicolas Schmid, Anastasiia Shynkarenko, Bozidar Stojadinović, Domenico Giardini, and Stefan Wiemer
Nat. Hazards Earth Syst. Sci., 24, 583–607, https://doi.org/10.5194/nhess-24-583-2024, https://doi.org/10.5194/nhess-24-583-2024, 2024
Short summary
Short summary
Seismic hazard and risk are time dependent as seismicity is clustered and exposure can change rapidly. We are developing an interdisciplinary dynamic earthquake risk framework for advancing earthquake risk mitigation in Switzerland. This includes various earthquake risk products and services, such as operational earthquake forecasting and early warning. Standardisation and harmonisation into seamless solutions that access the same databases, workflows, and software are a crucial component.
Rimali Mitra, Hajime Naruse, and Tomoya Abe
Nat. Hazards Earth Syst. Sci., 24, 429–444, https://doi.org/10.5194/nhess-24-429-2024, https://doi.org/10.5194/nhess-24-429-2024, 2024
Short summary
Short summary
This study estimates the behavior of the 2011 Tohoku-oki tsunami from its deposit distributed in the Joban coastal area. In this study, the flow characteristics of the tsunami were reconstructed using the DNN (deep neural network) inverse model, suggesting that the tsunami inundation occurred in the very high-velocity condition.
Sedat İnan, Hasan Çetin, and Nurettin Yakupoğlu
Nat. Hazards Earth Syst. Sci., 24, 397–409, https://doi.org/10.5194/nhess-24-397-2024, https://doi.org/10.5194/nhess-24-397-2024, 2024
Short summary
Short summary
Two devastating earthquakes, Mw 7.7 and Mw 7.6, occurred in Türkiye on 6 February 2023. We obtained commercially bottled waters from two springs, 100 km from the epicenter of Mw 7.7. Samples of the first spring emanating from fault zone in hard rocks showed positive anomalies in major ions lasting for 6 months before the earthquake. Samples from the second spring accumulated in an alluvium deposit showed no anomalies. We show that pre-earthquake anomalies are geologically site-dependent.
Olga-Joan Ktenidou, Antonia Papageorgiou, Erion-Vasilis Pikoulis, Spyros Liakopoulos, Fevronia Gkika, Ziya Cekinmez, Panagiotis Savvaidis, Kalliopi Fragouli, and Christos P. Evangelidis
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-233, https://doi.org/10.5194/nhess-2023-233, 2024
Revised manuscript accepted for NHESS
Short summary
Short summary
Greek seismic data are valuable in European and even global databases, due to its high seismicity and numerous seismic stations. Seismic data coming from stations that lie on rock (i.e., not soil) sits are particularly valuable in seismology to define reference ground conditions and ground motions. However, little knowledge exists yet on how rock stations in Greece behave. This is the first time the network of the National Observatory is studied systematically to reveal reference stations.
Sylvain Michel, Clara Duverger, Laurent Bollinger, Jorge Jara, and Romain Jolivet
Nat. Hazards Earth Syst. Sci., 24, 163–177, https://doi.org/10.5194/nhess-24-163-2024, https://doi.org/10.5194/nhess-24-163-2024, 2024
Short summary
Short summary
The Upper Rhine Graben, located in France and Germany, is bordered by north–south-trending faults, posing a potential threat to dense population and infrastructures on the Alsace plain. We build upon previous seismic hazard studies of the graben by exploring uncertainties in greater detail, revisiting a number of assumptions. There is a 99 % probability that a maximum-magnitude earthquake would be below 7.3 if assuming a purely dip-slip mechanism or below 7.6 if assuming a strike-slip one.
Edlira Xhafaj, Chung-Han Chan, and Kuo-Fong Ma
Nat. Hazards Earth Syst. Sci., 24, 109–119, https://doi.org/10.5194/nhess-24-109-2024, https://doi.org/10.5194/nhess-24-109-2024, 2024
Short summary
Short summary
Our study introduces new earthquake forecasting models for Albania, aiming to map out future seismic hazards. By analysing earthquakes from 1960 to 2006, we have developed models that predict where activity is most likely to occur, highlighting the western coast and southern regions as high-hazard zones. Our validation process confirms these models are effective tools for anticipating seismic events, offering valuable insights for earthquake preparedness and hazard assessment efforts.
Franz Livio, Maria Francesca Ferrario, Elisa Martinelli, Sahra Talamo, Silvia Cercatillo, and Alessandro Maria Michetti
Nat. Hazards Earth Syst. Sci., 23, 3407–3424, https://doi.org/10.5194/nhess-23-3407-2023, https://doi.org/10.5194/nhess-23-3407-2023, 2023
Short summary
Short summary
Here we document the occurrence of an historical earthquake that occurred in the European western Southern Alps in the sixth century CE. Analysis of the effects due to earthquake shaking in the city of Como (N Italy) and a comparison with dated offshore landslides in the Alpine lakes allowed us to make an inference about the possible magnitude and the location of the seismic source for this event.
Simone Francesco Fornasari, Deniz Ertuncay, and Giovanni Costa
Nat. Hazards Earth Syst. Sci., 23, 3219–3234, https://doi.org/10.5194/nhess-23-3219-2023, https://doi.org/10.5194/nhess-23-3219-2023, 2023
Short summary
Short summary
We analysed the background seismic noise for the Italian strong motion network by developing the Italian accelerometric low- and high-noise models. Spatial and temporal variations of the noise levels have been analysed. Several stations located near urban areas are affected by human activities, with high noise levels in the low periods. Our results provide an overview of the background noise of the strong motion network and can be used as a station selection criterion for future research.
Subash Ghimire, Philippe Guéguen, Adrien Pothon, and Danijel Schorlemmer
Nat. Hazards Earth Syst. Sci., 23, 3199–3218, https://doi.org/10.5194/nhess-23-3199-2023, https://doi.org/10.5194/nhess-23-3199-2023, 2023
Short summary
Short summary
This study explores the efficacy of several machine learning models for damage characterization, trained and tested on the Database of Observed Damage (DaDO) for Italian earthquakes. Reasonable damage prediction effectiveness (68 % accuracy) is observed, particularly when considering basic structural features and grouping the damage according to the traffic-light-based system used during the post-disaster period (green, yellow, and red), showing higher relevancy for rapid damage prediction.
Ekbal Hussain, Endra Gunawan, Nuraini Rahma Hanifa, and Qori'atu Zahro
Nat. Hazards Earth Syst. Sci., 23, 3185–3197, https://doi.org/10.5194/nhess-23-3185-2023, https://doi.org/10.5194/nhess-23-3185-2023, 2023
Short summary
Short summary
The earthquake potential of the Lembang Fault, located near the city of Bandung in West Java, Indonesia, is poorly understood. Bandung has a population of over 8 million people. We used satellite data to estimate the energy storage on the fault and calculate the likely size of potential future earthquakes. We use simulations to show that 1.9–2.7 million people would be exposed to high levels of ground shaking in the event of a major earthquake on the fault.
Huaiqun Zhao, Wenkai Chen, Can Zhang, and Dengjie Kang
Nat. Hazards Earth Syst. Sci., 23, 3031–3050, https://doi.org/10.5194/nhess-23-3031-2023, https://doi.org/10.5194/nhess-23-3031-2023, 2023
Short summary
Short summary
Early emergency response requires improving the utilization value of the data available in the early post-earthquake period. We proposed a method for assessing seismic intensities by analyzing early aftershock sequences using the robust locally weighted regression program. The seismic intensity map evaluated by the method can reflect the range of the hardest-hit areas and the spatial distribution of the possible property damage and casualties caused by the earthquake.
Asim M. Khawaja, Behnam Maleki Asayesh, Sebastian Hainzl, and Danijel Schorlemmer
Nat. Hazards Earth Syst. Sci., 23, 2683–2696, https://doi.org/10.5194/nhess-23-2683-2023, https://doi.org/10.5194/nhess-23-2683-2023, 2023
Short summary
Short summary
Testing of earthquake forecasts is important for model verification. Forecasts are usually spatially discretized with many equal-sized grid cells, but often few earthquakes are available for evaluation, leading to meaningless tests. Here, we propose solutions to improve the testability of earthquake forecasts and give a minimum ratio between the number of earthquakes and spatial cells for significant tests. We show applications of the proposed technique for synthetic and real case studies.
Lukas Bodenmann, Jack W. Baker, and Božidar Stojadinović
Nat. Hazards Earth Syst. Sci., 23, 2387–2402, https://doi.org/10.5194/nhess-23-2387-2023, https://doi.org/10.5194/nhess-23-2387-2023, 2023
Short summary
Short summary
Understanding spatial patterns in earthquake-induced ground motions is key for assessing the seismic risk of distributed infrastructure systems. To study such patterns, we propose a novel model that accounts for spatial proximity, as well as site and path effects, and estimate its parameters from past earthquake data by explicitly quantifying the inherent uncertainties.
José A. Álvarez-Gómez, Paula Herrero-Barbero, and José J. Martínez-Díaz
Nat. Hazards Earth Syst. Sci., 23, 2031–2052, https://doi.org/10.5194/nhess-23-2031-2023, https://doi.org/10.5194/nhess-23-2031-2023, 2023
Short summary
Short summary
The strike-slip Carboneras fault is one of the largest sources in the Alboran Sea, with it being one of the faster faults in the eastern Betics. The dimensions and location of the Carboneras fault imply a high seismic and tsunami threat. In this work, we present tsunami simulations from sources generated with physics-based earthquake simulators. We show that the Carboneras fault has the capacity to generate locally damaging tsunamis with inter-event times between 2000 and 6000 years.
Antonio Posadas, Denisse Pasten, Eugenio E. Vogel, and Gonzalo Saravia
Nat. Hazards Earth Syst. Sci., 23, 1911–1920, https://doi.org/10.5194/nhess-23-1911-2023, https://doi.org/10.5194/nhess-23-1911-2023, 2023
Short summary
Short summary
In this paper we understand an earthquake from a thermodynamics point of view as an irreversible transition; then it must suppose an increase in entropy. We use > 100 000 earthquakes in northern Chile to test the theory that Shannon entropy, H, is an indicator of the equilibrium state. Using variation in H, we were able to detect major earthquakes and their foreshocks and aftershocks, including the 2007 Mw 7.8 Tocopilla earthquake and 2014 Mw 8.1 Iquique earthquake.
Dirsa Feliciano, Orlando Arroyo, Tamara Cabrera, Diana Contreras, Jairo Andrés Valcárcel Torres, and Juan Camilo Gómez Zapata
Nat. Hazards Earth Syst. Sci., 23, 1863–1890, https://doi.org/10.5194/nhess-23-1863-2023, https://doi.org/10.5194/nhess-23-1863-2023, 2023
Short summary
Short summary
This article presents the number of damaged buildings and estimates the economic losses from a set of earthquakes in Sabana Centro, a region of 11 towns in Colombia.
Andrea Antonucci, Andrea Rovida, Vera D'Amico, and Dario Albarello
Nat. Hazards Earth Syst. Sci., 23, 1805–1816, https://doi.org/10.5194/nhess-23-1805-2023, https://doi.org/10.5194/nhess-23-1805-2023, 2023
Short summary
Short summary
The earthquake effects undocumented at 228 Italian localities were calculated through a probabilistic approach starting from the values obtained through the use of an intensity prediction equation, taking into account the intensity data documented at close localities for a given earthquake. The results showed some geographical dependencies and correlations with the intensity levels investigated.
Cited articles
Baker, J., Bradley, B., and Stafford, P.: Seismic hazard and risk analysis, Cambridge University Press, Cambridge, UK, https://doi.org/10.1017/9781108425056, 2021. a
Båth, M.: Seismic risk in Fennoscandia, Tectonophysics, 57, 285–295, https://doi.org/10.1016/0040-1951(79)90152-5, 1979. a, b
Båth, M.: Intensity relations for Swedish earthquakes, Tectonophysics, 67, 163–173, https://doi.org/10.1016/0040-1951(80)90171-7, 1980. a
Beirlant, J., Kijko, A., Reynkens, T., and Einmahl, J.: Estimating the maximum possible earthquake magnitude using extreme value methodology, Nat. Hazards, 98, 1091–1113, https://doi.org/10.1007/s11069-017-3162-2, 2019. a
Bingen, B., Viola, G., Möller, C., Vander Auwera, J., Laurent, A., and Yi, K.: The Sveconorwegian orogeny, Gondwana Res., 90, 273–313, https://doi.org/10.1016/j.gr.2020.10.014, 2021. a
Bodare, A. and Kulhánek, O.: Dam safety. Earthquake hazard for dams in Sweden, Tech. Rep. 06:72, Elforsk, https://energiforsk.se/program/dammsakerhet/rapporter/earthquake-hazard-for-dams-in-sweden-2006-72/ (last access: 17 November 2024), 2006. a
Bödvarsson, R., Lund, B., Roberts, R., and Slunga, R.: Earthquake activity in Sweden. Study in connection with a proposed nuclear waste repository in Forsmark or Oskarshamn, Tech. rep., Swedish Nuclear Fuel and Waste Management Co., https://skb.se/publikation/1143996 (last access: 17 November 2024), 2006. a, b
Bogdanova, S., Bingen, B., Gorbatschev, R., Kheraskova, T., Kozlov, V., Puchkov, V., and Volozh, Y.: The East European Craton (Baltica) before and during the assembly of Rodinia, Precambrian Res., 160, 23–45, https://doi.org/10.1016/j.precamres.2007.04.024, 2008. a
Bungum, H., Pettenati, F., Schweitzer, J., Sirovich, L., and Faleide, J. I.: The 23 October 1904 MS 5.4 Oslofjord Earthquake: Reanalysis Based on Macroseismic and Instrumental Data, Bull. Seismol. Soc. Am., 99, 2836–2854, https://doi.org/10.1785/0120080357, 2016. a
Calais, E., Camelbeeck, T., Stein, S., Liu, M., and Craig, T.: A new paradigm for large earthquakes in stable continental plate interiors, Geophys. Res. Lett., 43, 10621–10637, https://doi.org/10.1002/2016GL070815, 2016. a, b
Corfu, F., Gasser, D., and Chew, D. M.: New perspectives on the Caledonides of Scandinavia and related areas: introduction, Geol. Soc. Lond. Spec. Publ., 390, 1–8, https://doi.org/10.1144/sp390.28, 2014. a
Cornell, C. A.: Engineering seismic risk analysis, Bull. Seismol. Soc. Am., 58, 1583–1606, https://doi.org/10.1785/BSSA0580051583, 1968. a, b
Danciu, L., Şeşetyan, K., Demircioglu, M., Gülen, L., Zare, M., Basili, R., Elias, A., Adamia, S., Tsereteli, N., Yalçın, H., Utkucu, M., Khan, M. A., Sayab, M., Hessami, K., Rovida, A. N., Stucchi, M., Burg, J.-P., Karakhanian, A., Babayan, H., Avanesyan, M., Mammadli, T., Al-Qaryouti, M., Kalafat, D., Varazanashvili, O., Erdik, M., and Giardini, D.: The 2014 Earthquake Model of the Middle East: seismogenic sources, Bull. Earthq. Eng., 16, 3465–3496, https://doi.org/10.1007/s10518-017-0096-8, 2017. a
Danciu, L., Nandan, S., Reyes, C. G., Basili, R., Weatherill, G., Beauval, C., Rovida, A., Vilanova, S., Sesetyan, K., Bard, P.-Y., Cotton, F., Wiemer, S., and Giardini, D.: The 2020 update of the European Seismic Hazard Model: Model Overview, EFEHR Technical Report 001, v1.0.0, EFEHR, https://doi.org/10.12686/a15, 2021. a, b, c, d, e, f, g, h, i, j
Eggertsson, G., Lund, B., Roth, M., and Schmidt, P.: Earthquake or blast? Classification of local-distance seismic events in Sweden using fully connected neural networks, Geophys. J. Int., 236, 1728–1742, https://doi.org/10.1093/gji/ggae018, 2024. a
Elliott, J. R.: Earth Observation for the Assessment of Earthquake Hazard, Risk and Disaster Management, Surv. Geophys. 41, 1323–1354, https://doi.org/10.1007/s10712-020-09606-4, 2020. a
EMSC: Euro-Mediterranean Seismological Centre Newsletter, 15, 3 pp., 1999. a
England, P. and Jackson, J.: Uncharted seismic risk, Nat. Geosci., 4, 348–349, https://doi.org/10.1038/ngeo1168, 2011. a, b
Field, E. H., Jordan, T. H., and Cornell, C. A.: OpenSHA: A Developing Community-modeling Environment for Seismic Hazard Analysis, Seismol. Res. Lett., 74, 406–419, https://doi.org/10.1785/gssrl.74.4.406, 2003. a
Finnish National Seismic Network: Interactive map tool for browsing earthquake dat: 17 November 2024), 2023. a
FNSN: Institute of Seismology, University of Helsinki, HE: The Finnish National Seismic Network, Earthquake catalogue data – FNSN, GFZ Data Services [data set], https://doi.org/10.14470/UR044600, 1980. a
Fülöp, L., Mäntyniemi, P., Malm, M., Toro, G., Crespo, M., Schmitt, T., Burck, S., and Välikangas, P.: Probabilistic seismic hazard analysis in low‐seismicity regions: an investigation of sensitivity with a focus on Finland, Nat. Hazards, 116, 111–132, https://doi.org/10.1007/s11069-022-05666-4, 2023. a, b
Gardner, J. and Knopoff, L.: Is the sequence of earthquakes in Southern California, with aftershocks removed, Poissonian?, Bull. Seismol. Soc. Am., 64, 1363–1367, 1974. a
Geffers, G.-M., Main, I., and Naylor, M.: Biases in estimating b-values from small earthquake catalogues: how high are high b-values?, Geophys. J. Int., 229, 1840–1855, https://doi.org/10.1093/gji/ggac028, 2022. a
Goulet, C., Kishida, T., Ancheta, T., Cramer, C., Darragh, R., Silva, W., Hashash, Y., Harmon, J., Stewart, J., Wooddell, K., and Young, R. R.: PEER NGA-East database, Tech. Rep. 2014/17, Pacific Earthquake Engineering Research Center, University of California, Berkeley, USA, https://doi.org/10.1177/87552930211015695, 2014. a
Goulet, C. A., Bozorgnia, Y., Kuehn, N., Al Atik, L., Youngs, R. R., Graves, R. W., and Atkinson, G. M.: NGA-East Ground-Motion Characterization model part I: Summary of products and model development, Earthq. Spectra, 37, 1231–1282, https://doi.org/10.1177/87552930211018723, 2021. a
Graizer, V.: Ground-motion prediction equations for Central and Eastern North America, Bull. Seismol. Soc. Am., 106, 1600–1612, https://doi.org/10.1785/0120150374, 2016. a
Gregersen, S., Wiejacz, P., Dębski, W., Domanski, B., Assinovskaya, B., Guterch, B., Mäntyniemi, P., Nikulin, V., Pacesa, A., Puura, V., Aronov, A., Aronova, T., Grünthal, G., Husebye, E., and Sliaupa, S.: The exceptional earthquakes in Kaliningrad district, Russia on September 21, 2004, Phys. Earth Planet. Int., 164, 63–74, https://doi.org/10.1016/j.pepi.2007.06.005, 2007. a, b
Gregersen, S., Lindholm, C., Korja, A., Lund, B., Uski, M., Oinonen, K., Voss, P. H., and Keiding, M.: Seismicity and Sources of Stress in Fennoscandia, Cambridge University Press, 177–197, https://doi.org/10.1017/9781108779906.014, 2021. a, b, c, d
Grünthal, G. and Group, T. G. R. W.: Seismic hazard assessment for Central, North and Northwest Europe: GSHAP Region 3, Ann. Geophys., 42, 999–1011, https://doi.org/10.4401/ag-3783, 1999. a
Grünthal, G., Wahlström, R., and Stromeyer, D.: The SHARE European Earthquake Catalogue (SHEEC) for the time period 1900–2006 and its comparison to the European-Mediterranean Earthquake Catalogue (EMEC), J. Seismol., 17, 1339–1344, https://doi.org/10.1007/s10950-013-9379-y, 2013. a
GSE – Geological Survey of Estonia: Estonian Seismic Network, Earthquake catalogue data – Estonian seismic network, GSE [data set], https://www.egt.ee/en/fields-activity-and-objectives/geology-and-environment/seismic-research-and-monitoring (last access: 17 November 2024), 1998. a
Gutenberg, B. and Richter, C. F.: Frequency of earthquakes in California, Bull. Seismol. Soc. Am., 34, 185–188, https://doi.org/10.1785/BSSA0340040185, 1944. a, b
Hanks, T. and Kanamori, H.: A moment magnitude scale, J. Geophys. Res., 84, 2348–2350, https://doi.org/10.1029/JB084iB05p02348, 1979. a, b
Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R., Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A., Fernández del Río, J., Wiebe, M., Peterson, P., Gérard-Marchant, P., Sheppard, K., Reddy, T., Weckesser, W., Abbasi, H., Gohlke, C., and Oliphant, T. E.: Array programming with NumPy, Nature, 585, 357–362, https://doi.org/10.1038/s41586-020-2649-2, 2020. a
Hashash, Y. M. A., Ilhan, O., Harmon, J. A., Parker, G. A., Stewart, J. P., Rathje, E. M., Campbell, K. W., and Silva, W. J.: Nonlinear site amplification model for ergodic seismic hazard analysis in Central and Eastern North America, Earthq. Spectra, 36, 69–86, https://doi.org/10.1177/8755293019878193, 2020. a
Hunter, J. D.: Matplotlib: A 2D graphics environment, Comput. Sci. Eng., 9, 90–95, https://doi.org/10.1109/MCSE.2007.55, 2007. a
Johnston, A., Coppersmith, K., Kanter, L., and Cornell, C.: The Earthquakes of Stable Continental Regions – Assessment of large earthquake potential, Tech. Rep. TR-102261-V1, Electric Power Research Institute, Palo Alto, California, http://www.epri.com/search/Pages/results.aspx?k=stable continental regions (last access: August 2023), 1994. a
Jordahl, K., Van den Bossche, J., Fleischmann, M., Wasserman, J., McBride, J., Gerard, J., Tratner, J., Perry, M., Garcia Badaracco, A., Farmer, C., Hjelle, G. A., Snow, A. D., Cochran, M., Gillies, S., Culbertson, L., Bartos, M., Eubank, N., Albert, M., Bilogur, A., Rey, S., Ren and, C., Wasser, L., Wolf, L. J., Journois, M., Wilson, J., Greenhall, A., Holdgraf, C., Filipe, and Leblanc, F.: geopandas/geopandas: v0.8.1, Zenodo [code], https://doi.org/10.5281/zenodo.3946761, 2020. a
Kijko, A. and Graham, G.: Parametric-historic procedure for probabilistic seismic hazard analysis. Part II: Assessment of seismic hazard at specified site, Pure Appl. Geophys., 154, 1–22, 1999. a
Kijko, A. and Singh, M.: Statistical Tools for Maximum Possible Earthquake Magnitude Estimation, Acta Geophys., 59, 674–700, https://doi.org/10.2478/s11600-011-0012-6, 2011. a, b
Kijko, A., Skordas, E., Wahlström, R., and Mäntyniemi, P.: Maximum Likelihood Estimation of Seismic Hazard for Sweden, Nat. Hazards, 7, 41–57, https://doi.org/10.1007/BF00595678, 1993. a, b, c, d
Kortström, J., Uski, M., and Tiira, T.: Automatic classification of seismic events within a regional seismograph network, Comput. Geosci., 87, 22–30, https://doi.org/10.1016/j.cageo.2015.11.006, 2016. a
Kotha, S. R., Weatherill, G., Bindi, D., and Cotton, F.: A regionally-adaptable ground-motion model for shallow crustal earthquakes in Europe, Bull. Earthq. Eng., 18, 4091–4125, https://doi.org/10.1007/s10518-020-00869-1, 2020. a, b, c, d
Larsson, J. and Larsson, E.: ESHM13 – En ny PSHA-modell för Europa betraktad ur ett svenskt perspektiv, Tech. Rep. 2018:27, SSM – Swedish Radiation Safety Authority, https://www.stralsakerhetsmyndigheten.se/contentassets/2c9cede (last access: 17 November 2024), 2018. a
Lomnitz, C.: Global tectonics and earthquake risk, Developments in geotectonics, Elsevier Scientific Pub. Co., https://www.sciencedirect.com/bookseries/developments-in-geotectonics/vol/5/suppl/C (last access: 17 November 2024), 1974. a
Lund, B.: Palaeoseismology of glaciated terrain, in: Encyclopedia of Earthquake Engineering, edited by: Beer, M., Kougioumtzoglou, I., Patelli, E., and Au, S.-K., Springer, Berlin, Heidelberg, 1765–1779, ISBN 9781108779906, https://doi.org/10.1007/978-3-642-36197-5_25-1, 2015. a, b
Lund, B., Shomali, H., Buhcheva, D., Högdahl, K., Tryggvason, A., Bödvarsson, R., Schmidt, P., and Jørgensen, P.: The 2014 magnitude 4.1 Sveg earthquake, Nordic Seminar on Seismology, 8–10 October 2014, Visby, Sweden, https://nordquake.net/nordic/Nordic-Seminar-2014.pdf (last access: 17 November 2024), 2014. a
Lund, B., Roberts, R., and Smith, C.: Review of paleo-, historical and current seismicity in Sweden and surrounding areas with implications for the seismic analysis underlying SKI report 92:3, Tech. Rep. 2017:35, SSM – Swedish Radiation Safety Authority, https://www.stralsakerhetsmyndigheten.se/publikationer/rapporter/sakerhet-vid-karnkraftverken/2017/201735/ (last access: 17 November 2024), 2017. a
Lund, B., Mäntyniemi, P., Sadegi-Bagherabadi, A., Korja, A., and Lundwall, J.: Comparing European Seismic Hazard Models: ESHM20 versus ESHM13 at nuclear power plant sites in Sweden and Finland, Tech. Rep. 2024:1013, Energiforsk, ISBN 978-91-89919-13-6, 2024. a
Mantovani, M. and Scherneck, H.-G.: DInSAR investigation in the Pärvie end-glacial fault region, Lapland, Sweden, Int. J. Remote Sens., 34, 8491–8502, https://doi.org/10.1080/01431161.2013.843871, 2013. a
Mäntyniemi, P.: Some features of Finnish earthquake data, Geophysica, 32, 273–289, 1996. a
McGuire, R. K.: FORTRAN computer program for seismic risk analysis, USGS, https://doi.org/10.3133/ofr7667, 1976. a
McGuire, R. K.: Deterministic vs. probabilistic earthquake hazards and risks, Soil Dynam. Earthq. Eng., 21, 377–384, https://doi.org/10.1016/s0267-7261(01)00019-7, 2001. a
Miller, A. C. and Rice, T. R.: Discrete Approximations of Probability Distributions, Manage. Sci., 29, 352–362, 1983. a
Mosca, I., Sargeant, S., Baptie, B., Musson, R., and Pharaoh, T.: The 2020 national seismic hazard model for the United Kingdom, Bull. Earthq. Eng., 20, 633–675, https://doi.org/10.1007/s10518-021-01281-z, 2022. a
Muir Wood, R.: The Scandinavian earthquakes of 22 December 1759 and 31 August 1819, Disasters, 12, 223–236, https://doi.org/10.1111/j.1467-7717.1988.tb00672.x, 1989. a
Munier, R., Adams, J., Brandes, C., Brooks, G.,Dehls, J., Einarsson, P., Gibbons, S. J., Hjartardóttir, A. R., Hogaas, F., Johansen, T. A., Kvaerna, T., Mattila, J., Mikko, H., Müller, K., Nikolaeva, S. B., Ojala, A. E. K., Olesen, O., Olsen, L., Palmu, J.-P., Ruskeeniemi, T., Ruud, B. O., Sandersen, P. B. E., Shvarev, S. V., Smith, C. A., Steffen, H., Steffen, R., Sutinen, R., and Tassis, G.: International Database of Glacially-Induced Faults, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.922705, 2020. a, b
Mäntyniemi, P., Wahlström, R., Lindholm, C., and Kijko, A.: Seismic hazard in Fennoscandia: A regionalized study, Tectonophysics, 227, 205–213, https://doi.org/10.1016/0040-1951(93)90095-2, 1993. a, b
Mäntyniemi, P., Sørensen, M., Tatevossian, T., Tatevossian, R., and Lund, B.: A Reappraisal of the Lurøy, Norway, Earthquake of 31 August 1819, Seismol. Res. Lett., 91, 2462–2472, https://doi.org/10.1785/0220190363, 2020. a, b
Norsar: NORSAR Station Network, https://doi.org/10.21348/D.NO.0001, 1971. a
Olesen, O., Olsen, L., Gibbons, S. J., Ruud, B. O., Høgaas, F., Johansen, T. A., and Kværna, T.: Postglacial Faulting in Norway: Large Magnitude Earthquakes of the Late Holocene Age, in: Glacially-Triggered Faulting, edited by: Steffen, H., Olesen, O., and Sutinen, R., Cambridge University Press, 198–217, https://doi.org/10.1017/9781108779906.015, 2021. a, b, c
Ottemöller, L., Strømme, M. L., and Storheim, B. M.: Seismic monitoring and data processing at the Norwegian National Seismic Network, Summary of the Bulletin of the International Seismological Centre, 52, 27–40, https://doi.org/10.31905/1M97CSYL, 2018. a, b
Pagani, M., Monelli, D., Weatherill, G., Danciu, L., Crowley, H., Silva, V., Henshaw, P., Butler, L., Nastasi, M., Panzeri, L., Simionato, M., and Vigano, D.: OpenQuake Engine: An Open Hazard (and Risk) Software for the Global Earthquake Model, Seismol. Res. Lett., 85, 692–702, https://doi.org/10.1785/0220130087, 2014. a, b, c, d
QGIS Development Team: QGIS Geographic Information System, https://www.qgis.org/en/site/ (last access: 27 November 2024), 2024. a
Rosberg, J.-E. and Erlström, M.: Evaluation of the Lund deep geothermal exploration project in the Romeleåsen Fault Zone, South Sweden: a case study, Geoth. Energy, 7, 10, https://doi.org/10.1186/s40517-019-0126-7, 2019. a
Rovida, A. and Antonucci, A.: EPICA – European PreInstrumental Earthquake CAtalogue, version 1.1, EPICA, https://doi.org/10.13127/EPICA.1.1, 2021. a
Saari, J., Lund, B., Malm, M., Mäntyniemi, P., Oinonen, K., Tiira, T., Uski, M., and Vuorinen, T.: Evaluating Seismic Hazard for the Hanhikivi Nuclear Power Plant Site, Seismological Characteristics of the Source Areas, Attenuation of Seismic Signal, and Probabilistic Analysis of Seismic Hazard, Tech. Rep. NE-4459, ÅF-Consult Ltd, Finland, https://researchportal.helsinki.fi/en/publications/evaluating-seismic-hazard-for-the-hanhikivi-nuclear-power-plant-s (last access: 27 November 2024), 2015. a
Sadeghisorkhani, H., Gudmundsson, O., Li, K. L., Tryggvason, A., Lund, B., and Högdahl, K.: Shear wave structure of southern Sweden from precise phase-velocity measurements of ambient-noise data, Geophys. J. Int., 225, 494–511, https://doi.org/10.1093/gji/ggaa598, 2020. a
Sandersen, P. B. E., Gregersen, S., and Voss, P. H.: Postglacial Faulting in Norway: Large Magnitude Earthquakes of the Late Holocene Age, in: Glacially-Triggered Faulting, edited by: Steffen, H., Olesen, O., and Sutinen, R., Cambridge University Press, 263–282, https://doi.org/10.1017/9781108779906.015, 2021. a
Sargeant, S., Stafford, P., Lawley, R., Weatherill, G., A-J.S., W., Bommer, J., Burton, P., Free, M., Musson, R., Kuuyor, T., and Rossetto, T.: Observations from the Folkestone, UK, earthquake of 28 April 2007, Seismol. Res. Lett., 79, 672–687, https://doi.org/10.1785/gssrl.79.5.672, 2008. a
Schorlemmer, D., Euchner, F., Kästli, P., and Saul, J.: QuakeML: status of the XML-based seismological data exchange format, Ann. Geophys., 54, 59–65, https://doi.org/10.4401/ag-4874, 2011. a
Schulte, S. M. and Mooney, W. D.: An updated global earthquake catalogue for stable continental regions: reassessing the correlation with ancient rifts, Geophys. J. Int., 161, 707–721, https://doi.org/10.1111/j.1365-246x.2005.02554.x, 2005. a
Shiddiqi, H. A., Ottemöller, L., Rondenay, S., Halpaap, F., Gradmann, S., and Michálek, J.: Crustal structure and intraplate seismicity in Nordland, Northern Norway: insight from seismic tomography, Geophys. J. Int., 230, 813–830, https://doi.org/10.1093/gji/ggac086, 2022. a
Silva, V., Crowley, H., Pagani, M., Monelli, D., and Pinho, R.: Development of the OpenQuake engine, the Global Earthquake Model's open-source software for seismic risk assessment, Nat. Hazards, 72, 1409–1427, https://doi.org/10.1007/s11069-013-0618-x, 2013. a
Rögnvaldsson, S. T. and Slunga, R.: Routine fault plane solutions for local networks: A test with synthetic data, Bull. Seismol. Soc. Am., 83, 1232–1247, 1993. a
SKI: Project Seismic Safety. Characterization of seismic ground motions for probabalistic safety analyses of nuclear facilities in Sweden, Tech. Rep. 92:3, SKI – Swedish Nuclear Power Inspectorate, https://www.stralsakerhetsmyndigheten.se/en/publications/reports/safety-at-nuclear-power-plants/1992/19923/ (last access: 27 November 2024), 1992. a, b, c, d, e
Smith, C. A., Mikko, H., and Grigull, S.: Glacially Induced Faults in Sweden: The Rise and Reassessment of the Single-Rupture Hypothesis, in: Glacially-Triggered Faulting, edited by: Steffen, H., Olesen, O., and Sutinen, R., Cambridge University Press, Cambridge, 218–230, ISBN 9781108779906, https://doi.org/10.1017/9781108779906, 2021. a, b, c, d, e
SNSN – Swedish National Seismic Network: Earthquake catalogue data – SNSN, SNSN [data set], https://doi.org/10.18159/SNSN, 1904. a
Sodankylä Geophysical Observatory/University of Oulu: Northern Finland Seismological Network, https://doi.org/10.14470/SA879454, 1980. a
Soosalu, H., Uski, M., Komminaho, K., and Veski, A.: Recent Intraplate Seismicity in Estonia, East European Platform, Seismol. Res. Lett., 93, 1800–1811, https://doi.org/10.1785/0220210277, 2022. a
Steffen, H., Olesen, O., and Sutinen, R.: Glacially-Triggered Faulting, Cambridge University Press, Cambridge, ISBN 9781108779906, https://doi.org/10.1017/9781108779906, 2021. a
Stephens, M. B. and Bergman-Weihed, J.: Sweden: Lithotectonic Framework, Tectonic Evolution and Mineral Resources, in: vol. 50, Geological Society, Memoirs, London, https://doi.org/10.1144/M50-2019-21, 2020. a, b, c, d
Stewart, J. P., Parker, G. A., Atkinson, G. M., Boore, D. M., Hashash, Y. M. A., and Silva, W. J.: Ergodic site amplification model for central and eastern North America, Earthq. Spectra, 36, 42–68, https://doi.org/10.1177/8755293019878185, 2020. a
Svendsen, J. I., Alexanderson, H., Astakhov, V. I., Demidov, I., Dowdeswell, J. A., Funder, S., Gataullin, V., Henriksen, M., Hjort, C., Houmark-Nielsen, M., Hubberten, H. W., Ólafur Ingólfsson, Jakobsson, M., Kjær, K. H., Larsen, E., Lokrantz, H., Lunkka, J. P., Lyså, A., Mangerud, J., Matiouchkov, A., Murray, A., Möller, P., Niessen, F., Nikolskaya, O., Polyak, L., Saarnisto, M., Siegert, C., Siegert, M. J., Spielhagen, R. F., and Stein, R.: Late Quaternary ice sheet history of northern Eurasia, Quaternary Sci. Rev., 23, 1229–1271, https://doi.org/10.1016/j.quascirev.2003.12.008, 2004. a
Tan, Y. J. and Maharjan, R.: What Googling Trends Tell Us about Public Interest in Earthquakes, Seismol. Res. Lett., 89, 653–657, https://doi.org/10.1785/0220170116, 2018. a
The pandas development team: pandas-dev/pandas: Pandas, Zenodo [code], https://doi.org/10.5281/zenodo.3509134, 2020. a
Tian, T., Uieda, L., Leong, W. J., Fröhlich, Y., Schlitzer, W., Grund, M., Jones, M., Toney, L., Yao, J., Magen, Y., Tong, J.-H., Materna, K., Belem, A., Newton, T., Anant, A., Ziebarth, M., Quinn, J., and Wessel, P.: PyGMT: A Python interface for the Generic Mapping Tools, Zenodo [code], https://doi.org/10.5281/zenodo.13679420, 2024. a, b
Tinti, S. and Mulargia, F.: Confidence intervals of b-values for grouped magnitudes, Bull. Seismol. Soc. Am., 77, 2125–2134, https://doi.org/10.1785/BSSA0770062125, 1987. a, b
University of Bergen: University of Bergen Seismic Network, University of Bergen [data set], https://doi.org/10.7914/SN/NS, 1982. a
Uski, M. and Tuppurainen, A.: A new local magnitude scale for the Finnish seismic network, Tectonophysics, 261, 23–37, 1996. a
Uski, M., Lund, B., and Oinonen, K.: Compilation of a homogenized earthquake catalogue, in: Evaluating Seismic Hazard for the Hanhikivi Nuclear Power Plant Site, Seismological Characteristics of the Source Areas, Attenuation of Seismic Signal, and Probabilistic Analysis of Seismic Hazard, Report NE-4459, edited by: Saari, J., Lund, B., Malm, M., Mäntyniemi, P., Oinonen, K., Tiira, T., Uski, M., and Vuorinen, T., ÅF-Consult Ltd, Finland, p. 123, https://researchportal.helsinki.fi/en/publications/evaluating-seismic-hazard-for-the-hanhikivi-nuclear-power-plant (last access: 17 November 2024), 2015. a, b, c, d, e, f, g, h, i
van Stiphout, T., Zhuang, J., and Marsan, D.: Seismicity declustering, Community Online Resource for Statistical Seismicity Analysis, CORSSA, https://doi.org/10.5078/corssa-52382934, 2012. a
Veikkolainen, T., Kukkonen, I. T., and Tiira, T.: Heat flow, seismic cut-off depth and thermal modeling of the Fennoscandian Shield, Geophys. J. Int., 211, 1414–1427, https://doi.org/10.1093/gji/ggx373, 2017. a
Veikkolainen, T., Kortström, J., Vuorinen, T., Salmenperä, I., Luhta, T., Mäntyniemi, P., Hillers, G., and Tiira, T.: The Finnish National Seismic Network: Toward Fully Automated Analysis of Low‐Magnitude Seismic Events, Seismol. Res. Lett., 92, 1581–1591, https://doi.org/10.1785/0220200352, 2021. a, b
Vestøl, O., Ågren, J., Steffen, H., Kierulf, H., and Tarasov, L.: NKG2016LU: a new land uplift model for Fennoscandia and the Baltic Region, J. Geod., 93, 1759-1779, https://doi.org/=10.1007/s00190-019-01280-8, 2019. a, b
Wahlström, R. and Grünthal, G.: Probabilistic seismic hazard assessment (horizontal PGA) for Sweden, Finland and Denmark using different logic tree approaches, Soil Dynam. Earthq. Eng., 20, 45–58, https://doi.org/10.1016/S0267-7261(00)00037-3, 2000. a
Weatherill, G. and Cotton, F.: A ground motion logic tree for seismic hazard analysis in the stable cratonic region of Europe: regionalisation, model selection and development of a scaled backbone approach, Bull. Earthq. Eng., 18, 6119–6148, https://doi.org/10.1007/s10518-020-00940-x, 2020. a, b, c, d, e, f, g
Weichert, D. H.: Estimation of the earthquake recurrence parameters for unequal observation periods for different magnitudes, Bull. Seismol. Soc. Am., 70, 1337–1346, https://doi.org/10.1785/BSSA0700041337, 1980. a, b, c
Wessel, P., Luis, J. F., Uieda, L., Scharroo, R., Wobbe, F., Smith, W. H. F. and Tian, D.: The Generic Mapping Tools Version 6, Geochem. Geophy. Geosy., 20, 5556–5564, https://doi.org/10.1029/2019gc008515, 2019. a, b, c
Wheeler, R. L.: Maximum Magnitude (Mmax) in the Central and Eastern United States for the 2014 U.S. Geological Survey Hazard Model, Bull. Seismol. Soc. Am., 106, 2154–2167, https://doi.org/10.1785/0120160048, 2016. a, b
Woessner, J., Laurentiu, D., Giardini, D., Crowley, H., Cotton, F., Grünthal, G., Valensise, G., Arvidsson, R., Basili, R., Demircioglu, M. B., Hiemer, S., Meletti, C., Musson, R. W., Rovida, A. N., Sesetyan, K., Stucchi, M., and Consortium, T. S.: The 2013 European Seismic Hazard Model: key components and results, Bull. Earthq. Eng., 13, 3553–3596, https://doi.org/10.1007/s10518-015-9795-1, 2015. a, b, c
Zöller, G.: A Note on the Estimation of the Maximum Possible Earthquake Magnitude Based on Extreme Value Theory for the Groningen Gas Field, Bull. Seismol. Soc. Am., 112, 1825–1831, https://doi.org/10.1785/0120210307, 2022. a
Short summary
Few large earthquakes and low occurrence rates make seismic hazard assessment of Sweden a challenging task. Recent expansion of the seismic network has improved the quality and quantity of the data recorded. We use these new data to estimate the Swedish seismic hazard using probabilistic methods to find that hazard was previously underestimated in the north. The north has the highest hazard in Sweden, with estimated mean peak ground acceleration of up to 0.06 g for a 475-year return period.
Few large earthquakes and low occurrence rates make seismic hazard assessment of Sweden a...
Special issue
Altmetrics
Final-revised paper
Preprint