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On modeling seismicity in seismic hazard assessment problems

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1. Title Title of document On modeling seismicity in seismic hazard assessment problems
2. Creator Author's name, affiliation, country P. N. Shebalin; Institute of Earthquake Prediction Theory and Mathematical Geophysics, Russian Academy of Sciences; Geophysical Center, Russian Academy of Sciences; Russian Federation
2. Creator Author's name, affiliation, country S. B. Baranov; Institute of Earthquake Prediction Theory and Mathematical Geophysics, Russian Academy of Sciences; Kola Branch, Geophysical Survey, Russian Academy of Sciences; Russian Federation
2. Creator Author's name, affiliation, country I. A. Vorobieva; Institute of Earthquake Prediction Theory and Mathematical Geophysics, Russian Academy of Sciences; Geophysical Center, Russian Academy of Sciences; Russian Federation
2. Creator Author's name, affiliation, country Е. M. Grekov; Institute of Earthquake Prediction Theory and Mathematical Geophysics, Russian Academy of Sciences; Russian Federation
2. Creator Author's name, affiliation, country К. V. Krushelnitskii; Institute of Earthquake Prediction Theory and Mathematical Geophysics, Russian Academy of Sciences; Russian Federation
2. Creator Author's name, affiliation, country A. A. Skorkina; Institute of Earthquake Prediction Theory and Mathematical Geophysics, Russian Academy of Sciences; Russian Federation
2. Creator Author's name, affiliation, country О. V. Selyutskaya; Institute of Earthquake Prediction Theory and Mathematical Geophysics, Russian Academy of Sciences; Russian Federation
3. Subject Discipline(s)
3. Subject Keyword(s) earthquake; seismic hazard; General seismic zoning; GSZ; seismic regime; earthquake intensity; synthetic catalog of earthquakes
4. Description Abstract

Seismicity modeling is an important part of creating General Seismic Zoning maps within the framework of a probabilistic approach. We consider the main disadvantages of individual elements of the recent seismicity models. A variant of the methodology is proposed, which, due to the improvements of those elements, should provide more accurate estimates of the future seismicity. For the first time, a stochastic seismicity model has been proposed in the form of a synthetic earthquake catalog, generated for an arbitrary conditional period and reproducing the properties of the catalog of actual earthquakes, including spatiotemporal grouping. A methodology for verifying seismicity models is proposed to check the compliance of the models with the initial data, to assess the predictive efficiency of the models, and to compare efficiency of different models.

5. Publisher Organizing agency, location The Russian Academy of Sciences
6. Contributor Sponsor(s) Russian Science Foundation (20-17-00180-П)
7. Date (DD-MM-YYYY) 30.09.2024
8. Type Status & genre Peer-reviewed Article
8. Type Type Research Article
9. Format File format
10. Identifier Uniform Resource Identifier https://journals.eco-vector.com/2686-7397/article/view/649966
10. Identifier Digital Object Identifier (DOI) 10.31857/S2686739724030121
11. Source Title; vol., no. (year) Doklady Rossijskoj akademii nauk. Nauki o Zemle; Vol 515, No 1 (2024)
12. Language English=en ru
13. Relation Supp. Files Fig. 1. Variations in seismic activity, – an estimate of the number of earthquakes with magnitude M ≥ 3.5, calculated using the formula (1). Earthquakes are shown in black circles. The values are linked to the centers of the scan circles. (589KB)
Fig. 2. Map of earthquake epicenters in a circle with the coordinates of the center (106° vd, 53° s. w.). The blue cross shows the center of the circle, the red cross shows the average position of earthquakes (106.8° vd, 52.6° s. w.), which is shifted relative to the center of the circle by 70 km. (74KB)
Fig. 3. Variations in seismic activity, – an estimate of the number of earthquakes with magnitude M ≥ 3.5, calculated using the formula (1). The values are linked to the average position of the sample earthquakes. Earthquakes are shown in black circles. (596KB)
Fig. 4. Results of verification of the synthetic earthquake catalog of the Altai-Sayan-Baikal region according to the actual catalog from 1982 to 2021, M – L-test. The empirical distribution function (blue curve on the left) and the histogram (on the right) are logarithmic likelihood values. The vertical line shows the value of L. (142KB)
14. Coverage Geo-spatial location, chronological period, research sample (gender, age, etc.)
15. Rights Copyright and permissions Copyright (c) 2024 Russian Academy of Sciences