Towards a reduction of the high-frequency uncertainty of ground-motion-models: 
Inventory of insufficiently taken into account phenomena that disturb seismic 
record

Hollender, Fabrice; Rischette, Pauline; Perron, Vincent; Theodoulidis, Nikolaos; Roumelioti, Zafeiria; Traversa, Paola; Buscetti, Margaux

doi:10.57757/IUGG23-4598

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Towards a reduction of the high-frequency uncertainty of ground-motion-models: Inventory of insufficiently taken into account phenomena that disturb seismic record

Authors

Hollender, Fabrice
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Rischette, Pauline
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Perron, Vincent
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Theodoulidis, Nikolaos
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Roumelioti, Zafeiria
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Traversa, Paola
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Buscetti, Margaux
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

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Citation

Hollender, F., Rischette, P., Perron, V., Theodoulidis, N., Roumelioti, Z., Traversa, P., Buscetti, M. (2023): Towards a reduction of the high-frequency uncertainty of ground-motion-models: Inventory of insufficiently taken into account phenomena that disturb seismic record, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-4598

Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5021008

Abstract

Reducing the standard deviation of ground motion models (GMMs) is a challenge that has engaged the seismic hazard scientific community for many years with results that unfortunately do not match the dedicated efforts. The work of the last few years, allowing the processing of an ever-increasing amount of data with machine learning approaches, has allowed great progress towards the reduction of these uncertainties, nevertheless, the high frequency uncertainty remains large, especially for GMMs developed in the Fourier domain. While these machine learning approaches are particularly promising, it is nevertheless necessary for the seismologist to provide them with the relevant parameters to test. In this work, we inventory a set of phenomena that disturb high frequency signals and that are not or rarely taken into account. We present a synthesis of recent results on different phenomena: small-scale soil-structure interaction generated by slabs or pillars often used to couple seismometers and accelerometers, depth effect, small-scale topography effect, seasonal variations. We discuss the interest of a better documentation of the installation conditions within the metadata associated to seismic motion databases.