EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Noise-based estimation of local seismic amplification in an industrialized area of the French Rhone Valley

Loïc Gisselbrecht1, Bérénice Froment2, and Pierre Boué3
Loïc Gisselbrecht et al.
  • 1IRSN (Institut de radioprotection et de sûreté nucléaire), Fontenay-aux-Roses, France (
  • 2IRSN (Institut de radioprotection et de sûreté nucléaire), Fontenay-aux-Roses, France (
  • 3ISTerre (Institut des Sciences de la Terre), Univ. Grenoble Alpes, Grenoble, France (

Shallow sedimentary layers have a strong impact on seismic motion. These so-called site effects may be responsible for dramatic ground motion amplification and increase the duration of shaking when an earthquake occurs. The quantification of such amplification effects for specific sites might be challenging to carry out in low-to-moderate seismicity regions where moderate to large earthquakes have long return periods. Therefore, methods based on background ambient noise might be of great interest for these areas.

In this study, we investigate the potential of ambient noise in ground motion amplification assessment through SSRn (noise-based Standard Spectral Ratio) and SSRh (hybrid Standard Spectral Ratio, Perron et al., 2018) computation. We continuously recorded ambient noise from February to March 2020 on a 400-sensor seismic array covering an area of about 10 x 10 km in the Tricastin industrial region (French Rhone Valley) where critical facilities are located. This area is located on a very elongated valley, filled with Pliocene sediments (sands and clays), that was dug during the Messinian Salinity Crisis in Cretaceous sandstones and limestones. The strong lithological contrast between the sedimentary filling and the bedrock, as well as the valley's incised geometry, is prone to generate strong and complicated site effects.

Previous studies have shown that SSRn is not able to reproduce earthquake-based SSR amplification factor for frequencies higher than 1 Hz. This disagreement may be explained by the influence of local noise sources. Here, we introduce an approach to mitigate the influence of strong local sources in SSRn and SSRh. Our workflow relies on a clustering algorithm to select the Fourier Amplitude Spectrum (FAS) used in the SSRn and SSRh computation. By applying this method, we were able to remove strong anthropic transient signals at some sites and therefore improve the amplification assessment above 1Hz through the SSRn and SSRh. However, half part of the array is located nearby permanent anthropic sources that remain a major issue in quantifying the amplification at the scale of the valley. This study provides some insights into the conditions of applications of SSRn and SSRh in noisy industrialized environments.

How to cite: Gisselbrecht, L., Froment, B., and Boué, P.: Noise-based estimation of local seismic amplification in an industrialized area of the French Rhone Valley, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9511,, 2022.