Dataset description
Here is provided the full dataset of seismic profiles acquired at the Strengbach catchment, OHGE observatory (Observatoire Géochimique et Hydrologique de l’Environnement) which is part of the national research infrastructure OZCAR-RI (Critical Zone Observatories, applications et research) in France. The Strengbach catchment is located in the commune of Aubure (60 km southwest of Strasbourg) in a mid-altitude mountainous area in the Vosges massif. More information on the site and the observatory can be found on the observatory website.
Ten SRT profiles are available, they were acquired in June 2018 and August 2019 and cover a total length of 2 km. The data were collected along profiles of different lengths with 24-channel seismic recorders (Geometrics) and 14-Hz vertical-component geophones. The inter-distance between geophones was fixed to 2 m, and the sources were distant by 8–10 m. The source signal was generated using a 5 kg sledgehammer swung on a metal plate. For each shot, the seismic wave propagation was recorded with 72–144 geophones, depending on the profile as summarized in Table 1.
First arrival times were picked manually on each trace gathered by recorded shots, when the signal-to-noise ratio is high enough to confidently identify first breaks. The observed travel times were then used to build the subsurface P-wave velocity structure by solving an inverse problem with the pyGIMLi refraction tomography inversion module (Rücker et al., 2017). In pyGIMLi, the inversion domain corresponds to a triangular mesh with cells of constant velocity through which rays are traced using a shortest-path algorithm (Dijkstra, 1959; Moser, 1991). The velocity in each mesh cell is estimated using a generalized Gauss-Newton inversion framework. The inversion is iterative and starts with an initial model consisting of a velocity field that increases linearly with depth from [250 – 750] m/s at surface to [2000 – 5000] m/s in depth (Table 2). The velocity field is then smoothly updated at each iteration in order to reach the closest match between predicted and observed travel times. Inversions were performed with 144 combinations of starting models and regularization parameters (Table 2) in order to explore the possible solutions and estimate the uncertainty of the velocity distribution along each profile (Pasquet et al., 2016). The data can be used to study the underground structure of the critical zone (Pasquet et al., 2022).
| Top velocity (m/s) | 250, 500, 750 |
| Bottom velocity (m/s) | 2000, 3000, 4000, 5000 |
| z_weight | 0.25, 0.5, 0.75, 1 |
| lambda | 2, 20, 200 |
Download links
The dataset available in the H+ database may be downloaded from the link below:
| Seismic profiles |
|---|
| Files of the dataset |
Acknowledgements
Fundings:
The Equipex CRITEX ANR-11-EQPX-0011 project provided the instruments used for the seismic data acquisition.
The ANR HYDROCRIZSTO-15-CE01-0010-02 project funded the field campaigns.
Collaborators:
Pasquet, S.1, Battais, A.2
1 Université de Paris, IPGP, CNRS, OZCAR – 75238 Paris Cedex 05, France.
2 Univ Rennes, CNRS, Géosciences Rennes – UMR 6118, 35000 Rennes, France.
References
- Dijkstra, E. W. A note on two problems in connexion with graphs, Numerische Mathematik, 1:269–271, 1959. [ DOI ]
- Moser, T. J. Shortest path calculation of seismic rays. Geophysics, 56(1):59-67, 1991. [ DOI ]
- Pasquet, S., Holbrook, W. S., Carr, B. J., & Sims, K. W. W. Geophysical imaging of shallow degassing in a Yellowstone hydrothermal system. Geophysical Research Letters, 43(23):12-027, 2016. [ DOI ]
- Pasquet, S., Marçais, J., Hayes, J. L., Sak, P. B., Ma, L., & Gaillardet, J. Catchment-Scale Architecture of the Deep Critical Zone Revealed by Seismic Imaging. Geophysical Research Letters, 49(13):e2022GL098433, 2022. [ DOI ]
- Rücker, C., Günther, T., & Wagner, F. M. pyGIMLi: An open-source library for modelling and inversion in geophysics. Computers & Geosciences, 109:10–123, 2017. [ DOI ]