An enhanced catalog and earthquake source parameter estimations in the Lower-Rhine Embayment region, western Central Europe

A high-resolution earthquake catalog and detailed quantification of earthquake source parameters are essential for constraining fault structure and earthquake interactions. As a candidate site for the next-generation gravitational wave detector (i.e., Einstein Telescope), the Lower-Rhine Embayment region requires a comprehensive assessment of the fault distribution inferred through seismicity and earthquake source properties. In this study, we build an enhanced earthquake catalog using both permanent seismic stations and new data from temporary deployments together with AI-based techniques, including signal enhancement with a decoder-autoencoder denoiser, seismic phase detection using PhaseNet, and event association with PyOcto. We further refine earthquake locations with the NLL-SSST-coherence algorithm and then apply an automatic quality-control filter using event association to remove false detections resulting from the misinterpretation of teleseismic signals as local ones due to event denoising. We detect 3900 events for the period 2019 to 2025, with 2101 of them being classified as earthquakes. The enhanced catalog shows increased hypocentral depths along the NW-trending Sandgewand fault, with a maximum depth of 20 km at the southern end of the fault system. 

We also present the first results of a source-parameter catalog for earthquakes that occurred between 2000 and 2025 based on the dataset of Hinzen et al. (2021). Focal mechanisms for selected earthquakes in the region are determined with SKHASH by combining S/P ratios and first-motion polarities obtained from PhaseNet+. We fit individual earthquake spectral parameters, including corner frequency and seismic moment, and calculate stress-drop values for M_L≥1.5 events based on a circular crack model. Preliminary results indicate a median stress-drop value of 2.5 MPa across the region, with slightly higher stress-drop values observed on the Sandgewand fault relative to the Rurrand fault. In addition, we use the Distributed Acoustic Sensing (DAS) recordings to compute focal mechanism and corner frequency estimates and compare the results with broadband seismic stations for two earthquakes captured by DAS observations in the Netherlands in 2025. The enhanced spatial sampling density of DAS data provides additional constraints on earthquake source parameters and enables fault movement estimation that is difficult with seismic station data alone.