Group B, Poster #074, Tectonic Geodesy
Automated block closure and resolution tests in dense block models: preliminary results
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Poster Presentation
2022 SCEC Annual Meeting, Poster #074, SCEC Contribution #12264 VIEW PDF
ly preform remains a challenge. In this work, we compare block models with varying geometries in both toy models and larger-scale models. Larger-scale models are based on Southern California and generated with a block closure algorithm. The block closure algorithm automatically closes mapped fault segments into closed blocks using a modified cone search with adjustable parameters and allows us to produce suites of block geometries to explore the influence of block closure choices on estimated slip rates. Here, we perform resolution tests by employing the block closure algorithm to the dense Fault Sections database of the 2023 update to the USGS National Seismic Hazard Model (NSHM2023) in southern California. We estimate initial fault slip rates regularized with total variation regularization (TVR) within a representative block geometry; TVR allows robust slip rate estimation within a dense block model with many poorly constrained blocks. We use these estimated rates to generate a forward model. We then perform TVR inverse models on our algorithmically generated suite of block geometries, constrained by forward data, to assess block model performance. Toy model comparisons, as well as preliminary Southern California-based models, show that TVR slip rate estimates fit best on models that are similar in geometries to the representative model.
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