Seismic inversions of large, rapid landslides: what they can and cannot tell us about event dynamics

Researchers are increasingly incorporating force histories derived from long-period seismic waves into multidisciplinary studies of large, rapid landslides. The force history can provide important information about what happened during failure — information that complements data available from field investigations and remote sensing analyses. It can also provide additional constraints on the dynamics of landslide motion than can be used to validate and/or calibrate numerical landslide models. However, the inversions need to be of high quality and must be interpreted properly. Because this technique is relatively new, we are still discovering how to best conduct inversions to obtain robust results and how to appropriately interpret these results. In this study, we run numerical models of landslides with idealized source and path geometries using two different modeling packages, DAN3D and D-Claw, and we use the model outputs to generate synthetic long-period seismic data. Both models use depth-averaged flow equations over 3D topography, with DAN3D using semi-empirical material rheologies and D-Claw using a two-phase granular and fluid flow approach. To examine the influence of station azimuthal coverage and distance, we synthesize seismic data for a wide range of possible station configurations. We then use these synthetic seismic data to conduct seismic inversions using the recently released open-source Python-based software package, lsforce (https://code.usgs.gov/ghsc/lhp/lsforce). In doing these inversions, we add differing levels and types of noise, vary the inversion options (e.g., frequency range, regularization techniques) and then compare the results to the “known” dynamics of the modeled idealized landslides. We aim to understand common artefacts, limitations, and other potential pitfalls in interpretation, to guide the inversion process in future studies. We repeat this process for idealized landslides of increasing complexity, including multi-part failures, sinuous paths, and gradual versus sudden initiations, to simulate how these characteristics are reflected in the force history and to better understand what level of detail can be constrained from the seismic inversion. This work will help guide researchers to obtain more reliable information about landslide dynamics from seismic inversions in future landslide studies.