Topographic uncertainty quantification for flow-like landslide models via stochastic simulations

@article{Zhao2019TopographicUQ,
  title={Topographic uncertainty quantification for flow-like landslide
models via stochastic simulations},
  author={Hu Zhao and Julia Kowalski},
  journal={arXiv: Geophysics},
  year={2019}
}
Topography representing digital elevation models (DEMs) are essential inputs for computational models capable of simulating the run-out of flow-like landslides. Yet, DEMs are often subject to error, a fact that is mostly overlooked in landslide modeling. We address this research gap and investigate the impact of topographic uncertainty on landslide-run-out models. In particular, we will describe two different approaches to account for DEM uncertainty, namely unconditional and conditional… 

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