Operational Estimation of Landslide Runout: Comparison of Empirical and Numerical Methods
| Autor: | Yannick Thiery, Anne Mangeney, Gilles Grandjean, Jeremy Rohmer, Antoine Lucas, Clara Levy, Marc Peruzzetto |
|---|---|
| Přispěvatelé: | Institut de Physique du Globe de Paris (IPGP), Institut national des sciences de l'Univers (INSU - CNRS)-IPG PARIS-Université de La Réunion (UR)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Bureau de Recherches Géologiques et Minières (BRGM) (BRGM), Centre National de la Recherche Scientifique (CNRS)-Université de La Réunion (UR)-Université Paris Diderot - Paris 7 (UPD7)-IPG PARIS-Institut national des sciences de l'Univers (INSU - CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
landslide
[SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph] 0211 other engineering and technologies 02 engineering and technology 010502 geochemistry & geophysics 01 natural sciences Power law [SDU.STU.PL]Sciences of the Universe [physics]/Earth Sciences/Planetology statistical analysis Cliff [SDU.STU.GM]Sciences of the Universe [physics]/Earth Sciences/Geomorphology [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environment uncertainty Scaling 0105 earth and related environmental sciences 021110 strategic defence & security studies geography geography.geographical_feature_category Numerical analysis lcsh:QE1-996.5 Prediction interval runout Landslide Geodesy Debris lcsh:Geology numerical modeling 13. Climate action General Earth and Planetary Sciences Martinique Geology |
| Zdroj: | Geosciences, Vol 10, Iss 424, p 424 (2020) Geosciences Geosciences, Geological Survey of Iran, 2020, 10 (11), pp.424. ⟨10.3390/geosciences10110424⟩ Volume 10 Issue 11 |
| ISSN: | 2076-3263 1023-7429 |
| DOI: | 10.3390/geosciences10110424⟩ |
| Popis: | A key point of landslide hazard assessment is the estimation of their runout. Empirical relations linking angle of reach to volume can be used relatively easily, but they are generally associated with large uncertainties as they do not consider the topographic specificity of a given study site. On the contrary, numerical simulations provide more detailed results on the deposits morphology, but their rheological parameters can be difficult to constrain. Simulating all possible values can be time consuming and incompatible with operational requirements of rapid estimations. We propose and compare three operational methods to derive scaling power laws relating the landslide travel distance to the destabilized volume. The first one relies only on empirical relations, the second one on numerical simulations with back-analysis, and the third one combines both approaches. Their efficiency is tested on three case studies: the Samperre cliff collapses in Martinique, Lesser Antilles (0.5 to 4× 106 m3), the Frank Slide rock avalanche (36× 106 m3) and the Samperre cliff collapses in Martinique, Lesser Antilles (0.5 to 4× 106 m3) the Fei Tsui debris slide in Hong Kong (0.014× 106 m3). Purely numerical estimations yield the smallest uncertainty, but the uncertainty on rheological parameters is difficult to quantify. Combining numerical and empirical approaches allows to reduce the uncertainty of estimation by up to 50%, in comparison to purely empirical estimations. However, it may also induces a bias in the estimation, though observations always lie in the 95% prediction intervals. We also show that empirical estimations fail to model properly the dependence between volume and travel distance, particularly for small landslides (< 20,000 < 0.02× 106 m3). |
| Databáze: | OpenAIRE |
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