Prediction of changes in landslide rates induced by rainfall

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• 作者：S. Bernardie ; N. Desramaut ; J.-P. Malet ; M. Gourlay ; G. Grandjean
• 关键词：Landslide ; Displacement pattern ; Prediction ; Monitoring ; Early warning
• 刊名：Landslides
• 出版年：2015
• 出版时间：June 2015
• 年：2015
• 卷：12
• 期：3
• 页码：481-494
• 全文大小：2,602 KB
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• 作者单位：S. Bernardie (1)
  N. Desramaut (1)
  J.-P. Malet (2)
  M. Gourlay (1)
  G. Grandjean (1)
  
  1. BRGM, Orl茅ans, France
  2. Institut de Physique du Globe de Strasbourg, CNRS UMR 7516, EOST, Universit茅 de Strasbourg, Strasbourg, France
  
• 刊物类别：Earth and Environmental Science
• 刊物主题：Earth sciences
  Applied Geosciences
  Geography
  Agriculture
  Civil Engineering
  
• 出版者：Springer Berlin Heidelberg
• ISSN：1612-5118

文摘

This work focuses on the development of a combined statistical-mechanical approach to predict changes in landslide displacement rates from observed changes in rainfall amounts. The forecasting tool FLAME (Forecasting Landslides Accelerations induced by Meteorological Events) associates (1) a statistical impulse response (IR) model to simulate the changes in landslide rates by computing a transfer function between the input signal (e.g. rainfall) and the output signal (e.g. displacement) and (2) a simple 1D mechanical (MA) model (e.g. viscoplastic rheology) to take into account changes in pore water pressure. The models have been applied to forecast the displacement rates at the Super-Sauze landslide (South East France). The performance of different combinations of models (IR model alone, MA model alone and a combination of the IR and MA models) is evaluated against observed changes in pore water pressures and displacement rates at the study site. Results indicate that the three models are able to reproduce the displacement pattern in the general kinematic regime (succession of acceleration and deceleration phases); conversely, extreme kinematic regimes such as fluidization of part of the landslide mass are not being reproduced. The approach constitutes however a robust tool to predict changes in displacement rates from rainfall or groundwater time series.