Articles | Volume 26, issue 3
https://doi.org/10.5194/nhess-26-1621-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-26-1621-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Reconstruction and forecasting of slow-moving landslide displacement using a Kalman Filter approach
Mohit Mishra
Univ. Grenoble Alpes, CNRS, Grenoble INP – Institute of Engineering, GIPSA-Lab, 38000, Grenoble, France
Gildas Besançon
CORRESPONDING AUTHOR
Univ. Grenoble Alpes, CNRS, Grenoble INP – Institute of Engineering, GIPSA-Lab, 38000, Grenoble, France
Guillaume Chambon
Univ. Grenoble Alpes, CNRS INRAE, IRD, Grenoble INP – Institute of Engineering, IGE, Grenoble, France
Laurent Baillet
Univ. Grenoble Alpes, CNRS, ISTerre, Grenoble, France
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Saoirse Robin Goodwin, Thierry Faug, and Guillaume Chambon
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This paper considers how we can objectivity define stoppage of numerically-modelled snow avalanches. When modelling real topographies, numerically-modelled avalanche snow velocities typically do not converge to 0, so stoppage is defined with arbitrary criteria, which must be tuned on a case-by-case basis. We propose a new objective arrest criterion based on local flow properties, in tandem with a newly-implemented physical yielding criterion.
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We monitor the amount of snow on the ground using passive radiofrequency identification (RFID) tags. These small and inexpensive tags are wirelessly read by a stationary reader placed above the snowpack. Variations in the radiofrequency phase delay accurately reflect variations in snow amount, known as snow water equivalent. Additionally, each tag is equipped with a sensor that monitors the snow temperature.
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Ambient noise correlation is a broadly used method in seismology to monitor tiny changes in subsurface properties. Some environmental forcings may influence this method, including snow. During one winter season, we studied this snow effect on seismic velocity of the medium, recorded by a pair of seismic sensors. We detected and modeled a measurable effect during early snowfalls: the fresh new snow layer modifies rigidity and density of the medium, thus decreasing the recorded seismic velocity.
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Short summary
This work was initiated in the context of a large interdisciplinary research project about Risk at Grenoble University, France. It relates to the challenging topic of landslide monitoring, and combines geotechnical sciences with techniques from control system engineering. Considering a specific modelling approach, the study provides a methodology towards estimation of some landslide parameters and their use in motion prediction. This could then be extended to the design of alert systems.
This work was initiated in the context of a large interdisciplinary research project about Risk...
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