Articles | Volume 18, issue 10
https://doi.org/10.5194/nhess-18-2801-2018
https://doi.org/10.5194/nhess-18-2801-2018
Research article
 | 
26 Oct 2018
Research article |  | 26 Oct 2018

Data assimilation with an improved particle filter and its application in the TRIGRS landslide model

Changhu Xue, Guigen Nie, Haiyang Li, and Jing Wang

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Latest update: 28 Mar 2024
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Short summary
Landslide is a common and sudden geological disaster, which is difficult to monitor and prevent efficiently. This paper introduces an improved algorithm of data assimilation that merges the observations into a landslide evolutionary model. A nonlinear model experiment is applied to verify the feasibility of the algorithm. An application of landslide simulation is carried out. Results show that the estimations of states can effectively correct the running offset after assimilation.
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