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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Revised manuscript not accepted
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Cited articles

Arulampalam, M. S., Maskell, S., Gordon, N., and Clapp, T.: A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking, IEEE Trans. Signal Process., 50, 174–188, https://doi.org/10.1109/78.978374, 2002. 
Baines, P. G.: Lorenz, EN 1963: Deterministic nonperiodic flow. Journal of the Atmospheric Sciences 20, 130–41, Prog. Phys. Geogr., 32, 475–480, https://doi.org/10.1177/0309133308091948, 2008. 
Baum, R. L., Savage, W. Z., and Godt, J. W.: TRIGRS – A Fortran Program for Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis, version 2.0, U.S. Geological Survey Open-File Report, 2008–1159, 75, 2008. 
Iverson, R. M.: Landslide triggering by rain infiltration, Water Resour. Res., 36, 1897–1910, https://doi.org/10.1029/2000wr900090, 2000. 
Jiang, Y. A., Liao, M. S., Zhou, Z. W., Shi, X. G., Zhang, L., and Balz, T.: Landslide Deformation Analysis by Coupling Deformation Time Series from SAR Data with Hydrological Factors through Data Assimilation, Remote Sens., 8, 179, https://doi.org/10.3390/rs8030179, 2016. 
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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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