Articles | Volume 19, issue 7
https://doi.org/10.5194/nhess-19-1387-2019
https://doi.org/10.5194/nhess-19-1387-2019
Research article
 | 
11 Jul 2019
Research article |  | 11 Jul 2019

Simultaneous state–parameter estimation of rainfall-induced landslide displacement using data assimilation

Jing Wang, Guigen Nie, Shengjun Gao, and Changhu Xue

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Revised manuscript not accepted
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Cited articles

Abbaszadeh, P., Moradkhani, H., and Yan, H.: Enhancing Hydrologic Data Assimilation by Evolutionary Particle Filter and Markov Chain Monte Carlo, Adv. Water Resour., 111, 192–204, https://doi.org/10.1016/j.advwatres.2017.11.011, 2017. 
Chaussard, E., Wdowinski, S., Cabral-Cano, E., and Amelung, F.: Land subsidence in central Mexico detected by ALOS InSAR time-series, Remote Sens. Environ., 140, 94–106, https://doi.org/10.1016/j.rse.2013.08.038, 2014. 
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Desai, C. S., Samtani, N. C., and Vulliet, L.: Constitutive Modeling and Analysis of Creeping Slopes, J. Geotech. Eng., 122, 43–56, https://doi.org/10.1061/(ASCE)0733-9410(1995)121:1(43), 1995. 
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Short summary
It is necessary to do some prevention study of landslide hazard like the early warning and deformation prediction. This research proposes a new strategy to predict displacement of the landslide. Results confirm the accuracy and effectiveness of this method in displacement prediction, which can provide assistance in early risk assessment and landslide forecasting.
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