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Discussion papers
https://doi.org/10.5194/nhess-2019-16
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2019-16
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 12 Feb 2019

Research article | 12 Feb 2019

Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Natural Hazards and Earth System Sciences (NHESS).

Landslides Data Assimilation Using TRIGRS Based on Particle Filtering

Changhu Xue1, Guigen Nie1,2, Jie Dong3, Shuguang Wu1, Jing Wang1, Xiuzhen Li4, and Xiaogang Zhang4 Changhu Xue et al.
  • 1GNSS Research Center, Wuhan University, Wuhan, 430079, China
  • 2Collaborative Innovation Center for Geospatial Information Technology, Wuhan, 430206, China
  • 3State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, China
  • 4Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610041, China

Abstract. Studies about landslide modeling and monitoring are becoming more diverse. Data assimilation is an approach to combine mechanism models and observations. In this study, an improved particle filtering algorithm is used to assimilate the transient rainfall infiltration and grid-based regional slope-stability analysis (TRIGRS) model and landslide surface deformation monitoring data observed with GPS and InSAR. After assimilation calculation, FS has been effectively corrected, rather than continuously decreasing as the background model output. The root mean square difference (RMSD) tends to decrease from a maximum of 0.084 to a minimum of 0.026 in the process of assimilation, which means the assimilation process makes the model output FS closer to the actual observations. The friction angle (φ), which is an investigated parameter, can be updated and fed back in each step of assimilation. The value of the investigated parameter makes the model output closer to the observation. The groundwater pressure head is output as an assimilation result simultaneously.

Changhu Xue et al.
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Latest update: 18 Jul 2019
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Short summary
This paper provides an approach to apply data assimilation method to stability analysis and parameter update and feedback in a landslide. The experiment is implemented by particle filter algorithm. The result FS sequence of TRIGRS output decreases continuously with time and the assimilation can effectively correct the FS of the model output. The RMSD of FS indicates the assimilation results can correct the estimation of TRIGRS output close to actual observations.
This paper provides an approach to apply data assimilation method to stability analysis and...
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