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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 19, issue 7
Nat. Hazards Earth Syst. Sci., 19, 1387-1398, 2019
https://doi.org/10.5194/nhess-19-1387-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue: Advances in computational modelling of natural hazards and...

Nat. Hazards Earth Syst. Sci., 19, 1387-1398, 2019
https://doi.org/10.5194/nhess-19-1387-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 11 Jul 2019

Research article | 11 Jul 2019

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

Jing Wang1, Guigen Nie1,2, Shengjun Gao3, and Changhu Xue1 Jing Wang et al.
  • 1GNSS Research Center, Wuhan University, Wuhan, 430079, China
  • 2Collaborative Innovation Center for Geospatial Information Technology, Wuhan, 430079, China
  • 3Chinese Antarctic Center of Surveying and Mapping, Wuhan, 430079, China

Abstract. Landslide displacement prediction has great practical engineering significance to landslide stability evaluation and early warning. The evolution of landslide is a complex dynamic process, and applying a classical prediction method will result in significant error. The data assimilation method offers a new way to merge multisource data with the model. However, data assimilation is still deficient in the ability to meet the demand of dynamic landslide systems. In this paper, simultaneous state and parameter estimation (SSPE) using particle-filter-based data assimilation is applied to predict displacement of the landslide. A landslide SSPE assimilation strategy can make use of time-series displacements and hydrological information for the joint estimation of landslide displacement and model parameters, which can improve the performance considerably. We select Xishan Village, Sichuan Province, China, as the experiment site to test the SSPE assimilation strategy. Based on the comparison of actual monitoring data with prediction values, results strongly suggest the effectiveness and feasibility of the SSPE assimilation strategy in short-term landslide displacement estimation.

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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.
It is necessary to do some prevention study of landslide hazard like the early warning and...
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