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Prediction on landslide displacement using a new combination model: a case study of Qinglong landslide in China

Author

Listed:
  • Weidong Wang

    (Central South University
    Key Laboratory of Engineering Structures of Heavy-Haul Railway, Ministry of Education)

  • Jiaying Li

    (Central South University)

  • Xia Qu

    (China Railway Siyuan Survey and Design Group Co.LTD)

  • Zheng Han

    (Central South University)

  • Pan Liu

    (Central South University)

Abstract

Prediction on landslide displacement plays an important role in landslide early warning. Many models have been proposed for this purpose. However, the accuracy of the prediction results by these models often varies under different conditions. Rational evaluation and comprehensive consideration of these results still remain a scientific challenge. A new comprehensive combination model is proposed to predict the landslides displacement. The elementary displacement prediction is made by the support vector machine model, the exponential smoothing model, and the gray model (GM)(1,1). The results of the models are comprehensively evaluated by combining the results and introducing the accuracy matrix. The optimal weight in the evaluation work is obtained. A rational prediction result can be attained based on the so-called combination model. The proposed method has been tested by the application of Qinglong landslides in Guizhou Province, China. The comparison between the prediction results and in situ measurement shows that the prediction precision of the proposed model is satisfactory. The root-mean-square error (RMSE) of the combination model can be reduced to 1.4316 (monitoring site JCK2), 1.2623 (monitoring site JCK4), 2.3758 (monitoring site JCK6), 2.2704 (monitoring site JCK8), 1.4247 (monitoring site JCK11), and 0.9449 (monitoring site JCK12), which is much lower than the RMSE of the individual models.

Suggested Citation

  • Weidong Wang & Jiaying Li & Xia Qu & Zheng Han & Pan Liu, 2019. "Prediction on landslide displacement using a new combination model: a case study of Qinglong landslide in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 96(3), pages 1121-1139, April.
  • Handle: RePEc:spr:nathaz:v:96:y:2019:i:3:d:10.1007_s11069-019-03595-3
    DOI: 10.1007/s11069-019-03595-3
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    References listed on IDEAS

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    1. Xiuzhen Li & Jiming Kong & Zhenyu Wang, 2012. "Landslide displacement prediction based on combining method with optimal weight," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 61(2), pages 635-646, March.
    2. Dalia Kirschbaum & Robert Adler & Yang Hong & Stephanie Hill & Arthur Lerner-Lam, 2010. "A global landslide catalog for hazard applications: method, results, and limitations," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 52(3), pages 561-575, March.
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