Science China Earth Sciences

, Volume 60, Issue 4, pp 720–732 | Cite as

Spatio-temporal analysis and simulation on shallow rainfall-induced landslides in China using landslide susceptibility dynamics and rainfall I-D thresholds

  • WeiYue Li
  • Chun Liu
  • Marco Scaioni
  • WeiWei Sun
  • Yu Chen
  • DongJing Yao
  • Sheng Chen
  • Yang Hong
  • KaiHang Zhang
  • GuoDong Cheng
Research Paper

Abstract

An empirical simulation method to simulate the possible position of shallow rainfall-induced landslides in China has been developed. This study shows that such a simulation may be operated in real-time to highlight those areas that are highly prone to rainfall-induced landslides on the basis of the landslide susceptibility index and the rainfall intensity-duration (I-D) thresholds. First, the study on landslide susceptibility in China is introduced. The entire territory has been classified into five categories, among which high-susceptibility regions (Zone 4- ‘High’ and 5-‘Very high’) account for 4.15% of the total extension of China. Second, rainfall is considered as an external triggering factor that may induce landslide initiation. Real-time satellite-based TMPA 3B42 products may provide real rainfall spatial and temporal patterns, which may be used to derive rainfall duration time and intensity. By using a historical record of 60 significant past landslides, the rainfall I-D equation has been calibrated. The rainfall duration time that may trigger a landslide has resulted between 3 hours and 45 hours. The combination of these two aspects can be exploited to simulate the spatiotemporal distribution of rainfall-induced landslide hazards when rainfall events exceed the rainfall I-D thresholds, where the susceptibility category is ‘high’ or ‘very high’. This study shows a useful tool to be part of a systematic landslide simulation methodology, potentially providing useful information for a theoretical basis and practical guide for landslide prediction and mitigation throughout China.

Keywords

Rainfall-induced landslides Susceptibility Rainfall I-D thresholds Spatio-temporal Simulation 

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Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 41501458), China Postdoctoral Science Foundation Funded Project (Grant No. 2016M592860), National Basic Research Program of China (Grant No. 2013CB733204), Key Laboratory of Mining Spatial Information Technology of NASMG (Grant Nos. KLM201309), Science Program of Shanghai Normal University (Grant No. SK201525), the Shanghai Gaofeng & Gaoyuan Project for University Academic Program Development (Grant Nos. 2013LASW-A09 & SKHL1310) and the Center of Spatial Information Science and Sustainable Development Applications, Tongji University, Shanghai, China.

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Copyright information

© Science China Press and Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • WeiYue Li
    • 1
    • 2
  • Chun Liu
    • 3
  • Marco Scaioni
    • 3
    • 4
  • WeiWei Sun
    • 5
  • Yu Chen
    • 6
  • DongJing Yao
    • 7
  • Sheng Chen
    • 8
    • 9
  • Yang Hong
    • 10
    • 11
  • KaiHang Zhang
    • 12
  • GuoDong Cheng
    • 1
    • 2
  1. 1.Institute of Urban StudyShanghai Normal UniversityShanghaiChina
  2. 2.Cold and Arid Region Environmental and Engineering Research InstituteChinese Academy of SciencesLanzhouChina
  3. 3.College of Surveying and Geo-InformaticsTongji UniversityShanghaiChina
  4. 4.Department of Architecture, Built Environment and Construction EngineeringPolitecnico MilanoMilanoItaly
  5. 5.College of Architectural Engineering, Civil Engineering and EnvironmentNingbo UniversityNingboChina
  6. 6.Shandong Academy of Building ResearchJinanChina
  7. 7.Department of GeographyShanghai Normal UniversityShanghaiChina
  8. 8.School of Atmospheric SciencesSun Yat-sen UniversityGuangzhouChina
  9. 9.Key Laboratory of Beibu Gulf Environmental Evolution and Resources UtilizationGuangxi Teachers Education UniversityNanningChina
  10. 10.School of Civil Engineering and Environmental SciencesUniversity of OklahomaNormanUSA
  11. 11.Department of Hydraulic EngineeringTsinghua UniversityBeijingChina
  12. 12.Institute of TourismShanghai Normal UniversityShanghaiChina

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