Skip to main content

Advertisement

SpringerLink
Log in

Landslide monitoring based on GNSS and automated inclinometer systems and dynamic modeling using SPH: a case study in Qinghai, China

  • Original Article
  • Published:
Environmental Earth Sciences Aims and scope Submit manuscript

Abstract

Landslide deformation monitoring is crucial for early warning and disaster prevention. This study presents a comprehensive landslide monitoring approach using global navigation satellite systems (GNSS) and automated inclinometers through a case study in Qinghai, China. Numerical modeling utilizing smoothed particle hydrodynamics (SPH) predicted potential hazards from dynamic landslide movements. The results demonstrate that the combination of GNSS and automated inclinometer systems provides accurate and real-time data on landslide movements, enabling timely responses to mitigate the risks associated with landslides. Monitoring results demonstrate active deformation of Zone III with sliding velocities up to 2.5 mm/day and deep subsurface displacement along bedrock shear planes at 14–26 m depths. SPH simulations predict a maximum run out of 115 m over 50 s for potential slope failure under a Ms 7.0 earthquake, with debris flows capable of blocking the river channel and inducing secondary hazards. Additionally, the numerical modeling using SPH provides useful insights into the potential hazard of landslides, which can be used to develop more effective mitigation strategies in the future. The findings of this study contribute to the development of a more holistic and effective approach to landslide monitoring and management.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Data availability

Data can be provided at the request of the author.

References

  • Allil R, Lima L, Allila AS et al (2021) FBG-based inclinometer for landslide monitoring in tailings dams. IEEE Sens J 99:1

    Google Scholar 

  • Beyabanaki SAR, Bagtzoglou AC, Liu L (2015) Applying disk-based discontinuous deformation analysis (DDA) to simulate Donghekou landslide triggered by the Wenchuan earthquake. Geomech Geoeng 11(3):1–12

    Google Scholar 

  • Biagi L, Ludovico F, Grec M et al (2016) Low-cost GNSS receivers for local monitoring: experimental simulation, and analysis of displacements. Sensors 16(12):2140

    Article  PubMed  PubMed Central  Google Scholar 

  • Bui HH, Fukagawa R, Sako K et al (2010) Lagrangian meshfree particles method (SPH) for large deformation and failure flows of geomaterial using elastic-plastic soil constitutive model. Int J Numer Anal Methods Geomech 32(12):1537–1570. https://doi.org/10.1002/nag.688

    Article  Google Scholar 

  • Carla T, Tofani V, Lombardi L et al (2019) Combination of GNSS, satellite InSAR, and GBInSAR remote sensing monitoring to improve the understanding of a large landslide in high alpine environment. Geomorphology 335(JUN.15):62–75

    Article  Google Scholar 

  • Castagnetti C, Bertacchini E, Corsini A, et al (2014) A reliable methodology for monitoring unstable slopes: the multi-platform and multi-sensor approach. In: Spie Remote Sensing. International Society for Optics and Photonics, 2014

  • Chen D, Qiao H (2014) Application and analysis of inclinometer in monitoring landslide deformation. Geotech Eng Tech 28(3):126–130

    Google Scholar 

  • Dowding C (2016) Comparison of TDR and inclinometers for slope monitoring. American Society of Civil Engineers

    Google Scholar 

  • Du J, Yin K, Wang J (2015) Simulation of three-dimensional movement of landslide=debris flow based on finite volume method. Chinese J Rock Mech Eng 34(3):480–488 (in Chinese)

    Google Scholar 

  • Farolfi G, Bianchini S, Casagli N (2019) Integration of GNSS and satellite InSAR data: derivation of fine-scale vertical surface motion maps of Po Plain, Northern Apennines, and Southern Alps. Italy IEEE Trans Geosci Remote Sens 57:319–328

    Article  Google Scholar 

  • Gao Y, Li B, Gao H, Chen L, Wang Y (2020) Dynamic characteristics of high-elevation and long-runout landslides in the Emeishan basalt area: a case study of the Shuicheng “7.23” landslide in Guizhou, China. Landslides 17:1663–1677

    Article  Google Scholar 

  • Gao H, Gao Y, Li B, Yin Y, Yang C, Wan J, Zhang T (2023) The Dynamic Simulation and Potential Hazards Analysis of the Yigong Landslide in Tibet. China Remote Sens 15:1322. https://doi.org/10.3390/rs15051322

    Article  Google Scholar 

  • Gili JA, Moya J, Corominas J et al (2021) Past, Present and Future Monitoring at the Vallcebre Landslide (Eastern Pyrenees, Spain). Appl Sci 11(2):571

    Article  CAS  Google Scholar 

  • Hamza V, Stopar B, Ambroi T et al (2020) Testing multi-frequency low-cost gnss receivers for geodetic monitoring purposes. Sensors 20(16):4375

    Article  PubMed  PubMed Central  Google Scholar 

  • Hu M, Liu MB, Xie MW et al (2015) Three-dimensional run-out analysis and prediction of flow-like landslides using smoothed particle hydrodynamics. Environ Earth Sci 73(4):1629–1640. https://doi.org/10.1007/s12665-014-3513-1

    Article  Google Scholar 

  • Hu M, Liu Q, Wu F et al (2017) GIS enabled SPH-soil modeling for the post-failure flow of landslides under seismic loadings. Int J Comput Methods. https://doi.org/10.1142/S0219876218500469

    Article  Google Scholar 

  • Huang Y, Dai Z (2014) Large deformation and failure simulations for geo-disasters using smoothed particle hydrodynamics method. Eng Geol 168(1):86–97

    Article  Google Scholar 

  • Huang Y, Zhang W, Xu Q et al (2012) Run-out analysis of flow-like landslides triggered by the Ms 8.0 2008 Wenchuan earthquake using smoothed particle hydrodynamics. Landslides. https://doi.org/10.1007/s10346-011-0285-5

    Article  Google Scholar 

  • Jun Y U . Application of the GNSS in Landslide Monitoring. Management & Technology of SME, 2019.

  • Komac M, Holley R, Mahapatra P, van der Marel H, Bavec M (2015) Coupling of GPS/GNSS and radar interferometric data for a 3D surface displacement monitoring of landslides. Landslides 12:241–257

    Article  Google Scholar 

  • Liang X, Gui L, Wang W et al (2021) Characterizing the development pattern of a colluvial landslide based on long-term monitoring in the three gorges reservoir. Remote Sens 13(2):224

    Article  Google Scholar 

  • Liu GR, Liu MB (2003) Smoothed particle hydrodynamics: a meshfree particle method. World Scientific

    Book  Google Scholar 

  • Malet JP, Maquaire O, Calais E (2002) The use of Global Positioning System techniques for the continuous monitoring of landslides: application to the Super-Sauze earthflow (Alpes-de-Haute-Provence, France). Geomorphology 43(1–2):33–54

    Article  Google Scholar 

  • Man HU, Mowen XIE, Liwei WANG (2016) SPH simulations of post-failure flow of landslides using elastic-plastic soil constitutive model. Chin J Geotech Eng 38(1):58–67 (in Chinese)

    Google Scholar 

  • Pastor M, Haddad B, Sorbino G et al (2010) A depth-integrated, coupled SPH model for flow-like landslides and related phenomena. Int J Numer Anal Methods Geomech. https://doi.org/10.1002/nag.705

    Article  Google Scholar 

  • Pei J (2020) Experimental study on a new FBG-based and Terfenol-D inclinometer for slope displacement monitoring. Measurement 151:107172

    Article  Google Scholar 

  • Shen N, Chen L, Wang L et al (2021) Short-Term Landslide Displacement Detection Based on GNSS Real-Time Kinematic Positioning. IEEE Trans Instrum Meas 99:1–1

    Google Scholar 

  • Tang CL, Hu JC, Lin ML et al (2009) The Tsaoling landslide triggered by the Chi-Chi earthquake, Taiwan: Insights from a discrete element simulation. Eng Geol 106(1–2):1–19

    Article  Google Scholar 

  • Weiss JR, Walters RJ, Morishita Y, Wright TJ, Lazecky M, Wang H, Hussain E, Hooper AJ, Elliott JR, Rollins C, et al (2020) High-resolution surface velocities and strain for anatolia from sentinel-1 InSAR and GNSS data. Geophys Res Lett 47(17). https://doi.org/10.1029/2020GL087376

  • Xiao R, Shi H, He X, Li Z, Jia D, Yang Z (2019) Deformation monitoring of reservoir dams using GNSS: an application to south-to-north water diversion project, China. IEEE Access 7:54981–54992

    Article  Google Scholar 

Download references

Funding

This work was funded by Science and Technology Support Program Project of Guizhou Province with Grant No. [2021] General 341, and funded by Research 2035 Pilot Plan of Southwest University (SWUXDPY22003).

Author information

Authors and Affiliations

  1. College of Engineering and Technology, Southwest University, Chongqing, 400715, China

    Man Hu, Yi Ren, Leyuan Xiao & Qiuting Tan

  2. State Nuclear Electric Power Planning Design & Research Institute Co., Ltd, Beijing, 100095, China

    Xiangyu Liu

  3. Guizhou Communication Construction Group Co., Ltd., Guizhou, 550001, China

    Hongju Han & Jiping Guo

Authors
  1. Man Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yi Ren
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Leyuan Xiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiangyu Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Qiuting Tan
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hongju Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jiping Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Man Hu: Supervision, Project administration, Formal analysis,Writing. Yi Ren: Coding,Data curation. Xiao Leyuan: Chart drawing. Xiang yu Liu: Software, Resources, Investigation, Funding acquisition. Qiu ting Tan: Coding,Software. Hong ju Han: Funding acquisition. Ji ping Guo：Funding acquisition.

Corresponding author

Correspondence to Man Hu.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hu, M., Ren, Y., Xiao, L. et al. Landslide monitoring based on GNSS and automated inclinometer systems and dynamic modeling using SPH: a case study in Qinghai, China. Environ Earth Sci 83, 170 (2024). https://doi.org/10.1007/s12665-024-11463-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12665-024-11463-y

Keywords

Search

Navigation