Authors

Affiliations

1 Vietnam Geological Department; nh14vn@gmail.com

2 Vietnam Institute of Geosciences and Mineral Resources; ninh.dcks@gmail.com; thanhtung.vigmr@gmail.com; glg.tanet@gmail.com; nguyenhuyduong112358@gmail.com

3 Thuyloi University; trantheviet@tlu.edu.vn

*Corresponding: nh14vn@gmail.com; Tel.: +84–989258025

Abstracts

Landslides represent a severe natural hazard, particularly in mountainous areas where steep slopes, intense rainfall, and unstable geological conditions frequently trigger destructive ground movements. This study focuses on assessing the potential landslides in Tia Dinh Commune, Dien Bien province, Vietnam, using the LS-RAPID model to simulate and predict potential hazards. By conducting extensive field surveys, geophysical measurements, and applying extreme-case scenario simulations, we identified three high-risk landslide zones (S1, S2, S3) alongside a larger area, zone S, which poses the most significant threat due to its potential for widespread and rapid material displacement. Despite challenges posed by limited geotechnical data in remote regions, the LS-RAPID model effectively predicted movement patterns, velocity, and impact zones of landslides, significantly improving our understanding of landslide dynamics. The results underscore the importance of integrating landslide risk assessments into local land-use planning to ensure safer community development. Additionally, we recommend the installation of groundwater monitoring devices at strategically identified locations within these high-risk zones to support early warning systems and enable timely preventive measures. Our findings highlight the need for a proactive approach to landslide risk management, combining prediction models with comprehensive monitoring strategies. This research provides a valuable framework for disaster preparedness, offering insights adaptable for regions facing similar landslide threats.

Keywords

Cite this paper

Ha, N.D.; Ninh, N.H.; Viet, T.T.; Tung, N.T.; Tho, L.D.; Duong, N.H. Prediction of landslide hazard using LS-RAPID model: A case study in the Tia Dinh area (Dien Bien province, Vietnam)J. Hydro-Meteorol. 202421, 90-102.

References

1. Wieczorek, G.F. Landslide triggering mechanisms. In: Turner AK, Schuster RL (eds) Landslides: investigation and mitigation (Special Report). National Research Council, Transportation and Research Board Special Report 247, Washington, D.C. USA. 1996, pp. 76–90.

2. Glade, T.; Crozier, M.J. A review of scale dependency in landslide hazard and risk analysis. Landslide Hazard and Risk (eds Glade T, Anderson M, Crozier MJ), 2012, pp. 75–138. https://doi.org/10.1002/9780470012659.ch3.

3. An, H.; Viet, T.T.; Lee, G.H.; Kim, Y.; Kim, M.; Noh, S.; Noh, J. Development of time-variant landslide-prediction software considering three-dimensional subsurface unsaturated flow. Environ. Modell. Software 2016, 85, 172–183.

4. Tran, T.V.; Alvioli, M.; Lee, G.H.; An, H. Three-dimensional, time-dependent modeling of rainfall-induced landslides over a digital landscape: a case study. Landslides 2018, 15, 1071–1084. https://doi.org/10.1007/s10346-017-0931-7.

5. Plafker, G.; Ericksen, G.E. Nevados Huascarán Avalanches, Peru. Developments in Geotechnical Engineering (Editor(s): Barry Voight). Dev. Geotech. Eng. 1978, 14, 277–314. https://doi.org/10.1016/B978-0-444-41507-3.50016-7.

6. Sassa, K.; Nagai, O.; Solidum, R.; Yamazaki, Y.; Ohta, H. An integrated model simulating the initiation and motion of earthquake and rain induced rapid landslides and its application to the 2006 Leyte landslide. Landslides 2010, 7(3), 219–236. https://doi.org/10.1007/s10346-010-0230-z.

7. Hung, L.Q.; Van, N.T.H.; Son, P.V.; Ninh, N.H.; Tam, N.; Huyen, N.T. Landslide inventory mapping in the fourteen Northern Provinces of Vietnam: achievements and difficulties. In: Sassa K, Mikoš M, Yin Y (eds) Advancing culture of living with landslides, 2017, pp. 501–510.

8. Ha, N.D.; Quoc, H.L.; Sayama, T.; Sassa, K.; Takara, K.; Dang, K. An integrated WebGIS system for shallow landslide hazard early warning. (Eds) Understanding and Reducing Landslide Disaster Risk. WLF 2020. ICL Contribution to Landslide Disaster Risk Reduction. Springer, Cham. 2020, pp. 195–202. https://doi.org/10.1007/978-3-030-60311-3_22

9. Vung, D.V.; Tran, T.V.; Duc, H.N.; Huy. D.N. Advancements, challenges, and future directions in rainfall-induced landslide prediction: A comprehensive review. J. Eng. Technol. Sci. 2023, 55(4), 466–478. https://doi.org/10.5614/j.eng.technol.sci.2023.55.4.9.

10. Gao, Y.; Zhang, Y.; Ma, C.; Zheng, X.; Li, T.; Zeng, P.; Jin, J. Failure process and stability analysis of landslides in Southwest China while considering rainfall and supporting conditions. Front. Environ. Sci. 2023, 10, 1084151. https://doi.org/10.3389/fenvs.2022.1084151.

11. Zhang, J.; Qian, J.; Lu, Y.; Li, X.; Song, Z. Study on landslide susceptibility based on multi-model coupling: A case study of Sichuan Province, China. Sustainability 2024, 16, 6803. https://doi.org/10.3390/ su16166803.

12. Chen, J.H.; Lee, C.F. Landslide mobility analysis using MADflow. Int. Forum Landslide Disaster Manage. Hong Kong, China 2007, 2, 857–874.

13. Pirulli, M.; Mangeney, A. Results of back-analysis of the propagation of rock avalanches as a function of the assumed rheology. Rock Mech. Rock Eng. 2008, 41(1), 59–84. https://doi.org/10.1007/s00603-007-0143-x.

14. Roth, W. Dreidimensionale numerische Simulation von Felsmassenstürzen mittels der Methode der Distinkten Elemente (PFC). PhD Dissertation, Institute for Engineering Geology, Vienna University of Technology. 2003.

15. Hungr, O.; McDougall, S. Two numerical models for landslide dynamic analysis. Comput. Geosci. 2009, 35(5), 978–992. https://doi.org/10.1016/j.cageo.2007.12.003.

16. Sassa, K. Geotechnical model for the motion of landslides. Proceeding of 5th international symposium on landslides. “Landslides”, Balkema, Rotterdam, 1988, 1, 37–56.

17. Ha, N.D.; Sayama, T.; Sassa, K.; Takara, K.; Uzuoka, R.; Dang, K.; Pham, T.V. A coupled hydrological-geotechnical framework for forecasting shallow landslide hazard—a case study in Halong City, Vietnam. Landslides 2020, 17, 1619–1634. https://doi.org/10.1007/s10346-020-01385-8.

18. Sassa, K.; Dang, K.; He, B.; et al. A new high-stress undrained ring-shear apparatus and its application to the 1792 Unzen–Mayuyama megaslide in Japan. Landslides 2014, 11, 827–842. https://doi.org/10.1007/s10346-014-0501-1.

19. Setiawan, H.; Sassa, K.; Takara, K.; Ostric, M.; Miyagi, T.; Fukuoka, H. TXT-tool 4.081-1.2: Mechanism of the Aratozawa large-scale landslide induced by the 2008 Iwate-Miyagi earthquake. In (eds) Landslide Dynamics: ISDR-ICL Landslide Interactive Teaching Tools. Springer, Cham. 2018, pp. 819–831.

20. Jovančević, S.D.; Nagai, O.; Sassa, K.; Arbanas, Ž. TXT-tool 3.385-1.2: Deterministic Landslide Susceptibility Analyses Using LS-Rapid Software. In: (eds) Landslide Dynamics: ISDR-ICL Landslide Interactive Teaching Tools. Springer, Cham. 2018, pp. 169–179.

21. Gradiški, K.; Sassa, K.; He, B.; Arbanas, Ž.; Arbanas, S.M.; Krkač, M.; Kvasnička, P.; Oštrić, M. TXT-tool 3.385-1.1: Application of integrated landslide simulation model LS-rapid to the Kostanjek Landslide, Zagreb, Croatia. In: Sassa K, Tiwari B, Liu KF, McSaveney M, Strom A, Setiawan H (eds) Landslide Dynamics: ISDR-ICL Landslide Interactive Teaching Tools. Springer, Cham. 2018, pp. 101–109.

22. Dang, K.; Sassa, K.; Konagai, K.; Karunawarden, A.; Bandara, R.M.S.; Hirota, K.; Tan, Q.; Ha, N.D. Recent rainfall-induced rapid and long-traveling landslide on 17 May 2016 in Aranayaka, Kegalle District, Sri Lanka. Landslides 2019, 16(1), 155–164. https://doi.org/10.1007/s10346-018-1089-7.

23. Dang, K.; Loi, D.H.; Sassa, K.; Duc, D.M.; Ha, N.D. Hazard assessment of a rainfall-induced deep-seated landslide in Hakha City, Myanmar. (Eds) Understanding and Reducing Landslide Disaster Risk. WLF 2020. ICL Contribution to Landslide Disaster Risk Reduction. Springer. Cham. 2020, pp. 249–257. https://doi.org/10.1007/978-3-030-60706-7_23.

24. Loi, D.H.; Lam, H.Q.; Sassa, K.; Takara, K.; Dang, K.; Thanh, N.K.; Tien, P.V. The 28 July 2015 rapid landslide at Ha Long city, Quang Ninh, Vietnam. Landslides 2017, 14(3), 1207–1215. https://doi.org/10.1007/s10346-017-0814-y.

25. Quang, L.H.; Loi, D.H.; Sassa, K.; Takara, K.; Ochiai, H.; Dang, K.; Abe, S.; Asano, S.; Ha, D.N. Susceptibility assessment of the precursor stage of a landslide threatening Haivan Railway Station, Vietnam. Landslides 2018, 15, 309–325. https://doi.org/10.1007/s10346-017-0870-3.