Abstract
In the early morning of 24 June 2017, a slow-moving landslide suddenly accelerated and impacted Xinmo village after a sustained period of low-intensity rainfall. The landslide caused more than 80 casualties and damaged approximately 100 houses. Although many studies have been performed to understand the failure mechanism, the entire failure process of the Xinmo landslide is still not clear. In this study, a depth-integrated particle method coupled with a soil–water mixing model is used to back-analyse both slowly progressive movement and sudden failure processes of the Xinmo event. A representative volume element of the sliding zone is modeled, with consideration of erosion that progressively changes the solid concentration of the sliding mud. Numerical results show that the continuous erosion of sliding mud by rainwater accelerates the displacement rate of the landslide body. During the slow-moving stage, the simulated displacement rate is approximately 0.6 mm/year. On the other hand, the rapid failure process lasts 105 s from sudden failure to final deposition, with a maximum velocity of 58.6 m/s. As evidenced by the analysis of the seismic signals, the depth-integrated particle method has a good performance in simulating the rapid failure process of a landslide. The results demonstrate that the erosion of sliding mud resulted from the rainwater may play a critical role in the Xinmo landslide. This study contributes to understanding failure processes of rainfall-induced slow-moving landslides and provides guidelines on hazard prevention and mitigation.
Similar content being viewed by others
References
Abuzied S, Alrefaee H (2019) Spatial prediction of landslide-susceptible zones in El-Qaá area, Egypt, using an integrated approach based on GIS statistical analysis. B Eng Geol Environ 78:2169–2195. https://doi.org/10.1007/s10064-018-1302-x
Abuzied SM, Pradhan B (2020) Hydro-geomorphic assessment of erosion intensity and sediment yield initiated debris-flow hazards at Wadi Dahab Watershed. Egypt Georisk Assess Manag Risk Eng Syst Geohazards. https://doi.org/10.1080/17499518.2020.1753781
Abuzied S, Ibrahim S, Kaiser M, Saleem T (2016) Geospatial susceptibility mapping of earthquake-induced landslides in Nuweiba area, Gulf of Aqaba. Egypt J MT Sci 13(7):1286–1303. https://doi.org/10.1007/s11629-015-3441-x
Bayer B, Simoni A, Mulas M, Corsini A, Schmidt D (2018) Deformation responses of slow moving landslides to seasonal rainfall in the Northern Apennines, measured by InSAR. Geomorphology 308(14):293–306. https://doi.org/10.1016/j.geomorph.2018.02.020
Chen KT, Wu JH (2018) Simulating the failure process of the Xinmo landslide using discontinuous deformation analysis. Eng Geol 239:269–281. https://doi.org/10.1016/j.enggeo.2018.04.002
Cheng D, Cui Y, Su F, Jia Y, Choi CE (2018) The characteristics of Mocoa compound disaster event Colombia. Landslides 15(6):1223–1232. https://doi.org/10.1007/s10346-018-0969-1
Choi CE, Cui Y, Zhou GDD (2018a) Utilizing crowdsourcing to enhance the mitigation and management of landslides. Landslides 15(9):1889–1899. https://doi.org/10.1007/s10346-018-1034-9
Choi CE, Cui YF, Au K, Liu H, Wang J, Liu D, Wang H (2018b) Case study: effects of a partial-debris dam on riverbank erosion in the Parlung Tsangpo River. China WATER 10(3):250. https://doi.org/10.3390/w10030250
Cruden DM, Varnes DJ (1996) Landslide types and processes. In: Schuster T (ed) Landslides, investigation and mitigation, Special Report 247. Transportation research board, national research council. National Academy Press
Cui Y, Choi CE, Liu HD, Ng CWW (2018) Effects of particle size of mono-disperse granular flows impacting a rigid barrier. NAT HAZARDS 91(3):1179–1201. https://doi.org/10.1007/s11069-018-3185-3
Dong J, Zhang L, Li MH, Yu YH, Liao MS, Gong JY, Luo H (2018) Measuring precursory movements of the recent Xinmo landslide in Mao County, China with Sentinel-1 and ALOS-2 PALSAR-2 datasets. Landslides 15:135–144. https://doi.org/10.1007/s10346-017-0914-8
Fan XM, Xu Q, Scarigi G (2017a) Failure mechanism and kinematics of the deadly June 24th 2017 Xinmo landslide, Maoxian, Sichuan, China. Landslides 14:2129–2146. https://doi.org/10.1007/s10346-017-0907-7
Fan JR, Zhang XY, Su FH (2017b) Geometrical feature analysis and disaster assessment of the Xinmo landslide based on remote sensing data. J MT SCI 14(9):1677–1688. https://doi.org/10.1007/s11629-017-4633-3
Glastonbury J, Fell R (2008) Geotechnical Characterization of large slow, very slow and extremely slow landslides. Can Geotech J 45:984–1005. https://doi.org/10.1139/T08-021
Guo C, Cui Y (2020) Pore structure characteristics of debris flow source material in the Wenchuan earthquake area. Eng Geol 267:105499. https://doi.org/10.1016/j.enggeo.2020.105499
Handwerger AL, Roering J, Schmidt DA (2013) Controls on the seasonal deformation of slow-moving landslides. Earth Planet Sc Lett 377–378:239–247. https://doi.org/10.1016/j.epsl.2013.06.047
Handwerger AL, Fielding EJ, Huang MH, Bennett GL, Liang C, Schulz WH (2019) Widespread initiation, reactivation, and acceleration of landslides in the northern California Coast Ranges due to extreme rainfall. J Geophys Res-Earth 124:1782–1797. https://doi.org/10.1029/2019JF005035
Helmstetter A, Sornette D, Grasso JR, Andersen JV, Gluzman S, Pisarenko V (2004) Slider block friction model for landslides: application to Vaiont and La Clapie`re landslides. J Geophys Res 109:B02409. https://doi.org/10.1029/2002JB002160
Hilley GE, Bürgmann R, Ferretti A, Novali F, Rocca F (2004) Dynamics of slow-moving landslides from permanent scatter analysis. Science 304:1952–1955. https://doi.org/10.1126/science.1098821
Hu KH, Wu CH, Tang JB, Pasuto A, Li YJ, Yan SX (2018) New understandings of the June 24th 2017 Xinmo Landslide, Maoxian, Sichuan, China. Landslides 15:2465–2474. https://doi.org/10.1007/s10346-018-1073-2
Intrieri E, Raspini F, Fumagalli A (2017) The Maoxian landslide as seen from space: detecting precursors of failure with Sentinel-1 data. Landslides 15:123–133. https://doi.org/10.1007/s10346-017-0915-7
Iverson RM (2000) Landslide triggering by rain infiltration. Water Resour Res 36(7):1897–1910. https://doi.org/10.1029/2000WR900090
Iverson RM, Ouyang CJ (2015) Entrainment of bed material by Earth-surface mass flows: review and reformulation of depth-integrated theory. Rev Geophys 53(1):27–58. https://doi.org/10.1002/2013RG000447
Jiang HC, Mao X, Xu HY, Yang HL, Ma XL, Zhong N, Li YH (2014) Provenance and earthquake signature of the last deglacial Xinmocun lacustrine sediments at Diexi, East Tibet. Geomorphology 204:518–531. https://doi.org/10.1016/j.geomorph.2013.08.032
Krzeminska DM, Bogaard TA, Malet JP, van Beek LPH (2012) A model of hydrological and mechanical feedbacks of preferential crack flow in a slow-moving landslide. Hydrol Earth Syst Sci 17:949–959. https://doi.org/10.5194/hess-17-947-2013
Lacroix P, Berthier E, Maquerhua ET (2015) Earthquake-driven acceleration of slow-moving landslides in the Colca valley, Peru, detected from Pleiades images. Remote Sens Environ 165:148–158. https://doi.org/10.1016/j.rse.2015.05.010
Lacroix P, Handwerger AL, Bièvre G (2020) Life and death of slow-moving landslides. Nat Rev Earth Environ 1:404–419. https://doi.org/10.1038/s43017-020-0072-8
Li W, Chen Y, Liu F, Yang H, Liu J, Fu B (2019) Chain style landslide hazardous process: Constraints from seismic signals analysis of the 2017 Xinmo landslide, SW China. J Geophys Res-Sol Ea 124:2025–2037. https://doi.org/10.1029/2018JB016433
Ling S. (2015) Landslide damming in Western Sichuan Province, China, with special reference to the 1786 Dadu River and 1933 Diexi events. Master thesis, University of Waterloo, Ontario, Canada. URL: http://hdl.handle.net/10012/9496
Liu W, Wang D, Zhou J, He S (2019) Simulating the Xinmo landslide runout considering entrainment effect. Environ Earth Sci 78(19):585. https://doi.org/10.1007/s12665-019-8596-2
Luna BQ, Remaitre A, Van Asch ThWJ (2012) Analysis of debris flow behavior with a one dimensional run-out model incorporating entrainment. Eng Geol 128:63–75. https://doi.org/10.1016/j.enggeo.2011.04.007
Mansour MF, Morgenstern NR, Martin CD (2011) Expected damage from displacement of slow-moving slides. Landslides 8:117–131. https://doi.org/10.1007/s10346-010-0227-7
McDougall S, Hungr O (2005) Dynamic modelling of entrainment in rapid landslides. Can Geotech J 42(5):1437–1448. https://doi.org/10.1139/t05-064
McGuire LA, Rengers FK, Kean JW, Staley DM (2017) Debris flow initiation by runoff in a recently burned basin: Is grain-by-grain sediment bulking or en masse failure to blame? Geophys Res Lett 44:7310–7319. https://doi.org/10.1002/2017GL074243
Ouyang CJ, Zhao W, He SM (2017) Numerical modeling and dynamic analysis of the 2017 Xinmo landslide in Maoxian County China. J Mt Sci 14(9):1701–1711. https://doi.org/10.1007/s11629-017-4613-7
Parteli EJR, Gomes MAF, Brito VP (2005) Nontrivial temporal scaling in a Galilean stick-slip dynamics. Phys Rev E 71:036137. https://doi.org/10.1103/PhysRevE.71.036137
Pastor M, Haddad B, Sorbino G, Cuomo S, Drempetic V (2009) A depth-integrated, coupled SPH model for flow-like landslides and related phenomena. Int J Numer Anal Met 33:143–172. https://doi.org/10.1002/nag.705
Pastor M, Blanc T, Haddad B, Petrone S, Morles MS, Drempetic V, Issler D, Crosta GB, Cascini L, Sorbino G, Cuomo S (2014) Application of a SPH depth-integrated models to landslide run-out analysis. Landslides 11:793–812. https://doi.org/10.1007/s10346-014-0484-y
Pastor M, Yague A, Stickle MM, Manzanal D, Mira P (2018) A two-phase SPH model for debris flow propagation. Int J Numer Anal Met 42:418–448. https://doi.org/10.1002/nag.2748
Pei XJ, Guo B, Cui SH, Wang DP, Xu Q, Li TT (2018) On the initiation, movement and deposition of a large landslide in Maoxian County, China. J Mt Sci 15:1319–1330. https://doi.org/10.1007/s11629-017-4627-1
Scaringi G, Fan XM, Xu Q, Liu C, Ouyang CJ, Domènech G, Yang F, Dai LX (2018) Some considerations on the use of numerical methods to simulate past landslides and possible new failures: the case of the recent Xinmo landslide (Sichuan, China). Landslides 15:1359–1375. https://doi.org/10.1007/s10346-018-0953-9
Shao CJ, Li PY, Li Y (2017) Sliding mechanism of Maoxian landslide and geological condition analysis of formation of post-earthquake landslide. J Chengdu Univ Technol Sci Technol 44(4):385–402. https://doi.org/10.3969/j.issn.1671-9727.2017.04.01
Shibasaki T, Matsuura S, Okamoto T (2016) Experimental evidence for shallow, slow-moving landslides activated by a decrease in ground temperature. Geophys Res Lett 43:6975–6984. https://doi.org/10.1002/2016GL069604
Su LJ, Hu KH, Zhang WF (2017) Characteristics and triggering mechanism of Xinmo landslide on 24 June 2017 in Sichuan China. J Mt Sci 14(9):1689–1700. https://doi.org/10.1007/s11629-017-4609-3
van Asch ThWJ, Van Beek LPH, Bogaard TA (2007) Problems in predicting the mobility of slow-moving landslides. Eng Geol 91:46–55. https://doi.org/10.1016/j.enggeo.2006.12.012
Wang YS, Zhao B, Li J (2018) Mechanism of the catastrophic June 2017 landslide at Xinmo Village, Songping River, Sichuan Province, China. Landslides 15:333–345. https://doi.org/10.1007/s10346-017-0927-3
Yamada M, Mori J, Matsushi Y (2016) Possible stick-slip behavior before the rausu landslide inferred from repeating seismic events. Geophys Res Lett 43:9038–9044. https://doi.org/10.1002/2016GL069288
Yan Y, Cui YF, Guo J, Hu S, Wang Z, Yin SY (2020) Landslide reconstruction using seismic signal characteristics and numerical simulations: Case study of the 2017 “6.24” Xinmo landslide. Eng Geol 270(105582):1–15
Zhang N, Matsushima T (2016) Simulation of rainfall-induced debris flow considering material entrainment. Eng Geol 214:107–115. https://doi.org/10.1016/j.enggeo.2016.10.005
Zhang N, Matsushima T (2018) Numerical investigation of debris materials prior to debris flow hazards using satellite images. Geomorphology 308:54–63. https://doi.org/10.1016/j.geomorph.2018.02.008
Zhang N, Matsushima T, Yamada Y (2014) Efficient numerical simulation of debris flow with erosion and sedimentation. Proceedings of 14th IACMAG 1529–1534.
Zhou GGD, Zhou M, Shrestha MS, Song D, Choi CE, Cui KFE, Peng M, Shi Z, Zhu X, Chen H (2019) Experimental investigation of the longitudinal evolution of landslide dam breaching and outburst floods. Geomorphology 334:29–43. https://doi.org/10.1016/j.geomorph.2019.02.035
Acknowledgments
The authors wish to express their gratitude for the financial support from the National Natural Science Foundation of China (No. 41807257; 51909205), the Key Laboratory of Western China’s Mineral Resource and Geological Engineering (No. 300102260504), the Science and Technology Co-ordination and Innovation Project of Shaanxi Province in China (2016KTZDSF03-02) and the National Key Research and Development Program of China (2017YFD0800501).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Zhang, N., Zhang, J., Mu, Q. et al. Numerical modeling of the Xinmo landslide from progressive movement to sudden failure. Environ Earth Sci 80, 355 (2021). https://doi.org/10.1007/s12665-021-09651-1
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s12665-021-09651-1