Skip to main content

Advertisement

Log in

Characteristics and geomorphology change detection analysis of the Jiangdingya landslide on July 12, 2018, China

  • Recent Landslides
  • Published:
Landslides Aims and scope Submit manuscript

Abstract

The reactivation of landslides has always been a prominent problem that has endangered town construction and people’s safety worldwide. At about 8 a.m. on July 12, 2018, on a mountain near the Bailong River in Nanyu Township, Zhouqu County, Gansu Province, China, a landslide collapse event occurred. About 10,000 m3 of sloped material slid into the Bailong River, with the largest stone reaching 3 m3. As a result, a large number of houses were flooded. Highways and bridges were destroyed. Using field investigations, unmanned aerial vehicle (UAV) photography, InSAR traces, historical records, and multiple remote sensing images, we extracted the landslide’s geometry and geomorphic parameters to quantify the characteristics of the Jiangdingya landslide. Based on high-resolution topographic data collected before and after the landslide, the change in the geomorphological factors, geomorphologic stability, and detection of the precursory motion before the landslide failure were analyzed to fully investigate the temporal geomorphological changes. Synthesizing the above research, we discuss the causes of landslide reactivation. The Jiangdingya landslide is a typical ancient landslide formed by the coupling of internal and external dynamics. Rainfall, seismic fault zone activity, human activities, and river erosion were the main causes of this reactivation event.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  • 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(1):293–306

    Google Scholar 

  • Catane SG, Veracruz NAS, Flora JRR, Go CMM, Santos ERU (2019) Mechanism of a low-angle translational block slide: evidence from the September 2018 Naga landslide, Philippines. Landslides 16:1709–1719

    Google Scholar 

  • Chen H (1991) Brief Introduction of Nanyu Large Landslide in Zhouqu County, Gansu. Northwest Hydropower 4:63

    Google Scholar 

  • Cheng D, Cui Y, Su F, Jia Y, Choi CE (2018) The characteristics of the Mocoa compound disaster event, Colombia. Landslides 15:1223–1232

    Google Scholar 

  • Cui Y, Cheng D, Choi CE, Jin W, Lei Y, Kargel JS (2019) The cost of rapid and haphazard urbanization: lessons learned from the Freetown landslide disaster. Landslides 16:1167–1176

    Google Scholar 

  • Dai K, Li Z, Tomás R, Liu G, Yu B, Wang X, Cheng H, Chen J, Stockamp J (2016) Monitoring activity at the Daguangbao mega-landslide (China) using Sentinel-1 TOPS time series interferometry. Remote Sens Environ 186:501–513

    Google Scholar 

  • Dai K, Xu Q, Li Z, Tomás R, Fan X, Dong X, Li W, Zhou Z, Gou J, Ran P (2019a) Post-disaster assessment of 2017 catastrophic Xinmo landslide (China) by spaceborne SAR interferometry. Landslides 16:1189–1199

    Google Scholar 

  • Dai K, Zhuo G, Xu Q, Li Z, Li W, Guan W (2019b) Tracing the pre-failure two-dimensional surface displacements of Nanyu landslide, Gansu Province with Rader Interferometry. Geomatics Inform Sci Wuhan Univ 44(12):1778–1786

    Google Scholar 

  • Darren T, Arko L, Steven DJ (2015) Time series analysis of landslide dynamics using an unmanned aerial vehicle (UAV). Remote Sens 7(2):1736–1757

    Google Scholar 

  • Davis WM (1889) The rivers and valleys of Pennsylvania. Natl Geogra Soc.

  • Dong J, Liao M, Xu Q, Zhang L, Tang M, Gong J (2018) Detection and displacement characterization of landslides using multi-temporal satellite SAR interferometry: A case study of Danba County in the Dadu River Basin. Eng Geol 240:95–109

    Google Scholar 

  • Fan X, Xu Q, Scaringi G, Zheng G, Huang R, Dai L, Ju Y (2018a) The “long” runout rock avalanche in Pusa, China, on August 28, 2017: a preliminary report. Landslides 16:139–154

    Google Scholar 

  • Fan X, Zhan W, Dong X, Van Westen CJ, Xu Q, Dai L, Yang Q, Huang R, Havenith HB (2018b) Analyzing successive landslide dam formation by different triggering mechanisms: the case of the Tangjiawan landslide, Sichuan, China. Eng Geol 243:128–144

    Google Scholar 

  • Fu X (2017) Research on revival mechanism and stability of disturbed ancient landslide. Xihua University, Chengdu

    Google Scholar 

  • Guo C, Zhang Y, Montgomery DR, Du Y, Zhang G, Wang S (2016) How unusual is the long-runout of the earthquake-triggered giant Luanshibao landslide, Tibetan Plateau, China? Geomorphology 259(15):145–154

    Google Scholar 

  • Guo C, Ren S, Li X, Zhang Y, Yang Z, Wu R, Jin J (2019) Development characteristics and reactivation mechanism of the Jiangdingya ancient landslide in the Nanyu Town, Zhouqu Country, Gansu Province. Geoscience 33(1):206–217

    Google Scholar 

  • Guo C, Zhang Y, Li X, Ren S, Yang Z, Wu R, Jin J (2020) Reactivation of giant Jiangdingya ancient landslide in Zhouqu County, Gansu Province, China. Landslides 17:179–190

    Google Scholar 

  • Handwerger AL, Roering JJ, Schmidt DA (2013) Controls on the seasonal deformation of slow-moving landslides. Earth Planet Sci Lett 377-378:239–247

    Google Scholar 

  • Hu S, Qiu H, Wang X, Gao Y, Wang N, Wu J, Yang D, Cao M (2018) Acquiring high-resolution topography and performing spatial analysis of loess landslides by using low-cost UAVs. Landslides 15:593–612

    Google Scholar 

  • Hu S, Qiu H, Pei Y, Cui Y, Xie W, Wang X, Yang D, Tu X, Zou Q, Cao P, Cao M (2019) Digital terrain analysis of a landslide on the loess tableland using high-resolution topography data. Landslides 16:617–632

    Google Scholar 

  • Lacroix P, Bièvre G, Pathier E, Kniess U, Jongmans D (2018) Use of Sentinel-2 images for the detection of precursory motions before landslide failures. Remote Sens Environ 215:507–516

    Google Scholar 

  • Ma S, Xu C, Shao X, Zhang P, Liang X, Tian Y (2018) Geometric and kinematic features of a landslide in Mabian Sichuan, China, derived from UAV photography. Landslides 16:373–381

    Google Scholar 

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

    Google Scholar 

  • Martino S, Antonielli B, Bozzano F, Caprari P, Discenza ME, Esposito C, Fiorucci M, Iannucci R, Marmoni GM, Schilirò L (2020) Landslides triggered after the 16 August 2018 Mw 5.1 Molise earthquake (Italy) by a combination of intense rainfalls and seismic shaking. Landslides 17:1177–1190

    Google Scholar 

  • Mu P (2011) Analysis on causes and stability of landslide at Jiangdingya in Zhouqu County of Gansu. China Water Resour 4:50–52

    Google Scholar 

  • Ouyang C, Zhao W, Xu Q, Peng D, Li W, Wang D, Zhou S, Hou S (2018) Failure mechanisms and characteristics of the 2016 catastrophic rockslide at Su village, Lishui, China. Landslides 15:1391–1400

    Google Scholar 

  • Pasternack GB, Wyrick JR (2017) Flood-driven topographic changes in a gravel-cobble river over segment, reach, and morphological unit scales. Earth Surf Process Landf 42(3):487–502

    Google Scholar 

  • Qiu H, Cui P, Hu S, Liu Q, Wang Y, Gao Y (2016) Size-frequency distribution of landslides in different landforms on the Loess Plateau of Northern Shaanxi. Earth Sci 41(2):343–350

    Google Scholar 

  • Qiu H, Cui P, Regmi AD, Hu S, Wang X, Zhang Y, He Y (2017) Influence of topography and volume on mobility of loess slides within different slip surfaces. Catena 157:180–188

    Google Scholar 

  • Qiu H, Cui P, Regmi A, Hu S, Wang X, Zhang Y (2018) The effects of slope length and slope gradient on the size distributions of loess slides: Field observations and simulations. Geomorphology 300:69–76

  • Qiu H, Cui Y, Pei Y, Yang D, Hu S, Wang X, Ma S (2020) Temporal patterns of nonseismically triggered landslides in Shaanxi Province, China. Catena 187:104356

  • Shahverdian S, Macfarlane W, Stevens G, Meier M, Wheaton JM (2017) Geomorphic response to Pilot River Restoration on the San Rafael River. A Pilot Installation of Beaver Dam Analogues, Utah Retrieved from https://doi.org/10.13140/RG.2.2.18963.37928

  • Singleton A, Li Z, Hoey T, Mullerc JP (2014) Evaluating sub-pixel offset techniques as an alternative to D-InSAR for monitoring episodic landslide movements in vegetated terrain. Remote Sens Environ 147:133–144

    Google Scholar 

  • Song S (2014) Formation mechanism analysis of Cuifengshan landslide in Lingshi County. Shanxi Architecture 40(36):74–75

    Google Scholar 

  • Strahler AN (1952) Hypsometric (area-altitude) analysis of erosional topography. Geol Soc Am Bull 63(11):1117–1142

    Google Scholar 

  • Sun Q, Zhang L, Ding X, Hu J, Li Z, Zhu J (2015) Slope deformation prior to Zhouqu, China landslide from InSAR time series analysis. Remote Sens Environ 156:45–57

    Google Scholar 

  • Teshebaeva K, Echtler HP, Bookhagen B, Strecker MR (2019) Deep-seated gravitational slope deformation (DSGSD) and slow moving landslides in the southern Tien Shan Mountains: new insights from InSAR, tectonic, and geomorphic analysis. Earth Surf Process Landf 44:2333–2348. https://doi.org/10.1002/esp.4648

    Article  Google Scholar 

  • Tian S, Chen N, Wu H, Yang C, Zhong Z, Rahman MM (2020) New insights into the occurrence of the Baige landslide along the Jinsha River in Tibet. Landslides 17:1207–1216

    Google Scholar 

  • Tomás R, Li Z, Lopez-Sanchez JM, Liu P, Singleton A (2016) Using wavelet tools to analyse seasonal variations from InSAR time-series data: a case study of the Huangtupo landslide. Landslides 13:437–450

    Google Scholar 

  • Wang G (2013) Lessons learned from protective measures associated with the 2010 Zhouqu debris flow disaster in China. Nat Hazards 69(3):1835–1847

    Google Scholar 

  • Wang J, Qi L, Cui X (1994) Analysis on landslide of Nanyu in Zhouqu county of Gansu province. Bull Soil Water Conserv 14(1):57–60

    Google Scholar 

  • Wartman J, Montgomery DR, Anderson SA, Keaton JR, Benoît J, Chapelle J, Gilbert R (2016) The 22 March 2014 Oso landslide, Washington, USA. Geomorphology 253(15):275–288

    Google Scholar 

  • Wheaton JM (2014) Trends and challenges in geomorphic change detection. Retrieved from https://doi.org/10.13140/RG.2.2.26758.68167

  • Xu J (2015) Discussion on causes and prevention and control measure of landslide geological disasters in Yuci Beishan. Shanxi Archit 41(24):85–86

    Google Scholar 

  • Yan Y, Cui Y, Tian X, Hu S, Liao L (2020) Seismic signal recognition and interpretation of the 2019 “7.23” Shuicheng landslide by seismogram stations. Landslides 17:1191–1206

    Google Scholar 

  • Yang W, Huang X, Zhang C, Liu T (2013) The deformation characteristics of the landslide along Pingding-Huama active fault zone and its prevention and control. Geol Bull China 32(12):1925–1935

    Google Scholar 

  • Yang W, Huang X, Zhang C, Si H (2014) Deformation behavior of landslides and their formation mechanism along Pingding-Huama active fault in Bailongjiang River region. J Jilin Univ (Earth Sci Ed) 44(2):574–583

    Google Scholar 

  • Yang W, Wang Y, Sun S, Wang Y, Ma C (2019) Using Sentinel-2 time series to detect slope movement before the Jinsha River landslide. Landslides 16:1313–1324

    Google Scholar 

  • Yuan Y, Zheng W, Zheng Y, Zhu S (1998) The characteristics of the Baitukan Landslide in Kangdin, Sichuan and its countermeasures. Chin J Geol Hazard Control 9(S1):235–241

    Google Scholar 

  • Zeng Y (2010) Research on the mechanism of groundwater in reactivating of old landslides on Reservoir Bank. China University of Geosiences Wuhan China

  • Zhang N (2018) Study on formation mechanism and comprehensive prevention of debris flow disasters in Sanyanyu valley, Zhouqu China. University of Geosciences Wuhan China

  • Zhang F, Huang X (2018) Trend and spatiotemporal distribution of fatal landslides triggered by non-seismic effects in China. Landslide 15(8):1663–1674

    Google Scholar 

  • Zhang F, Wang G, Kamai T, Chen W, Zhang D, Yang J (2013) Undrained shear behavior of loess saturated with different concentrations of sodium chloride solution. Eng Geol 155(6):69–79

    Google Scholar 

  • Zhang Y, Meng X, Chen G, Qiao L, Zeng R, Chang J (2016) Detection of geohazards in the Bailong River Basin using synthetic aperture radar interferometry. Landslides 13:1273–1284

    Google Scholar 

  • Zhang Y, Wu R, Guo C, Wang L, Yao X, Yang Z (2018) Research progress and prospect on reactivation of ancient landslides. Adv Earth Sci 33(7):728–740

    Google Scholar 

  • Zhou S, Ouyang C, An H, Jiang T, Xu Q (2020) Comprehensive study of the Beijing Daanshan rockslide based on real-time videos, field investigations, and numerical modeling. Landslides 17:1–15

    Google Scholar 

  • Zhuang J, Peng J (2014) A coupled slope cutting—a prolonged rainfall-induced loess landslide: a 17 October 2011 case study. Bull Eng Geol Environ 73:997–1011

    Google Scholar 

Download references

Funding

This work was funded by the Second Tibetan Plateau Scientific Expedition and Research Program (STEP) (Grant No. 2019QZKK0902), International Science & Technology Cooperation Program of China (Grant No. 2018YFE0100100), National Natural Science Foundation of China (Grant No. 41771539), Strategic Priority Research Program of Chinese Academy of Sciences (Grant No. XDA20030301), International Partnership Program of Chinese Academy of Sciences (Grant No. 131551KYSB20160002), China Postdoctoral Science Foundation (Grant No. 2019 M663792), and Scientific Research Foundation of Northwest University (Grant No. 360051900075).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Haijun Qiu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ma, S., Qiu, H., Hu, S. et al. Characteristics and geomorphology change detection analysis of the Jiangdingya landslide on July 12, 2018, China. Landslides 18, 383–396 (2021). https://doi.org/10.1007/s10346-020-01530-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10346-020-01530-3

Keywords

Navigation