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Spatial distribution and susceptibility zoning of geohazards along the Silk Road, Xian-Lanzhou

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Abstract

The region between Xi’an and Lanzhou is the first and most important part of the so-called Silk Road in China. However, this section is highly susceptible to geohazards, including landslides, debris flows, etc., as a result of complex geological formations, steep landforms, seasonal heavy rainfall, and intensive anthropogenic activity that characterize this region. These geohazards have resulted in significant damage to the local infrastructure and economy and are becoming increasingly frequent with time. To identify the distribution of characteristics of geohazards and susceptibility zoning in this region, a frequency analysis and logistic analysis were used to study the spatial distribution of geohazards. The key factors of surface topography and geology associated with geohazards were considered, including slope gradient, height differential, profile curvature, slope aspect, and rock hardness. First, the distribution and frequency of geohazards were discussed in relation to the five factors. Second, each factor’s influence was evaluated by logistic regression and the relative importance of each of the variables was discussed. Finally, geohazard susceptibility zoning was mapped using logistic regression and geography information system tools. The results of the susceptibility zoning model were validated using the locations that had recorded geohazards in recent decades; the accuracy of the model was greater than 86.8 %. The model validation proved that there was good agreement between the susceptibility mapping and historically recorded geohazards. The logistic regression model produced acceptable results using a receiver operating characteristics curve in which the total area under the receiver operating characteristics curve was 0.879. The results of this study can assist in preliminary planning for land use, particularly with reference to construction projects in high risk areas.

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References

  • Aleotti P, Chowdhury R (1999) Landslide hazard assessment: summary review and new perspectives. Bull Eng Geol Environ 58(1):21–44

    Article  Google Scholar 

  • Anbalagan R (1992) Landslide hazard evaluation and zonation mapping in mountainous terrain. Eng Geol 32(4):269–277

    Article  Google Scholar 

  • Ayalew L, Yamagishi H (2005) The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology 65:15–31

    Article  Google Scholar 

  • Baghem M, Chouabi B, Abdel M, Demdoum C, Abdeslem D (2012) Geologic, topographic and climatic controls in landslide hazard assessment using GIS modeling: a case study of Souk Ahras region, NE Algeria. Quat Int 302(17):224–237

    Google Scholar 

  • Bai S, Lu G, Wang J, Zhou P, Ding L (2010a) GIS-based rare events logistic regression for landslide-susceptibility mapping of Lianyungang, China. Environ Earth Sci 62(1):139–149

    Article  Google Scholar 

  • Bai SB, Wang J, Lu G, Zhou P, Hou SS, Xu SN (2010b) GIS-based logistic regression for landslide susceptibility mapping of the Zhongxian segment in the Three Gorges area China. Geomorphology 115:23–31

    Article  Google Scholar 

  • Carrara A, Pike RJ (2008) GIS technology and models for assessing landslide hazard and risk. Geomorphology 94(3):257–260

    Article  Google Scholar 

  • Cui P, Zhou GGD, Zhu XH, Zhang JQ (2012) Scale amplification of natural debris flows caused by cascading landslide dam failures. Geomorphology 123:1–17

    Google Scholar 

  • Cui P, Zou Q, Xiang LZ, Zeng C (2013) Risk assessment of simultaneous debris flows in mountain townships. Prog Phys Geogr 37(4):516–542

    Article  Google Scholar 

  • Cui P, Zhang J, Yang Z, Chen X, You Y, Li Y (2014) Activity and distribution of geohazards induced by the Lushan earthquake, April 2013. Nat Hazards 73(2):711–726

    Article  Google Scholar 

  • Dai FC, Lee CF (2002) Landslide characteristics and slope instability modeling using GIS, Lantau Island, Hong Kong. Geomorphology 42:213–228

    Article  Google Scholar 

  • Dai FC, Lee CF, Zhang XH (2001) GIS-based geo-environmental evaluation for urban land-use planning: a case study. Eng Geol 61:257–271

    Article  Google Scholar 

  • Daneshvar MRM, Bagherzadeh A (2011) Landslide hazard zonation assessment using GIS analysis at Golmakan Watershed, northeast of Iran. Front Earth Sci 5(1):70–81

    Article  Google Scholar 

  • Ermini L, Catani F, Casagli N (2005) Artificial neural networks applied to landslide susceptibility assessment. Geomorphology 66:327–343

    Article  Google Scholar 

  • Fawcett T (2006) An introduction to ROC analysis. Pattern Recogn Lett 27(8):861–874

    Article  Google Scholar 

  • Fell R, Corominas J, Bonnard C, Cascini L, Leroi E, Savage WZ (2008) Guidelines for landslide susceptibility, hazard and risk zoning for land use planning. Eng Geol 102(3–4):85–98

    Article  Google Scholar 

  • Fernandes NF, Renato RF, Guimaraes RAT, Gomes BC, Vieira DR, Montgomery HG (2004) Topographic controls of landslides in Rio de Janeiro: field evidence and modeling. Catena 55:163–181

    Article  Google Scholar 

  • García-Rodríguez MJ, Malpica JA, Benito B, Díaz M (2008) Susceptibility assessment of earthquake-triggered landslides in El Salvador using logistic regression. Geomorphology 95:172–191

    Article  Google Scholar 

  • Guzzetti F, Reichenbach P, Ardizzone F, Cardinali M, Galli M (2006) Estimating the quality of landslide susceptibility models. Geomorphology 81:166–184

    Article  Google Scholar 

  • Guzzetti F, Peruccacci S, Rossi M, Stark CP (2008) The rainfall intensity-duration control of shallow landslides and debris flows: an update. Landslides 5(1):3–17

    Article  Google Scholar 

  • Iverson RM (1997) The physics of debris flows. Rev Geophys 35:245–296

    Article  Google Scholar 

  • Kayastha P (2012) Application of fuzzy logic approach for landslide susceptibility mapping in Garuwa sub-basin, East Nepal. Front Earth Sci 6(4):420–432

    Article  Google Scholar 

  • Keefer DK, Wilson RC, Mark RK, Brabb EE, Brown WM (1987) Real-time landslide warning during heavy rainfall. Science 238(13):921–925

    Article  Google Scholar 

  • Lee S (2007) Comparison of landslide susceptibility maps generated through multiple logistic regression for three test areas in Korea. Earth Surf Proc Land 32(14):2133–2148

    Article  Google Scholar 

  • Lee S, Min K (2001) Statistical analysis of landslide susceptibility at Yongin, Korea. Environ Geol 40(9):1095–1113

    Article  Google Scholar 

  • Lee S, Pradhan B (2007) Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models. Landslides 4:33–41

    Article  Google Scholar 

  • Li YS (1992) Xi’an crack and the Weihe River basin active fault research. Seismological Press, Beijing (in Chinese with English Abstract)

    Google Scholar 

  • Li PY, Qian H, Wu JH (2014) Accelerate research on land creation. Nature 510:29–31

    Article  Google Scholar 

  • Li P, Qian H, Howard KWF, Wu J (2015) Building a new and sustainable “Silk Road economic belt”. Environ Earth Sci. doi:10.1007/s12665-015-4739-2

    Google Scholar 

  • Li P, Wu J, Qian H (2016a) Hydrochemical appraisal of groundwater quality for drinking and irrigation purposes and the major influencing factors: a case study in and around Hua County, China. Arab J Geosci 9(1):15. doi:10.1007/s12517-015-2059-1

    Article  Google Scholar 

  • Li P, Wu J, Qian H (2016b) Preliminary assessment of hydraulic connectivity between river water and shallow groundwater and estimation of their transfer rate during dry season in the Shidi River, China. Environ Earth Sci 75(2):99. doi:10.1007/s12665-015-4949-7

    Article  Google Scholar 

  • Liu XL, Yu L, Liu CJ, Shi J, Yu PJ, Fang J, Shi WH (2012) Debris flow and landslide hazard mapping and risk analysis in China. Front Earth Sci 6(3):306–313

    Article  Google Scholar 

  • Ministry of Construction of the People’s Republic of China (2009) Code for investigation of geotechnical engineering 2009-GB 50021 2001

  • Montgomery DR, Dietrich WE (1994) A physically based model for the topographic control on shallow landsliding. Water Resour Res 30:1153–1171

    Article  Google Scholar 

  • Nandi A, Shakoor A (2010) A GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analyses. Eng Geol 110:11–20

    Article  Google Scholar 

  • Nefeslioglu HA, Sezer E, Gokceoglu C, Bozkir AS, Duman TY (2010) Assessment of landslide susceptibility by decision trees in the metropolitan area of Istanbul, Turkey. Math Probl Eng 90(105):89–93

    Google Scholar 

  • Owen LA, Kamp U, Khattak GA, Harp EL, Keefer DK, Bauer MA (2008) Landslides triggered by the 8 October 2005 Kashmir earthquake. Geomorphology 94(1):1–9

    Article  Google Scholar 

  • Peng JB, Zhang J, Su SR, Mi FS (1992) Active faults and geological hazards in Wei Basin. Northwest University Press, Xi’an (in Chinese with English Abstract)

    Google Scholar 

  • Peng J, Fan Z, Wu D, Zhuang J, Dai F, Chen W, Zhao C (2015) Heavy rainfall triggered loess-mudstone landslide and subsequent debris flow in Tianshui, China. Eng Geol 186:79–90

    Article  Google Scholar 

  • Piacentini D, Troiani F, Soldati M, Notarnicola C, Savelli D, Schneiderbauer SSC (2012) Statistical analysis for assessing shallow-landslide susceptibility in South Tyrol (south-eastern Alps, Italy). Geomorphology 151–152:196–206

    Article  Google Scholar 

  • Pradhan B (2011) Use of GIS-based fuzzy logic relations and its cross application to produce landslide susceptibility maps in three test areas in Malaysia. Environ Earth Sci 63(2):329–349

    Article  Google Scholar 

  • Swets JA (1988) Measuring the accuracy of diagnostic systems. Science 240:1285–1293

    Article  Google Scholar 

  • Takahashi T (1981) Debris flow. Annu Rev Fluid Mech 13(1):57–77

    Article  Google Scholar 

  • Tang C, Zhu J, Ding J, Cui XF, Chen L, Zhang JS (2011) Catastrophic debris flows triggered by a 14 August 2010 rainfall at the epicenter of the Wenchuan earthquake. Landslides 8(4):485–497

    Article  Google Scholar 

  • Tang C, van Asch TWJ, Chang M, Chen GQ, Zhao XH, Huang XC (2012) Catastrophic debris flows on 13 August 2010 in the Qingping area, southwestern China: the combined effects of a strong earthquake and subsequent rainstorms. Geomorphology 139–140:559–576

    Article  Google Scholar 

  • Wang NQ, Zhang ZY (2005) Research on loess landslide. Lanzhou University Press, Lanzhou

    Google Scholar 

  • Wang HB, Zhou B, Wu SR, Shi JS, Li B (2011) Characteristic analysis of large-scale loess landslides: a case study in Baoji City of Loess Plateau of Northwest China. Nat Hazards Earth Syst Sci 11(7):1829–1837

    Article  Google Scholar 

  • Wilson JP, Gallant JC (2000) Terrain analysis. Principles and applications. Wiley, New York

    Google Scholar 

  • Wu WJ, Wang NQ (2006) Research on landslide in Gansu Province. Lanzhou University Press, Lanzhou

    Google Scholar 

  • Xu Q, Fan XM, Huang RQ, Yin YP, Hou SS, Dong XJ, Tang MG (2010) A catastrophic rockslide-debris flow in Wulong, Chongqing, China in 2009: background, characterization, and causes. Landslides 7(1):75–87

    Article  Google Scholar 

  • Xu C, Xu XW, Dai FC, Wu ZD, He HL, Shi F, Wu XY, Xu SN (2013) Application of an incomplete landslide inventory, logistic regression model and its validation for landslide susceptibility mapping related to the May 12, 2008 Wenchuan earthquake of China. Nat Hazards 68(2):883–900

    Article  Google Scholar 

  • Yilmaz I (2009) Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: a case study from Kat landslides (Tokat-Turkey). Comput Geosci 35:1125–1138

    Article  Google Scholar 

  • Yune CY, Chae YK, Paik J, Kim G, Lee SW, Seo HS (2013) Debris flow in metropolitan area—2011 Seoul debris flow. J Mt Sci 10(2):199–206

    Article  Google Scholar 

  • Zhuang JQ, Peng JB (2014) A coupled slope cutting—a prolonged rainfall-induced loess landslide: a 17 October 2011 case study. Bull Eng Geol Environ 73(4):997–1011

    Article  Google Scholar 

  • Zhuang JQ, Cui P, Peng JB, Hu KH, Iqbal J (2013) Initiation process of debris flows on different slopes due to surface flow and trigger-specific strategies for mitigating post-earthquake in old Beichuan County, China. Environ Earth Sci 68(5):1391–1403

    Article  Google Scholar 

  • Zhuang JQ, Peng JB, Iqbal J, Liu TM, Liu N, Li YZ, Ma PH (2015) Identification of landslide spatial distribution and susceptibility assessment in relation to topography in the Xi’an Region, Shaanxi Province, China. Front Earth Sci 9(3):449–462

    Article  Google Scholar 

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Acknowledgments

The authors are very grateful to the anonymous reviewers and editors for their thoughtful review comments and suggestions which have significantly improved this paper. The authors wish to thank Prof. Chen Wenwu, Prof. Han Wenfeng for their contributions and involvement in the field investigations. We would also like to express our gratitude to the academic and technical staff of the Institute of Geohazards Mitigation and Research of Chang’an University, China. This study was financially supported by the National Basic Research Program of China (No. 2014CB744703), the National Natural Science Foundation of China (Grant Nos. 41572272 and 41130753) and the State Key Laboratory Program of SKLGP (Grant No. SKLGP2016K002).

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Correspondence to Jianbing Peng.

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This article is a part of a Topical Collection in Environmental Earth Sciences on “Advances of Research in Soil, Water, Environment, and Geologic Hazards along the Silk Road” guest edited by Drs. Peiyue Li Hui Qian and Wanfang Zhou.

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Zhuang, J., Peng, J., Zhu, X. et al. Spatial distribution and susceptibility zoning of geohazards along the Silk Road, Xian-Lanzhou. Environ Earth Sci 75, 711 (2016). https://doi.org/10.1007/s12665-016-5428-5

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