Journal of the Korean GEO-environmental Society (한국지반환경공학회 논문집)

Korean Geo-Environmental Society (한국지반환경공학회)
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Shallow Landslide Assessment Considering the Influence of Vegetation Cover

  • Viet, Tran The (Department of Construction and Disaster Prevention Engineering, Kyungpook National University, Division of Geotechnical Engineering., Thuyloi University) ;
  • Lee, Giha (Department of Construction and Disaster Prevention Engineering, Kyungpook National University) ;
  • Kim, Minseok (International Water Resources Research Institute, Chungnam National University)
  • Received : 2016.01.04
  • Accepted : 2016.03.14
  • Published : 2016.04.01
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Abstract

Many researchers have evaluated the influence of vegetation cover on slope stability. However, due to the extensive variety of site conditions and vegetation types, different studies have often provided inconsistent results, especially when evaluating in different regions. Therefore, additional studies need to be conducted to identify the positive impacts of vegetation cover for slope stabilization. This study used the Transient Rainfall Infiltration and Grid-based Regional Slope-stability Model (TRIGRS) to predict the occurrence of landslides in a watershed in Jinbu-Myeon, Pyeongchang-gun, Korea. The influence of vegetation cover was assessed by spatially and temporally comparing the predicted landslides corresponding to multiple trials of cohesion values (which include the role of root cohesion) and real observed landslide scars to back-calculate the contribution of vegetation cover to slope stabilization. The lower bound of cohesion was defined based on the fact that there are no unstable cells in the raster stability map at initial conditions, and the modified success rate was used to evaluate the model performance. In the next step, the most reliable value representing the contribution of vegetation cover in the study area was applied for landslide assessment. The analyzed results showed that the role of vegetation cover could be replaced by increasing the soil cohesion by 3.8 kPa. Without considering the influence of vegetation cover, a large area of the studied watershed is unconditionally unstable in the initial condition. However, when tree root cohesion is taken into account, the model produces more realistic results with about 76.7% of observed unstable cells and 78.6% of observed stable cells being well predicted.

Keywords

References

  1. Abe, K. and Ziemer, R. R. (1991), Effect of tree roots on shallow-seated landslides. Proceeding of the IUFRO technical session on geomorphic hazards in managed forests; Montreal, Canada, Department of Agriculture, pp. 11-20.
  2. Aberrnethy, B. and BRutherfurd, I. D. (2000), The effect of riparian tree roots on the mass-stability of riverbanks, Earth Surface Processes and Landforms, Vol. 25, pp. 921-937. https://doi.org/10.1002/1096-9837(200008)25:9<921::AID-ESP93>3.0.CO;2-7
  3. Ali, F. H. and Osman, N. (2008), Shear strength of a soil containing vegetation roots, Japanese Geotechnical Society, Vol. 48, No. 4, pp. 587-596.
  4. Anderson, S. and Riemer, M. (1995), Collapse of saturated soil due to reduction in confinement, Journal of Geotechnical Engineering, Vol. 121, No. 2, pp. 216-220. https://doi.org/10.1061/(ASCE)0733-9410(1995)121:2(216)
  5. Baum, R. L., Godt, J. W. and Savage, W. Z. (2010), Estimating the timing and location of shallow rainfall-induced landslides using a model for transient, unsaturated infiltration, Journal of Geophysical Research, Vol. 115, No. 3, pp. 1-26.
  6. Baum, R. L., Savage, W. Z. and Godt, J. W. (2009), TRIGRS-A fortran program for transient rainfall infiltration and gridbased regional slope-stability analysis, Version 2.0. Colorado, U.S. Geological Survey, pp. 1-26.
  7. Bischetti, G. B. and Chiaradia, E. A. (2010), Calibration of distributed shallow landslide models in forested landscapes, Journal of Agricultural Engineering, Vol. 41, No. 3, pp. 23-35. https://doi.org/10.4081/jae.2010.3.23
  8. Bordoni, M., Meisina, C., Valentino, R., Bittelli, M. and Chersich, S. (2014), From slope-to regional-scale shallow landslides susceptibility assessment using TRIGRS, Nat. Hazards Earth Syst. Sci, Vol. 2, No. 12, pp. 7409-7464. https://doi.org/10.5194/nhessd-2-7409-2014
  9. Buchanan, P. and Savigny K. W. (1990), Factors controlling debris avalanche initiation, Can. Geotech. Journal, Vol. 27, No. 5, pp. 659-675. https://doi.org/10.1139/t90-079
  10. Buroughs, E. R. and Thomas, B. R. (1977), Declining root strength in douglas-fit after felling as a factor in slope stability, USDA Forest Service Research Paper, Vol. 190, pp. 1-27.
  11. Casadei, M., Dietrich, W. E. and Miller, N. (2003), Controls on shallow landslide size, in D. Rickenmann and C.L. Chen (eds), Debris-Flow Hazards Mitigation: Mechanics, Prediction, and Assessment, Davos, Switzerland, (Rotterdam: Millpress), pp. 91-101.
  12. Docker, B. B. and Hubble, T. C. T. (2008), Quantifying rootreinforcement of river bank soils by four Australian tree species, Geomorphology, Vol. 100, No. 3-4, pp. 401-418. https://doi.org/10.1016/j.geomorph.2008.01.009
  13. Frank, G., Frei, M. and Boll, A. (2009), Effects of vegetation on the angle of internal friction of a moraine, For. Snow Landsc. Res, Vol. 82, No. 1, pp. 61-77.
  14. Gray, D. H. (1973), Effects of forest clear-cutting on the stability of natural slopes: results of field studies, National Science Foundation. University of Michigan, Washington, pp. 45-66.
  15. Gray, D. H. and Megahan, W. F. (1981), Forest vegetation removal and slope stability in the idaho batholith, For. Serv., U.S. Dep. of Agric, pp. 1-23.
  16. Gritzner, M. L., Marcus, W. A., Aspinall, R. and Custer, S. G. (2001), Assessing landslide potential using GIS, soil wetness modeling and topographic attributes, Payette River, Idaho, Geomorphology, Vol. 37, No. 1-2, pp. 149-165. https://doi.org/10.1016/S0169-555X(00)00068-4
  17. Hanks, R. J. and Bowers S. A. (1963), Influence of variations in the diffusivity water content relation on infiltration, Soil Science Society of America Journal, Vol. 27, No. 3, pp. 263-265. https://doi.org/10.2136/sssaj1963.03615995002700030015x
  18. Ho, J. Y., Lee, K. T., Chang, T. C., Wang, Z. Y. and Liao, Y. H. (2012), Influences of spatial distribution of soil thickness on shallow landslide prediction, Engineering Geology, Vol. 124, No. 4, pp. 38-46. https://doi.org/10.1016/j.enggeo.2011.09.013
  19. Huang, J. C. and Kao, S. J. (2006), Optimal estimator for assessing landslide model performance, Hydrol. Earth Syst. Sci, Vol. 10, No. 6, pp. 957-965. https://doi.org/10.5194/hess-10-957-2006
  20. Hussain, M., Stark, T. D. and Akhtar, K. (2010), Back-analysis procedure for landslides, International Conference on Geotechnical Engineering. S. Kibria, H. M. Qureshi and A. M. Rana. Lahore, Pakistan, Pakistan Geot. Eng. Society, pp. 159-166.
  21. Iverson, R. M. (2000), Landslide triggering by rain infiltration, Water Resources Research, Vol. 36, No. 7, pp. 1897-1910. https://doi.org/10.1029/2000WR900090
  22. Jakob, M. (2000), The impacts of logging on landslide activity at clayoquot sound, british columbia, Cantena, Vol. 38, No. 4, pp. 279-300.
  23. Kim, D., Lee, S. H. and Im, S. (2011), Analysis of the effect of tree roots on soil reinforcement considering its spatial distribution, J. Korean Env. Res. Tech, Vol. 14, No. 4, pp. 41-54.
  24. Kim, D., Im, S., Lee, C. and Woo, C. (2013), Modeling the contribution of trees to shallow landslide development in a steep, forested watershed, Ecological Engineering, Vol. 61(C), pp. 658-668. https://doi.org/10.1016/j.ecoleng.2013.05.003
  25. Kim, D., Im, S. and Lee, S. H. (2010a), Predicting the rainfalltriggered landslides in a forested mountain region using TRIGRS model, Journal of Mountain Science, Vol. 7, No. 1, pp. 83-91. https://doi.org/10.1007/s11629-010-1072-9
  26. Kim, D., Lee, S. H., Combalicer, E. A., Hong, Y. and IM, S. (2010b), Estimating soil reinforcement by tree roots using the perpendicular root reinforcement model, International Journal of Erosion Control Engineering, Vol. 3, No. 1, pp. 80-84. https://doi.org/10.13101/ijece.3.80
  27. Kim, M. S., Onda, Y. and Kim, J. K. (2015a), Improvement of shallow landslide prediction accuracy using soil parameterisation for a granite area in South Korea, Nat. Hazards Earth Syst. Sci, Vol.3, No. 1, pp. 227-267. https://doi.org/10.5194/nhessd-3-227-2015
  28. Kim, M. S., Onda, Y., Kim, J. K. and Kim, S. W. (2015b), Effect of topography and soil parameterisation representing soil thicknesses on shallow landslide modelling, Quaternary International, Vol. 384, pp. 91-106. https://doi.org/10.1016/j.quaint.2015.03.057
  29. Lee, K. T. and Ho, J. Y. (2009), Prediction of landslide occurrence based on slope-instability analysis and hydrological model simulation, Journal of Hydrology, Vol. 375, No. 3, pp. 489-497. https://doi.org/10.1016/j.jhydrol.2009.06.053
  30. Lee, M. J., Choi, J., Park, I. and Lee, S. (2012a), Ensemblebased landslide susceptibility maps in Jinbu area, Korea, Environb Earth Sci, Vol. 67, No. 1, pp. 23-37. https://doi.org/10.1007/s12665-011-1477-y
  31. Lee, S., Hwang, J. and Park, I. (2012b), Application of datadriven evidential belief functions to landslide susceptibility mapping in Jinbu, Korea, Catena, Vol. 100, pp. 15-30.
  32. Lee, S., Song, K. Y., Oh, H. J. and Choi, J. (2012c), Detection of landslides using web-based aerial photographs and landslide susceptibility mapping using geospatial analysis, International Journal of Remote Sensing, Vol. 33, No. 16, pp. 4937-4966. https://doi.org/10.1080/01431161.2011.649862
  33. Lee, S. C. and Hencher, S. R. (2014), Recent extreme rainfallinduced landslides and government countermeasures in korea. Landslide Science for a Safer Geoenvironment. K. Sassa, P. Canuti and Y. Yin (eds), New York, Springer, Vol. 1, pp. 357-361.
  34. Liao, Z., Hong, Y., Kirschbaum, D., Adler, R. F., Gourley, J. J. and Wooten, R. (2011), Evaluation of TRIGRS (transient rainfall infiltration and grid-based regional slope-stability analysis)'s predictive skill for hurricane-triggered landslides: a case study in macon county, north carolina, Nat. Hazards, Vol. 58, No. 1, pp. 325-339. https://doi.org/10.1007/s11069-010-9670-y
  35. Liu, C. N. and Wu, C. C. (2008), Mapping susceptibility of rainfall-triggered shallow landslides using a probabilistic approach, Environ Geol, Vol. 55, No. 4, pp. 907-915. https://doi.org/10.1007/s00254-007-1042-x
  36. Montgomery, D. R. and Dietrich, W. E. (1994), A physically based model for the topographic control on shallow landsliding, Water Resour. Res., Vol. 30, No. 4, pp. 1153-1171. https://doi.org/10.1029/93WR02979
  37. O'Loughlin, C. (1974), The effect of timber removal on the stability of forest soils, Journal of hydrology (N.Z.), Vol. 13, No. 2, pp. 121-134.
  38. O'Loughlin, C. and Ziemer, R. R. (1982), The importance of root strength and deterioration rates upon edaphic stability in steepland forests. Proceedings of I.U.F.R.O. Workshop P.1.07-00 Ecology of Subalpine Ecosystems as a Key to Management, Oregon State University, Miscellaneous Publ, pp. 70-78.
  39. Park, D. W., Nikhil, N. V. and Lee, S. R. (2013), Landslide and debris flow susceptibility zonation using TRIGRS for the 2011 Seoul landslide event, Nat. Hazards Earth Syst. Sci, Vol. 1, No. 3, pp. 2547-2587. https://doi.org/10.5194/nhessd-1-2547-2013
  40. Penna, D., Borga, M., Aronica, G. T., Brigandi, G. and Tarolli, P. (2014), The influence of grid resolution on the prediction of natural and road-related shallow landslides, Hydrol. Earth Syst. Sci, Vol. 18, No. 6, pp. 2127-2139. https://doi.org/10.5194/hess-18-2127-2014
  41. Salciarini, D., Godt, J. W., Savage, W. Z., Conversini, P., Baum, R. L. and Michael, J. A. (2006), Modeling regional initiation of rainfall-induced shallow landslides in the eastern Umbria Region of central Italy, Landslides, Vol. 3, No. 3, pp. 181-194. https://doi.org/10.1007/s10346-006-0037-0
  42. Schmidt, K. M., Roering, J. J., Stock, J. D., Dietrich, W. E., Montgomery, D. R. and Schaub, T. (2001), The variability of root cohesion as an influence on shallow landslide susceptiblity in the oregon coast range, Can. Geotech, Vol. 38, No. 5, pp. 995-1024. https://doi.org/10.1139/t01-031
  43. Schwarz, M., Giadrossich, F. and Cohen, D. (2013), Modeling root reinforcement using root-failure weibull survival function, Hydrol. Earth Syst. Sci, Vol. 17, No. 11, pp. 4367-4377. https://doi.org/10.5194/hess-17-4367-2013
  44. Segoni, S, Rossi, G, Catani, F. (2012), Improving basin scale shallow landslide modelling using reliable soil thickness maps, Nat. Hazards, Vol. 61, No. 1, pp. 85-101. https://doi.org/10.1007/s11069-011-9770-3
  45. Sidle, R. C. and Ochiai, H. (2006), Landslides processes, prediction, and land use. Washington, DC, American Geophysical Union, pp. 1-312.
  46. Skaugset, A. E. (1997), Modelling root reinforcement in shallow forest soils. Oregon State University, Oregon State University libraries. PhD Thesis, pp. 1-300.
  47. Steinacher, R., Medicus, G., Fellin, W. and Zangerl, C. (2009), The influence of deforestation on slope (in-) stability, Austrian journal of earth sciences, Vol. 102, No. 2, pp. 90-99.
  48. Swanston, D. N. (1970), Mechanics of debris avalanching in shallow till soils of southeast alaska, USDA Forest Service Research Paper PNW, Vol. 103, pp. 121-134.
  49. Swanston, D. N. and Marion D. A. (1991), Landslide response to timber harvest in southeast alaska, Proceeding of the Fifth Interagency Sedimentation Conference, Las Vegas, Nevada, Federal Energy Regulatory Commission, pp. 10-49.
  50. Tarolli, P. and Tarboton, D. G. (2006), A new method for determining of most likely landslide initiation points and the evaluation of digital terrain model scale in terrain stability mapping, Hydrol. Earth Syst. Sci, Vol. 10, No. 5, pp. 663-677. https://doi.org/10.5194/hess-10-663-2006
  51. Taylor, D. W. (1948), Fundamentals of soil mechanics. New York, John Wiley & Sons, Inc, pp. 1-712.
  52. Terwilliger, V. J. and Waldron, L. J. (1990), Assessing the contribution of roots to the strength of undisturbed, slip prone soils, Catena, Vol. 17, pp. 151-162. https://doi.org/10.1016/0341-8162(90)90005-X
  53. Uchida, T., Tamur, K. and Akiyama, K. (2011), The role of grid cell size, flow routing algolithm and spatial variability of soil depth on shallow landslide prediction, Italian Journal of Engineering Geology and Environment - Book, Vol. 11, pp. 149-157.
  54. Van Asch, T. W. J. (1984), Landslides: The deduction of strength parameters of materials from equilibrium analysis, Catena, Vol. 11, pp. 39-49. https://doi.org/10.1016/S0341-8162(84)80004-1
  55. Wu, T. H., McKinnell, W. P. and Swanston, D. N. (1979), Strength of tree roots on prince of wales island, alaska, Can. Geotech, Vol. 16, No. 1, pp. 19-33. https://doi.org/10.1139/t79-003
  56. Wu, W. and Sidle, R. C. (1995), A distributed slope stability model for steep forested basins, Water Resour. Res, Vol. 31, No. 8, pp. 2097-2110. https://doi.org/10.1029/95WR01136
  57. Yuan, C. C., Chien, C. T., Chieh, Y. F. and Chi, L. S. (2005), Analysis of time-varying rainfall infiltration induced landslide, Environ Geol, Vol. 48, No. 4, pp. 466-479. https://doi.org/10.1007/s00254-005-1289-z
  58. Zhang, K., Cao, P. and Bao, R. (2012), Rigorous back analysis of shear strength parameters of landslide slip, Transactions of Nonferrous Metals Society of China, Vol. 23, No. 5, pp. 1459-1464.
  59. Ziemer, R. R. (1981), The role of vegetation in the stability of forested slopes. Proceedings of the International Union of Forestry Research Organizations, Kyoto, Japan, XVII World Congress, pp. 297-308.

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