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Preliminary Rock-Slope-Susceptibility Assessment Using GIS and the SMR Classification

Author

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  • C. Irigaray
  • T. Fernández
  • J. Chacón

Abstract

The geomechanical classification SMR (Slope Mass Rating) enables the preliminary assessment of the susceptibility of rock slopes to failure. The SMR index is obtained from Bieniawski's basic RMR (Rock Mass Rating) through an ``adjustment factor'' and an ``excavation factor''. Since its appearance in 1985, this classification has been used for appraisals and preliminary studies in many countries. The method is applied automatically by a Geographic Information System (Arc-Info GIS). The present study describes the methodology used and the results obtained after mapping the failure susceptibility in rock slopes by computing the SMR index using a GIS. Data have been gathered from the Digital Elevation Model (DEM), and by the statistical analysis of the parameters measured on the slopes. The methodology has been applied to the slopes along the N-340 road between Arraijana beach and Castell de Ferro (Granada, Spain). A total of 40 slopes have been studied along a linear distance of 4 km. As a result, in addition to all the factors that determine the SMR index, the most unfavourable SMR maps as well as the corresponding mean value have been established. From a cross analysis between these two maps and the instability phenomena observeddirectly in the field, we conclude that the average value of the SMR indexcalculated for the different discontinuity sets is the most representative valueof rock-slope-failure susceptibility. The results show the usefulness of theSMR's parameters to be used in GIS applications to rock-landslide hazardalong roads. Copyright Kluwer Academic Publishers 2003

Suggested Citation

  • C. Irigaray & T. Fernández & J. Chacón, 2003. "Preliminary Rock-Slope-Susceptibility Assessment Using GIS and the SMR Classification," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 30(3), pages 309-324, November.
    • Handle: RePEc:spr:nathaz:v:30:y:2003:i:3:p:309-324
    DOI: 10.1023/B:NHAZ.0000007178.44617.c6
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    Citations

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    Cited by:

    1. Chong Xu & Xiwei Xu & Fuchu Dai & Zhide Wu & Honglin He & Feng Shi & Xiyan Wu & Suning Xu, 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," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 68(2), pages 883-900, September.
    2. Bankim Mahanta & H. O. Singh & P. K. Singh & Ashutosh Kainthola & T. N. Singh, 2016. "Stability analysis of potential failure zones along NH-305, India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(3), pages 1341-1357, September.
    3. C. Irigaray & T. Fernández & R. El Hamdouni & J. Chacón, 2007. "Evaluation and validation of landslide-susceptibility maps obtained by a GIS matrix method: examples from the Betic Cordillera (southern Spain)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 41(1), pages 61-79, April.

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