Volume 2, Issue 1 — Year 2025 — Article e100033

ISSN (Online): 3115-8129 Biannually

Utilizing the Geological Strength Index (GSI) for Rock Mass Strength Assessment in Slopes: A Case Study

Article Type: Case Study
Pages: e100033
DOI: https://doi.org/10.22034/CGEL.2.1.e100033
Crossmark
Open Access
Authors
Affiliations
  1. Department of Geology, Shiraz University, Shiraz 7194684334, Iran
  2. Department of Geology, University of Isfahan, Isfahan 8174673441, Iran
  3. Department of Mining Engineering, Urmia University, Urmia 5756151818, Iran
Corresponding author
Email: alizadeh.fb@gmail.com
Received: 25 March 2025 / Accepted: 10 May 2025 / Published: 22 May 2025
Abstract

Quantifying rock mass conditions is essential in rock mechanics, providing critical insights into quality, strength, and durability. Rock mass classification systems, developed primarily through empirical and experimental studies, serve as vital tools for assessing geotechnical properties. These systems are especially crucial in slope stability analysis, aiding in evaluating structural integrity and guiding the design of reliable stabilization strategies. Among these systems, the Geological Strength Index (GSI) is widely regarded as a robust method for classifying rock masses. Developed by Prof. Hoek and his colleagues, GSI evaluates the geological and geomechanical characteristics of rock masses based on structural and material properties. Its global adoption across engineering and geotechnical projects highlights its reliability and versatility. This study applies GSI to evaluate slope rock mass behavior and its engineering implications. Field investigations were conducted at 12 sites west of Shiraz city as part of a highway development project to analyze the stability of roadside slopes. A comprehensive survey included 24 of Uniaxial Compressive Strength (UCS), point load, Schmidt hammer tests, all aimed at determining the mechanical properties of the rock masses. The collected data were processed using the GSI system, enabling the classification of slope rock masses and the identification of key engineering geological characteristics. The findings offer valuable insights into the stability and geomechanical behavior of the slopes, forming a foundation for reliable design and effective stabilization strategies. This approach underscores the importance of GSI in slope stability assessments.

Keywords

Rock mass classification, Slope stability, Geological strength index, Geotechnical engineering, Rock mechanics

Data availability statement

The data supporting the findings of this study are available within article. No publicly archived dataset was generated.

Funding

This research received no external funding.

Highlights
  • GSI classifies rock mass conditions effectively
  • Field tests evaluate slope stability behavior
  • Results support design and stabilization strategies
References
  1. Aghanabati A. (2009). Geology of Iran. Geological Survey and Mineral Exploration of Iran press, Tehran, Iran.
  2. Aksoy C.O. (2008). Review of rock mass rating classification: Historical developments, applications, and restrictions. Journal of Mining Science, 44, 51-63. https://doi.org/10.1007/s10913-008-0005-2.
  3. Aydin A. (2004). Fuzzy set approaches to classification of rock masses. Engineering Geology, 74(3-4), 227-245. https://doi.org/10.1016/j.enggeo.2004.03.011.
  4. Azarafza M., Akgün H., Asghari-Kaljahi E. (2017). Assessment of rock slope stability by slope mass rating (SMR): a case study for the gas flare site in Assalouyeh, South of Iran. Geomechanics and Engineering, 13(4), 571-584. https://doi.org/10.12989/gae.2017.13.4.571 .
  5. Azarafza M., Koçkar M.K., Zhu H.H. (2022). Correlations of SMR-Qslope data in stability classification of discontinuous rock slope: a modified relationship considering the Iranian data. Geotechnical and Geological Engineering, 40(4), 1751-1764. https://doi.org/10.1007/s10706-021-01991-w.
  6. Bieniawski Z.T. (1973). Engineering classification of jointed rock masses. Civil Engineering= Siviele Ingenieurswese, 1973(12), 335-343.
  7. Bieniawski Z.T. (1989). Engineering rock mass classifications. Wiley, New York, USA.
  8. Cai M., Kaiser P. (2006). Visualization of rock mass classification systems. Geotechnical and Geological Engineering, 24, 1089-1102. https://doi.org/10.1007/s10706-005-7464-x.
  9. Choi S.Y., Park H.D. (2002). Comparison among different criteria of RMR and Q-system for rock mass classification for tunnelling in Korea. Tunnelling and Underground Space Technology, 17(4), 391-401. https://doi.org/10.1016/S0886-7798(02)00063-9.
  10. Dastanpour M. (1996). The Devonian system in Iran: a review. Geological Magazine, 133(2), 159-170.
  11. Day J.J., Diederichs M.S., Hutchinson D.J. (2019). Composite geological strength index approach with application to hydrothermal vein networks and other intrablock structures in complex rock masses. Geotechnical and Geological Engineering, 37(6), 5285-5314. https://doi.org/10.1007/s10706-019-00980-4.
  12. Deere D.U. (1989). Rock quality designation (RQD) after 20 years. United States Army Corps of Engineers, Contract Report GL-89-1. Vicksburg, MS: Waterways Experimental Station.
  13. Feng W., Dong S., Wang Q., Yi X., Liu Z., Bai H. (2018). Improving the Hoek–Brown criterion based on the disturbance factor and geological strength index quantification. International Journal of Rock Mechanics and Mining Sciences, 108, 96-104. https://doi.org/10.1016/j.ijrmms.2018.06.004.
  14. Fereidooni D., Khanlari G.R., Heidari M. (2015). Assessment of a modified rock mass classification system for rock slope stability analysis in the Q-system. Earth Sciences Research Journal, 19(2), 147-152. https://doi.org/10.15446/esrj.v19n2.49127.
  15. Ferrari F., Apuani T., Giani G.P. (2014). Rock Mass Rating spatial estimation by geostatistical analysis. International Journal of Rock Mechanics and Mining Sciences, 70, 162-176. https://doi.org/10.1016/j.ijrmms.2014.04.016.
  16. Habibi T., Ponedelnik A.A., Yashalova N.N., Ruban D.A. (2018). Urban geoheritage complexity: Evidence of a unique natural resource from Shiraz city in Iran. Resources Policy, 59, 85-94. https://doi.org/10.1016/j.resourpol.2018.06.002.
  17. Hamasur G.A. (2023). Geological strength index-slope: an adaptation of the geological strength index system for use in the rock slope stability assessment. Brazilian Journal of Geology, 53(1), e20220044. https://doi.org/10.1590/2317-4889202320220044.
  18. Hoek E., Brown E.T. (1980). Underground Excavations in Rock. London Institution of Mining and Metallurgy, London, England, UK.
  19. Hoek E., Brown E.T. (2019). The Hoek–Brown failure criterion and GSI–2018 edition. Journal of Rock Mechanics and Geotechnical Engineering, 11(3), 445-463. https://doi.org/10.1016/j.jrmge.2018.08.001.
  20. Hoek E., Carranza-Torres C., Corkum B. (2002). Hoek-Brown failure criterion-2002 edition. Proceedings of NARMS-Tac, 1(1), 267-273.
  21. Hoek E., Carter T.G., Diederichs M.S. (2013). Quantification of the geological strength index chart. In: Proceedings of the 47th U.S. Rock Mechanics/Geomechanics Symposium, pp. ARMA-2013-672.
  22. Hoek E., Marinos P., Benissi M. (1998). Applicability of the Geological Strength Index (GSI) classification for very weak and sheared rock masses. The case of the Athens Schist Formation. Bulletin of Engineering Geology and the Environment, 57, 151-160. https://doi.org/10.1007/s100640050031.
  23. Hong K., Han E., Kang K. (2017). Determination of geological strength index of jointed rock mass based on image processing. Journal of Rock Mechanics and Geotechnical Engineering, 9(4), 702-708. https://doi.org/10.1016/j.jrmge.2017.05.001.
  24. Hudson J.A., Harrison J.P. (1997). Engineering rock mechanics: An introduction to the principles. Pergamon, Oxford, England.
  25. Hussian S., Mohammad N., Ur Rehman Z., Khan N.M., Shahzada K., Ali S., Sherin S. (2020). Review of the geological strength index (GSI) as an empirical classification and rock mass property estimation tool: Origination, modifications, applications, and limitations. Advances in Civil Engineering, 2020(1), 6471837. https://doi.org/10.1155/2020/6471837.
  26. Keshavarzi M., Afghah M., Asadi A., Shirazi M.P.N. (2020). Albian biozonation and facies analysis of the west of Shiraz (Nour Abad area, Southwest Iran). Himalayan Geology, 41(1), 105-114.
  27. Khosravi R., Zarei M., Bigalke M. (2018). Characterizing major controls on spatial and seasonal variations in chemical composition of surface and pore brine of Maharlu Lake, Southern Iran. Aquatic Geochemistry, 24, 27-54. https://doi.org/10.1007/s10498-018-9329-y.
  28. Kumar S., Pandey H.K. (2021). Slope stability analysis based on rock mass rating, geological strength index and kinematic analysis in Vindhyan rock formation. Journal of the Geological Society of India, 97, 145-150. https://doi.org/10.1007/s12594-021-1645-y.
  29. Li C., Zhou J., Armaghani D.J., Cao W., Yagiz S. (2021). Stochastic assessment of hard rock pillar stability based on the geological strength index system. Geomechanics and Geophysics for Geo-Energy and Geo-Resources, 7, 1-24. https://doi.org/10.1007/s40948-021-00243-8.
  30. Maazallahi V., Majdi A. (2021). Directional rock mass rating (DRMR) for anisotropic rock mass characterization. Bulletin of Engineering Geology and the Environment, 80, 4471-4499. https://doi.org/10.1007/s10064-021-02143-3.
  31. Marinos V., Marinos P., Hoek E. (2005). The geological strength index: applications and limitations. Bulletin of Engineering Geology and the Environment, 64, 55-65. https://doi.org/10.1007/s10064-004-0270-5.
  32. Moon V., Russell G., Stewart M. (2001). The value of rock mass classification systems for weak rock masses: a case example from Huntly, New Zealand. Engineering Geology, 61(1), 53-67. https://doi.org/10.1016/S0013-7952(01)00024-2.
  33. Pantelidis L. (2010). An alternative rock mass classification system for rock slopes. Bulletin of Engineering Geology and the Environment, 69, 29-39. https://doi.org/10.1007/s10064-009-0241-y.
  34. Pozo R. (2022). Equivalent Geological Strength Index (GSI) approach with application to rock mass slope stability. Rudarsko-geološko-naftni zbornik, 37(4), 53-70. https://doi.org/10.17794/rgn.2022.4.5.
  35. Qazi A., Singh K. (2023). Rock Mass Classification Techniques and Parameters: a Review. Journal of Mining and Environment, 14(1), 155-178. https://doi.org/10.22044/jme.2023.12618.2292.
  36. Renani H.R., Cai M. (2022). Forty-year review of the Hoek–Brown failure criterion for jointed rock masses. Rock Mechanics and Rock Engineering, 55(1), 439-461. https://doi.org/10.1007/s00603-021-02661-2.
  37. Rocscience (2023). The Precursor to RSData: Hoek-Brown Failure Criterion. Online Learning Resources, available at: https://www.rocscience.com/learning/the-precursor-to-rsdata-hoek-brown-failure-criterion; Accessed on 12 March 2024.
  38. Salmi E.F., Sellers E.J. (2021). A review of the methods to incorporate the geological and geotechnical characteristics of rock masses in blastability assessments for selective blast design. Engineering Geology, 281, 105970. https://doi.org/10.1016/j.enggeo.2020.105970.
  39. Sari M. (2012). An improved method of fitting experimental data to the Hoek–Brown failure criterion. Engineering Geology, 127, 27-35. https://doi.org/10.1016/j.enggeo.2011.12.011.
  40. Singh B., Goel R.K. (2011). Engineering Rock Mass Classification: Tunneling, Foundations, and Landslides. Butterworth-Heinemann, Boston, USA.
  41. Somodi G., Bar N., Kovács L., Arrieta M., Török Á., Vásárhelyi B. (2021). Study of Rock Mass Rating (RMR) and Geological Strength index (GSI) correlations in granite, siltstone, sandstone and quartzite rock masses. Applied Sciences, 11(8), 3351. https://doi.org/10.3390/app11083351.
  42. Sonmez H., Gokceoglu C., Ulusay R. (2003). An application of fuzzy sets to the geological strength index (GSI) system used in rock engineering. Engineering Applications of Artificial Intelligence, 16(3), 251-269. https://doi.org/10.1016/S0952-1976(03)00002-2.
  43. Sonmez H., Ulusay R. (1999). Modifications to the geological strength index (GSI) and their applicability to stability of slopes. International Journal of Rock Mechanics and Mining Sciences, 36(6), 743-760. https://doi.org/10.1016/S0148-9062(99)00043-1.
  44. Stoneley R. (1981). The geology of the Kuh-e Dalneshin area of southern Iran, and its bearing on the evolution of southern Tethys. Journal of the Geological Society, 138(5), 509-526.
  45. Tsiambaos G., Saroglou H. (2010). Excavatability assessment of rock masses using the Geological Strength Index (GSI). Bulletin of Engineering Geology and the Environment, 69, 13-27. https://doi.org/10.1007/s10064-009-0235-9.
  46. Wang Y., Aladejare A.E. (2016). Evaluating variability and uncertainty of geological strength index at a specific site. Rock Mechanics and Rock Engineering, 49, 3559-3573. https://doi.org/10.1007/s00603-016-0957-5.
  47. Xia K., Chen C., Wang T., Zheng Y., Wang Y. (2022). Estimating the geological strength index and disturbance factor in the Hoek–Brown criterion using the acoustic wave velocity in the rock mass. Engineering Geology, 306, 106745. https://doi.org/10.1016/j.enggeo.2022.106745.
  48. Yang B., Mitelman A., Elmo D., Stead D. (2022). Why the future of rock mass classification systems requires revisiting their empirical past. Quarterly Journal of Engineering Geology and Hydrogeology, 55(1), qjegh2021-039. https://doi.org/10.1144/qjegh2021-039.
  49. Yodsomjai W., Keawsawasvong S., Likitlersuang S. (2021). Stability of unsupported conical slopes in Hoek-Brown rock masses. Transportation Infrastructure Geotechnology, 8(2), 279-295. https://doi.org/10.1007/s40515-020-00137-4.
  50. Zuo J., Shen J. (2020). The Hoek-Brown Failure Criterion–From Theory to Application. Springer, Singapore.
How to cite
Nazari, M., Alivand, S., & Alizadeh, F. (2025). Utilizing the Geological Strength Index (GSI) for Rock Mass Strength Assessment in Slopes: A Case Study. Civil and Geoengineering Letters, 2(1), e100033. https://doi.org/10.22034/CGEL.2.1.e100033
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