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A methodology to obtain the block size distribution of fragmental rockfall deposits

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Abstract

Rock masses detached as rockfalls usually disintegrate upon impact on the ground surface. The knowledge of the rockfall block size distribution (RBSD) generated in the rockfall deposit is useful for the analysis of the trajectories of the rock blocks, run-out distances, impact energies and for the quantitative assessment of the rockfall hazard. Obtaining the RBSD of a large rockfall deposit may become a challenge due to the high number of blocks to be measured. In this paper, we present a methodology developed for mid-size fragmental rockfalls (103 up to 105 m3) and its application to the Cadí massif, Eastern Pyrenees. The methodology consists of counting and measuring block fragments in selected sampling plots within homogeneous zones in the young debris cover generated by the rockfall along with all the large scattered rock blocks. The size distribution of blocks obtained in the sampling plots is extrapolated to the whole young debris cover and summed to the inventoried large scattered blocks to derive the RBSD of the whole rockfall event. The obtained distributions from the fragments can be well fitted by a power law distribution, indicating the scale invariant character of the fragmentation process (Hartmann (Icarus 2(2):201–203, 1969); Turcotte (J Geophys Res 91(NO B2):1921–1926, 1986). The total volume of the rockfall fragments has been checked against the volume at the rockfall source. The latter has been calculated comparing 3D digital surface models before and after the rockfall event.

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References

  • Agliardi F, Crosta GB (2003) High resolution three-dimensional numerical modelling of rockfalls. Int J Rock Mech Min Sci 40:455–471

    Article  Google Scholar 

  • Chau KT, Wong RHC, Wub JJ (2002) Coefficient of restitution and rotational motions of rockfall impacts. Int J Rock Mech Min Sci 39:69–77

    Article  Google Scholar 

  • Clauset A, Shalizi CR, Newman MEJ (2009) Power-law distributions in empirical data. Soc Ind Appl Math (SIAM) Rev 51(4):664–703

    Google Scholar 

  • Corominas J, Mavrouli O, Santana D, Moya J (2012) Simplified approach for obtaining the block volume distribution of fragmental rockfalls. In Eberhardt E, Froese C, Turner AK, Leroueil S (eds). Landslides and engineered slopes. Taylor and Francis. 2:1159–1164

  • Crosta G, Frattini P, Fusi F (2007) Fragmentation in the Val Pola rock avalanche, Italian Alps. J Geophys Res 112, F01006

    Google Scholar 

  • Dussauge C, Grasso J, Helmstetter A (2003) Statistical analysis of rock fall volume distributions: implications for rock fall dynamics. J Geophys Res B 108(B6):2286. doi:10.1029/2001JB000650

    Article  Google Scholar 

  • Dussauge C, Helmstetter A, Grasso J, Hantz S, Desvarreux P, Jeannin M, Giraud A (2002) Probabilistic approach to rockfall hazard assessment: potential of historical data analysis. Nat Hazards Earth Syst Sci 2:15–26

    Article  Google Scholar 

  • Dorren LKA (2003) A review of rockfall mechanics and modeling approaches. Prog Phys Geogr 27(1):69–87

    Article  Google Scholar 

  • Evans S, Hungr O (1993) The assessment of rockfall hazard at the base of talus slopes. Can Geotech J 30:620–636

    Article  Google Scholar 

  • Firpo G, Salvini R, Francioni M, Ranjith P (2011) Use of digital terrestrial photogrammetry in rocky slope stability analysis by distinct elements numerical methods. Int J Rock Mech Min Sci 48:1045–1054

    Article  Google Scholar 

  • Giacomini A, Buzzi O, Renard B, Giani GP (2009) Experimental studies on fragmentation of rock falls on impact with rock surfaces. Int J Rock Mech Min Sci 46:708–715

    Article  Google Scholar 

  • Hantz D, Rossetti J P, Servant F, D’Amato J (2014) Etude de la distribution des blocs dans un éboulement pour l’évaluation de l’aléa. Proceedings of Rock Slope Stability 2014, Marrakesh

  • Hartmann WK (1969) Terrestrial, lunar and interplanetary rock fragmentation. Icarus 2(2):201–213

    Article  Google Scholar 

  • Hecht-Nielsen R (1987) Kolmogorov’s mapping neural net-work existence theorem. Proceedings of the first IEEE international conference on neural networks. San Diego, pp 11–14

  • Hungr O, Leroueil S, Picarelli L (2014) The Varnes classification of landslides types, an update. Landslides 11:167–194

    Article  Google Scholar 

  • Hungr O, Evans SG, Hazzard J (1999) Magnitude and frequency of rock falls and rock slides along the main transportation corridors of southwestern British Columbia. Can Geotech J 36(2):224–238. doi:10.1139/t98-106

    Article  Google Scholar 

  • Jaboyedoff M, Dudt JP, Labiouse V (2005) An attempt to refine rockfall hazard zoning based on the kinetic energy, frequency and fragmentation degree. Nat Hazards Earth Syst Sci 5:621–632

    Article  Google Scholar 

  • Okura Y, Kitahara H, Sammori T, Kawanami A (2000) The effects of rockfall volume on runout distance. Eng Geol 58(2):109–124

    Article  Google Scholar 

  • Perfect E (1997) Fractal models for the fragmentation of rocks and soils: a review. Eng Geol 48:185–198

    Article  Google Scholar 

  • Pickering G, Bull JM, Sanderson DJ (1995) Sampling power-law distributions. Tectonophysics 248:1–20

    Article  Google Scholar 

  • Salciarini D, Tamagnini C, Conversini P (2009) Numerical approaches for rockfall analysis: a comparison, Proceedings of the 18th World IMACS/MODSIM Congress, Cairns

  • Schalkoff R (1997) Artificial neural network. McGraw-Hill, New York

    Google Scholar 

  • Sturzenegger M, Stead D (2009) Close-range terrestrial digital photogrammetry and terrestrial scanning for discontinuity characterization on rock cuts. Eng Geol 106:163–182

    Article  Google Scholar 

  • Turcotte D (1986) Fractals and fragmentation. J Geophys Res 91(NO B2):1921–1926

    Article  Google Scholar 

  • Viero A, Furlanis S, Squarzoni C, Teza G, Galgaro A, Gianola P (2012) Dynamics and mass balance of the Cima Una rockfall (Eastern Alps, Italy). Landslides 10:393–408

    Article  Google Scholar 

  • Wang Y, Tonon F (2010) Discrete element modelling of rock fragmentation upon impact in rock fall analysis. Rock Mech Rock Eng 44:23–35

    Article  Google Scholar 

  • Wu, C (2011) VisualSFM: a visual structure from motion system. URL: http://homes.cs.washington.edu/~ccwu/vsfm,9

  • Zhang ZX, Kou SQ, Jiang LG, Lindqvist PA (2000) Effects of loading rate on rock fracture: fracture characteristics and energy partitioning. Int J Rock Mech Min Sci 37:745–762

    Article  Google Scholar 

Download references

Acknowledgments

The authors acknowledge the support of the Spanish Economy and Competitiveness Ministry to the Rockrisk research project (BIA2013-42582-P) and the support of the Ministry of Education to the first author (grant code FPU13/04252)

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Correspondence to Roger Ruiz-Carulla.

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Ruiz-Carulla, R., Corominas, J. & Mavrouli, O. A methodology to obtain the block size distribution of fragmental rockfall deposits. Landslides 12, 815–825 (2015). https://doi.org/10.1007/s10346-015-0600-7

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  • DOI: https://doi.org/10.1007/s10346-015-0600-7

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