Meethotamulla Landfill Failure Analysis: A Probabilistic Approach

Part of the Developments in Geotechnical Engineering book series (DGE)


This paper assesses the possible conditions that might have resulted in the recent catastrophic failure of the Meethotamulla landfill slope at Colombo. This paper presents a probabilistic approach to find the different combinations of parameters that might have caused the collapse of landfill slope. A performance function is formulated, and the reliability of the slope is assessed using first-order reliability method (FORM). The factor of safety associated with various slip surfaces are computed with different combinations of mean and COV. The results obtained from the reliability analysis based on FORM agree closely with the reported post-failure investigations. The analysis elucidated the possible causes of landfill slope failure. The outcome of the analysis can be utilized for finding a remediation with improved knowledge about the shear strength parameters of the solid waste. The probabilistic analysis conducted in the present work reveals that the mean value of shear strength parameters of MSW and its associated variability responsible for the collapse of Meethotamulla garbage dump are friction angle, \( \phi = 20^\circ \) and stability number, \( {c \mathord{\left/ {\vphantom {c {\gamma H}}} \right. \kern-0pt} {\gamma H}} = 0.05 \). The reliability analysis proved that the most likely reason for the dump failure is the reduction in shear strength parameters of the MSW. The excessive rainfall might have triggered the reduction in shear strength parameters. The analysis of Meethotamulla garbage dump disaster demonstrated that it is very essential to conduct reliability analysis as realistically as possible to find the conditions that have triggered the collapse.


Meethotamulla landfill Probabilistic approach MSW slopes Reliability analysis Variability 


  1. Basha, B. M., & Raviteja, K. V. N. S. (2017). Resistance factor calculations for load resistance factor design (LRFD) of MSW landfill slopes. In Geoenvironmental practices and sustainability linkages and directions (pp. 47–56). Berlin: Springer.Google Scholar
  2. Geotechnical Assessment on the Failure at Meethotamulla Waste Fill. (2017). A report by National Building Research Organization (NBRO). Colombo: Ministry of disaster management.Google Scholar
  3. Gilbert, R. B., Wright, S. G., & Liedtke, E. (1998). Uncertainty in back-analysis of slopes: Kettleman hills case history. Journal of Geotechnical and Geoenvironmental Engineering, 124(12), 1167–1176 (ASCE).Google Scholar
  4. Jahanfar, A., Gharabaghi, B., McBean, E. A., & Dubey, B. K. (2017). Municipal solid waste slope stability modelling: A probabilistic approach. Journal of Geotechnical and Geoenvironmental Engineering, 143(8), 1–10 (ASCE).Google Scholar
  5. Tang, W. H., Stark, T. D., & Angulo, M. (1999). Reliability in back analysis of slope failures. Soils and Foundations, JGS, 39(5), 73–80.CrossRefGoogle Scholar
  6. US Army Corps of Engineers. (1997). Engineering and design: Introduction to probability and reliability methods for use in geotechnical engineering, Engineering Circular 1110-2-547. Washington, DC: US Department of the Army.Google Scholar
  7. Zhang, J., Tang, W. H., & Zhang, L. M. (2010). Efficient probabilistic back-analysis of slope stability model parameters. Journal of Geotechnical and Geoenvironmental Engineering, 136(1), 99–109 (ASCE).Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Civil EngineeringIIT HyderabadKandi, SangareddyIndia

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