Probabilistic Risk Assessment of unsaturated Slope Failure Considering Spatial Variability of Hydraulic Parameters
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Probabilistic risk assessment of slope failure evaluates the slope safety in a quantitative manner, which considers the failure probability and failure consequence simultaneously. However, risk assessment of unsaturated slope accounting for spatially variable soil-water characteristic curve (SWCC) model parameter and saturated hydraulic conductivity has been rarely reported. A probabilistic risk assessment approach is proposed in current study for rationally quantifying the unsaturated slope failure risk with the aid of Monte Carlo (MC) simulation. The SEEP/W and SLOPE/W modules contained in Geostudio software are applied to carry out deterministic analysis, where factor of safety (FS) of the unsaturated slope is calculated by Morgenstern–Price method. The spatially variable hydraulic parameters are characterized by their respective random fields that are transferred from the random void ratio field in this study, rather than generating them separately. The proposed approach is subsequently employed to an unsaturated slope example for exploring the influences of spatially variable void ratio. Results show that the unsaturated slope failure risk is considerably affected by the spatially variable void ratio, and the single exponential autocorrelation function (ACF) popularized in geotechnical engineering tends to underestimate the failure risk in the unsaturated slope risk assessment.
Keywordsunsaturated slope risk assessment spatial variability hydraulic parameters random field
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This work was supported by the Key Laboratory of Ministry of Education for Geomechanics and Embankment Engineering (No. 2019018) and Chongqing Engineering Research Center of Disaster Prevention & Control for Banks and Structures in Three Gorges Reservoir Area (Nos. SXAPGC18ZD01 and SXAPGC18YB03). The financial support is gratefully acknowledged.
- Ali, A., Huang, J. S., Lyamin, A. V., Sloan, S. W., Griffiths, D. V., Cassidy, M. J., and Li, J. H. (2014). “Simplified quantitative risk assessment of rainfall-induced landslides modelled by infinite slopes.” Engineering Geology, Vol. 179, pp. 102–116, DOI: https://doi.org/10.1016/j.enggeo.2014.06.024.CrossRefGoogle Scholar
- Chen, F. Y., Wang, L., and Zhang, W. G. (2019). “Reliability assessment on stability of tunnelling perpendicularly beneath an existing tunnel considering spatial variabilities of rock mass properties.” Tunnelling and Underground Space Technology, Vol. 88, pp. 276–289, DOI: https://doi.org/10.1016/j.tust.2019.03.013.CrossRefGoogle Scholar
- GEO-SLOPE (2012). “Geostudio.” GEO-SLOPE International, Ltd., https://www.geoslope.com, [Accessed on December 5, 2014].
- Jha, S. K. and Ching, J.Y. (2012). “Simulating spatial averages of stationary random field using fourier series method.” Journal of Engineering Mechanics, Vol. 139, No. 5, pp. 594–605, DOI: https://doi.org/10.1061/(ASCE)EM.1943-7889.0000517.CrossRefGoogle Scholar
- Jiang, S. H., Li, D. Q., Zhang, L. M., and Zhou, C. B. (2015). “Slope reliability analysis considering spatially variable shear strength parameters using a non-intrusive stochastic finite element method.” Engineering Geology, Vol. 168, pp. 120–128, DOI: https://doi.org/10.1016/j.enggeo.2013.11.006.CrossRefGoogle Scholar
- Leong, E. C. and Rahardjo, H. (1997). “Permeability functions for unsaturated soils.” Journal of Geotechnical and Geoenvironmental Engineering, Vol. 123, No. 12, pp. 1118–1126, DOI: https://doi.org/10.1061/(ASCE)1090-0241(1997)123:12(1118).CrossRefGoogle Scholar
- Li, D. Q., Jiang, S. H., Cao, Z. J., Zhou, W., Zhou, C. B., and Zhang, L. M. (2015). “A multiple response-surface method for slope reliability analysis considering spatial variability of soil properties.” EngineeringGeology, Vol. 187, pp. 60–72, DOI: https://doi.org/10.1016/j.enggeo.2014.12.003.Google Scholar
- Li, D. Q., Xiao, T., Cao, Z. J., Zhou, C. B., and Zhang, L. M. (2016). “Enhancement of random finite element method in reliability analysis and risk assessment of soil slopes using subset simulation.” Landslides, Vol. 13, No. 2, pp. 293–303, DOI: https://doi.org/10.1007/s10346-015-0569-2.CrossRefGoogle Scholar
- Liu, L. L., Cheng, Y. M., Wang, X. M., Zhang, S. H, and Wu, Z. H. (2017). “System reliability analysis and risk assessment of a layered slope in spatially variable soils considering stratigraphic boundary uncertainty.” Computers and Geotechnics, Vol. 89, pp. 213-225, DOI: https://doi.org/10.1016/j.compgeo.2017.05.014.CrossRefGoogle Scholar
- Liu, L. L., Zhang, S. H., Cheng, Y. M., and Liang, L. (2019). “Advanced reliability analysis of slopes in spatially variable soils using multivariate adaptive regression splines.” Geoscience Frontiers, Vol. 10, No. 2, pp. 671–682, DOI: https://doi.org/10.1016/j.gsf.2018.03.013.CrossRefGoogle Scholar
- Lu, N. and Likos, W. J. (2004). Unsaturated soil mechanics, John Wiley & Sons, Hoboken, NJ, USA.Google Scholar
- Miao, F. S., Wu, Y. P., Xie, Y. H., Yu, F., and Peng, L. J. (2017). “Research on progressive failure process of Baishuihe landslide based on Monte Carlo model.” Stochastic Environmental Research and Risk Assessment, Vol. 31, No. 7, pp. 1683–1696, DOI: https://doi.org/10.1007/s00477-016-1224-8.CrossRefGoogle Scholar
- Phoon, K. K. and Ching, J. Y. (2015). Risk and reliability in geotechnical engineering, CRC Press, New York, NY, USA.Google Scholar
- Phoon, K. K., Santoso, A., and Quek, S. T. (2010). “Probabilistic analysis of soil-water characteristic curves.” Journal of Geotechnical and Geoenvironmental Engineering, Vol. 136, No. 3, pp. 445–455, DOI: https://doi.org/10.1061/(ASCE)GT.1943-5606.0000222.CrossRefGoogle Scholar
- van Genuchten, M. T. (1980). “A closed-form equation for predicting the hydraulic conductivity of unsaturated soils.” Soil Science Society of America Journal, Vol. 44, No. 5, pp. 892–898, DOI: https://doi.org/10.2136/sssaj1980.03615995004400050002x.CrossRefGoogle Scholar
- Wang, L., Cao, Z. J., Li, D. Q., Phoon, K. K., and Au, S. K. (2018). “Determination of site-specific soil-water characteristic curve from a limited number of test data – A Bayesian perspective.” Geoscience Frontiers, Vol. 9, No. 6, pp. 1665–1677, DOI: https://doi.org/10.1016/j.gsf.2017.10.014.CrossRefGoogle Scholar
- Wang, L., Wu, C. Z., and Zhang, W. G. (2019a). “Reliability analysis of unsaturated slope stability considering spatial variability in hydraulic parameters.” IOP Conference Series: Earth and Environmental Science, Vol. 304, No. 3, p. 032047, DOI: https://doi.org/10.1088/1755-1315/304/3/032047.Google Scholar
- Zhu, X., Xu, Q., Tang, M. G., Nie, W., Ma, S. Q., and Xu, Z. P. (2017). “Comparison of two optimized machine learning models for predicting displacement of rainfall-induced landslide: A case study in Sichuan.” Engineering Geology, Vol. 218, pp. 213–222, DOI: https://doi.org/10.1016/j.enggeo.2017.01.022.CrossRefGoogle Scholar