The stability study of the ongoing and recurring Amalpata landslide in Baglung in Nepal’s Gandaki Province is presented in this research. The impacted slope is around 200 meters high, with two terraces that have different slope inclinations. The lower bench, located above the basement, consistently fails and sets others up for failure. The fluctuating water level of the slope, which travels down the slope masses, exacerbates the slide problem. The majority of these rocks are Amalpata landslide area experiences several structural disruptions. The area’s stability must be evaluated in order to prevent and control more harm from occurring to the nearby agricultural land and people living along the slope. The slopes’ failures increase the damages of house existing in nearby area and the erosion of the slope. Two modeling techniques the finite element approach and the limit equilibrium method were used to simulate the slope. The findings show that, in every case, the terrace above the basement is where the majority of the stress is concentrated, with a safety factor of near unity. Using probabilistic slope stability analysis, the failure probability was predicted to be between 98.90% and 100%.
References
[1]
Javankhoshdel, S., Luo, N. and Bathurst, R.J. (2017) Probabilistic Analysis of Simple Slopes with Cohesive Soil Strength Using RLEM and RFEM. Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, 11, 231-246. https://doi.org/10.1080/17499518.2016.1235712
[2]
Stroulia, E., El-Ramly, M. and Sorenson, P. (2002) From Legacy to Web through Interaction Modeling. Proceedings of International Conference on Software Maintenance, 3-6 October 2002, 320-329. https://doi.org/10.1109/ICSM.2002.1167788
Christian, J.T., Ladd, C.C. and Baecher, G.B. (1994) Reliability Applied to Slope Stability Analysis. Journal of Geotechnical Engineering, 120, 2180-2207. https://doi.org/10.1061/(ASCE)0733-9410(1994)120:12(2180)
[5]
Khajehzadeh, M., Raihan Taha, M., El-Shafie, A. and Eslami, M. (2012) Locating the General Failure Surface of Earth Slope Using Particle Swarm Optimisation. Civil Engineering and Environmental Systems, 29, 41-57.
[6]
Leynaud, D., Mulder, T., Hanquiez, V., Gonthier, E. and Régert, A. (2017) Sediment Failure Types, Preconditions and Triggering Factors in the Gulf of Cadiz. Landslides, 14, 233-248. https://doi.org/10.1007/s10346-015-0674-2
[7]
Ji, S., Yu, D., Shen, C., Li, W. and Xu, Q. (2020) Landslide Detection from an Open Satellite Imagery and Digital Elevation Model Dataset Using Attention Boosted Convolutional Neural Networks. Landslides, 17, 1337-1352. https://doi.org/10.1007/s10346-020-01353-2
[8]
Javankhoshdel, S., Cami, B., Ma, T., Yacoub, T. and Chenari, R.J. (2021) Probabilistic Slope Stability Analysis of a Case Study Using Random Limit Equilibrium Method and Surface Altering Optimization. In The Evolution of Geotech-25 Years of Innovation, CRC Press, Boca Raton, 413-418. https://doi.org/10.1201/9781003188339-53
[9]
Li, L., Lan, H., Guo, C., Zhang, Y., Li, Q. and Wu, Y. (2017) A Modified Frequency Ratio Method for Landslide Susceptibility Assessment. Landslides, 14, 727-741. https://doi.org/10.1007/s10346-016-0771-x
[10]
Javankhoshdel, S. and Bathurst, R.J. (2014) Simplified Probabilistic Slope Stability Design Charts for Cohesive and Cohesive-Frictional (c-ϕ) Soils. Canadian Geotechnical Journal, 51, 1033-1045. https://doi.org/10.1139/cgj-2013-0385
[11]
Javankhoshdel, S., Rezvani, M., Fatehi, M. and Jamshidi Chenari, R. (2022) RLEM versus RFEM in Stochastic Slope Stability Analyses in Geomechanics. Proceedings ofGeo-Congress 2022, Charlotte, 20-23 March 2022, 241-250. https://doi.org/10.1061/9780784484036.025
[12]
Jing, L. and Hudson, J.A. (2002) Numerical Methods in Rock Mechanics. International Journal of Rock Mechanics and Mining Sciences, 39, 409-427. https://doi.org/10.1016/S1365-1609(02)00065-5
[13]
Hammah, R.E., Yacoub, T.E. and Curran, J.H. (2007) Serviceability-Based Slope Factor of Safety Using the Shear Strength Reduction (SSR) Method. International Congress on Rock Mechanics, Lisbon, 9-13 July 2007, 1317-1320.
[14]
Kanungo, D.P., Arora, M.K., Gupta, R.P. and Sarkar, S. (2008) Landslide Risk Assessment Using Concepts of Danger Pixels and Fuzzy Set Theory in Darjeeling Himalayas. Landslides, 5, 407-416. https://doi.org/10.1007/s10346-008-0134-3
[15]
Pradhan, B. and Lee, S. (2009) Landslide Risk Analysis Using Artificial Neural Network Model Focusing on Different Training Sites. International Journal of Physical Sciences, 3, 1-15.
[16]
Sarkar, K., Singh, T.N. and Verma, A.K. (2012) A Numerical Simulation of Landslide-Prone Slope in Himalayan Region—A Case Study. Arabian Journal of Geosciences, 5, 73-81. https://doi.org/10.1007/s12517-010-0148-8
[17]
Bali, R., Bhattacharya, A.R. and Singh, T.N. (2009) Active Tectonics in the Outer Himalaya: Dating a Landslide Event in the Kumaun Sector. Earth Science India, 2.
[18]
Vanmarcke, E.H. (1977) Reliability of Earth Slopes. Journal of the Geotechnical Engineering Division, 103, 1247-1265. https://doi.org/10.1061/AJGEB6.0000518
[19]
Yin, J., Lu, W., Xin, X. and Zhang, L. (2011) Application of Monte Carlo Sampling and Latin Hypercube Sampling Methods in Pumping Schedule Design during Establishing Surrogate Model. 2011 International Symposium on Water Resource and Environmental Protection, Xi'an, 20-22 May 2011, 212-215.