Stability Assessment of Shallow Soil Landslide and Activating Rainfall Threshold
Abstract
The transient rainfall infiltration and grid-based regional slope-stability (TRIGRS)-Scoops three-dimensional (3D) coupling model combines the influences of rainfall infiltration and 3D topography on slope safety. However, the Scoops 3D model defines the physical and mechanical parameters of underground materials with a uniform or layered method, which cannot describe the variability in the horizontal direction. To address this limitation, a method of creating a 3D distribution file of physical and mechanical parameters for underground materials was proposed. This method was applied to a mountainous area in Chishang Town, China. Based on the TRIGRS-Scoops 3D coupling model, the stability of slopes in the study area was assessed under different rainfall conditions. The dangerous slopes were located where the proportion of unstable grids exceeded 1%. The TRIGRS-Scoops 3D coupling model was repeatedly used to determine the curve of the rainfall threshold for landslide activation. This curve is based on the intensity () and duration () of rainfall. The results show that the 3D distribution file can effectively reflect the variability of parameters in the horizontal direction. The landslide activating rainfall threshold curves for the 13 dangerous slopes in the study area exhibit a linear relationship between and . This study can reveal slope stability under different rainfall conditions and provide a theoretical basis for landslide warnings.
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Data Availability Statement
The data that support the findings of this study are available from the corresponding author, Chao Yin, upon reasonable request.
Acknowledgments
This research was supported by the National Natural Science Foundation of China (Grant No. 51808327) and Natural Science Foundation of Shandong Province (Grant No. ZR2019PEE016).
References
Abraham, M. T., V. Manjunath, N. Satyam, and B. Pradhan. 2023. “Spatio-temporal landslide forecasting using process-based and data-driven approaches: A case study from Western Ghats, India.” Catena 223 (Apr): 106948. https://doi.org/10.1016/j.catena.2023.106948.
Alvioli, M., and R. L. Baum. 2016. “Parallelization of the TRIGRS model for rainfall-induced landslides using the message passing interface.” Environ. Modell. Software 81 (Jul): 122–135. https://doi.org/10.1016/j.envsoft.2016.04.002.
Alvioli, M., F. Guzzetti, and M. Rossi. 2014. “Scaling properties of rainfall induced landslides predicted by a physically based model.” Geomorphology 213 (May): 38–47. https://doi.org/10.1016/j.geomorph.2013.12.039.
Arsyad, U., A. S. Soma, B. Mappangaja, R. Amaliah, and P. F. Nurdin. 2021. “Analysis of the landslides vulnerability level using frequency ratio method in Tangka Watershed.” Earth Environ. Sci. 870 (1): 012013. https://doi.org/10.1088/1755-1315/870/1/012013.
Baumann, V., C. Bonadonna, and S. Cuomo. 2018. “Slope stability models for rainfall-induced lahars during long-lasting eruptions.” J. Volcanol. Geotherm. Res. 359 (Jun): 78–94. https://doi.org/10.1016/j.jvolgeores.2018.06.018.
Chen, Y. L., D. H. Chen, Z. C. Li, and J. B. Huang. 2016. “Preliminary studies on the dynamic prediction method of rainfall-triggered landslide.” J. Mountain Sci. 13 (10): 1735–1745. https://doi.org/10.1007/s11629-014-3110-5.
Dai, K., C. Chen, X. Shi, M. Wu, W. Feng, Q. Xu, R. Liang, G. Zhuo, and Z. Li. 2023. “Dynamic landslides susceptibility evaluation in Baihetan Dam area during extensive impoundment by integrating geological model and InSAR observations.” Int. J. Appl. Earth Obs. Geoinf. 116 (Feb): 103157. https://doi.org/10.1016/j.jag.2022.103157.
Dikshit, A., N. Satyam, and B. Pradhan. 2019. “Estimation of rainfall-induced landslides using the TRIGRS model.” Earth Syst. Environ. 3 (3): 575–584. https://doi.org/10.1007/s41748-019-00125-w.
Dyson, A. P., and A. Tolooiyan. 2020. “Comparative approaches to probabilistic finite element methods for slope stability analysis.” Simul. Modell. Pract. Theory 100 (Apr): 102061. https://doi.org/10.1016/j.simpat.2019.102061.
Elbaz, K., T. Yan, A. Zhou, and S. L. Shen. 2022. “Deep learning analysis for energy consumption of shield tunneling machine drive system.” Tunnelling Underground Space Technol. 123 (May): 104405. https://doi.org/10.1016/j.tust.2022.104405.
He, J., H. Qiu, S. Hu, W. Yang, Y. Pei, D. Yang, Y. Zhang, S. Ma, and M. Cao. 2019. “Stability analysis of shallow landslides based on TRIGRS model.” Quat. Sci. 39 (5): 1222–1234. https://doi.org/10.11928/j.issn.1001-7410.2019.05.14.
He, J., H. Qiu, F. Qu, S. Hu, D. Yang, Y. Shen, Y. Zhang, H. Sun, and M. Cao. 2021. “Prediction of spatiotemporal stability and rainfall threshold of shallow landslides using the TRIGRS and Scoops3D models.” Catena 197 (Feb): 104999. https://doi.org/10.1016/j.catena.2020.104999.
Khalid, E., A. N. Zhou, and S. L. Shen. 2023. “Deep reinforcement learning approach to optimize the driving performance of shield tunnelling machines.” Tunnelling Underground Space Technol. 136 (Jun): 105104. https://doi.org/10.1016/j.tust.2023.105104.
Kumar, A., R. K. Sharma, and V. K. Bansal. 2019. “GIS-based comparative study of information value and frequency ratio method for landslide hazard zonation in a part of mid-Himalaya in Himachal Pradesh.” Innovative Infrastruct. Solutions 4 (1): 1–17. https://doi.org/10.1007/s41062-018-0188-6.
Lin, S. S., A. N. Zhou, and S. L. Shen. 2023. “Safety assessment of excavation system via TOPSIS-based MCDM modelling in fuzzy environment.” Appl. Soft Comput. J. 138 (May): 110206. https://doi.org/10.1016/j.asoc.2023.110206.
Liu, L., K. L. Yin, J. J. Wang, J. Zhang, and F. M. Huang. 2016. “Dynamic evaluation of regional landslide hazard due to rainfall: A case study in Wanzhou central district Three Gorges Reservoir.” Chin. J. Rock Mech. Eng. 35 (3): 558–569. https://doi.org/10.13722/j.cnki.jrme.2015.0495.
Liu, L., K. L. Yin, Y. Xu, Z. Lian, and N. Wang. 2018. “Evaluation of regional landslide stability considering rainfall and variation of water level of reservoir.” Chin. J. Rock Mech. Eng. 37 (2): 403–414.
Liu, Y. F., X. Fu, Q. Zhu, H. W. Zeng, and H. Y. Wu. 2023. “An efficient and fine slope units division method with consideration of the regional geomorphological characteristics.” Sci. Surv. Mapp. 48 (4): 211–220.
Lv, J. J., W. Fan, and Y. Q. Lv. 2018. “Hazard assessment of shallow landslide considering soil depth distribution-A case study of Qinba Mountains in Shaanxi Province.” J. Catastrophology 33 (2): 218–223.
Ma, J., X. Wang, and G. Yuan. 2023. “Evaluation of geological hazard susceptibility based on the regional division information value method.” ISPRS Int. J. Geo-Inf. 12 (1): 17. https://doi.org/10.3390/ijgi12010017.
Marin, R. J. 2020. “Physically based and distributed rainfall intensity and duration thresholds for shallow landslides.” Landslides 17 (12): 2907–2917. https://doi.org/10.1007/s10346-020-01481-9.
Marin, R. J., E. F. García, and E. Aristizábal. 2020. “Effect of basin morphometric parameters on physically-based rainfall thresholds for shallow landslides.” Eng. Geol. 278 (Dec): 105855. https://doi.org/10.1016/j.enggeo.2020.105855.
Marin, R. J., M. F. Velásquez, E. F. García, M. Alvioli, and E. Aristizábal. 2021a. “Assessing two methods of defining rainfall intensity and duration thresholds for shallow landslides in data-scarce catchments of the Colombian Andean Mountains.” Catena 206 (Nov): 105563. https://doi.org/10.1016/j.catena.2021.105563.
Marin, R. J., M. F. Velásquez, and O. Sánchez. 2021b. “Applicability and performance of deterministic and probabilistic physically based landslide modeling in a data-scarce environment of the Colombian Andes.” J. South Am. Earth Sci. 108 (Jun): 103175. https://doi.org/10.1016/j.jsames.2021.103175.
Medina, V., M. Hürlimann, Z. Guo, A. Lloret, and J. Vaunat. 2021. “Fast physically-based model for rainfall-induced landslide susceptibility assessment at regional scale.” Catena 201 (Jun): 105213. https://doi.org/10.1016/j.catena.2021.105213.
Mukhammadzoda, S., F. Shohnavaz, O. Ilhomjon, and G. Zhang. 2021. “Application of frequency ratio method for landslide susceptibility mapping in the Surkhob Valley, Tajikistan.” J. Geosci. Environ. Prot. 9 (12): 168–189. https://doi.org/10.4236/gep.2021.912011.
NASAESDN (NASA Earth Science Data Network). 2016. “ASF data search vertex.” Accessed March 15, 2023. https://nasadaacs.eos.nasa.gov/.
Rashid, B., J. Iqbal, and L. J. Su. 2020. “Landslide susceptibility analysis of Karakoram Highway using analytical hierarchy process and Scoops 3D.” J. Mountain Sci. 17 (7): 1596–1612. https://doi.org/10.1007/s11629-018-5195-8.
RESDC (Resource and Environment Science and Data Center). 2023. “Geological and soil data.” Accessed March 15, 2023. https://www.resdc.cn.
Sameen, M. I., B. Pradhan, and S. Lee. 2020. “Application of convolutional neural networks featuring Bayesian optimization for landslide susceptibility assessment.” Catena 186 (Mar): 104249. https://doi.org/10.1016/j.catena.2019.104249.
Shen, S. L., S. S. Lin, and A. N. Zhou. 2023a. “A cloud model-based approach for risk analysis of excavation system.” Reliab. Eng. Syst. Saf. 231 (Mar): 108984. https://doi.org/10.1016/j.ress.2022.108984.
Shen, S. L., T. Yan, and A. N. Zhou. 2023b. “Estimating locations of soil–rock interfaces based on vibration data during shield tunneling.” Autom. Constr. 150 (Jun): 104813. https://doi.org/10.1016/j.autcon.2023.104813.
Vandromme, R., Y. Thiery, S. Bernardie, and O. Sedan. 2020. “ALICE (assessment of landslides induced by climatic events): A single tool to integrate shallow and deep landslides for susceptibility and hazard assessment.” Geomorphology 367 (Oct): 107307. https://doi.org/10.1016/j.geomorph.2020.107307.
Viet, T. T., M. Alvioli, G. Lee, and H. U. An. 2018. “Three-dimensional, time-dependent modeling of rainfall-induced landslides over a digital landscape: A case study.” Landslides 15 (Jun): 1071–1084. https://doi.org/10.1007/s10346-017-0931-7.
Xue, W., Z. Xu, H. Wang, and Z. Ren. 2019. “Hazard assessment of landslide dams using the evidential reasoning algorithm with multi-scale hesitant fuzzy linguistic information.” Appl. Soft Comput. 79 (Jun): 74–86. https://doi.org/10.1016/j.asoc.2019.03.032.
Yao, J., X. Z. Li, and R. C. Xu. 2021. “Dynamic identification of three-dimensional stability of potential landslides in a typical section of the proposed Sichuan-Tibet Railway under rainfall conditions.” J. Disaster Prev. Mitigation Eng. 4 (13): 422–431.
Yin, C. 2020. “Hazard evaluation and regionalization of highway flood disasters in China.” Nat. Hazards 100 (2): 535–550. https://doi.org/10.1007/s11069-019-03824-9.
Yin, C., H. Li, F. Che, Y. Li, Z. Hu, and D. Liu. 2020a. “Susceptibility mapping and zoning of highway landslide disasters in China.” PLoS One 15 (9): e0235780. https://doi.org/10.1371/journal.pone.0235780.
Yin, C., H. Li, Z. Hu, and Y. Li. 2020b. “Application of the terrestrial laser scanning in slope deformation monitoring: Taking a highway slope as an example.” Appl. Sci. 10 (8): 2808. https://doi.org/10.3390/app10082808.
Yin, C., and J. L. Zhang. 2018. “Hazard regionalization of debris-flow disasters along highways in China.” Supplement, Nat. Hazards 91 (Suppl1): 129–147. https://doi.org/10.1007/s11069-018-3229-8.
ZCPDON (Zibo City Public Data Open Network). 2023. “Information on geologic hazard sites.” Accessed March 15, 2023. https://data.zibo.gov.cn/.
Zhang, H., C. Yin, S. Wang, and B. Guo. 2022. “Landslide susceptibility mapping based on landslide classification and improved convolutional neural networks.” Nat. Hazards 116 (2): 1931–1971. https://doi.org/10.1007/s11069-022-05748-3.
Zhang, S., L. Zhao, R. Delgado-Tellez, and H. Bao. 2018. “A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale.” Nat. Hazards Earth Syst. Sci. 18 (3): 969–982. https://doi.org/10.5194/nhess-18-969-2018.
Zheng, J. L., X. Z. Li, J. Yao, and W. X. Yu. 2023. “Dynamic prediction of spatiotemporal stability of potential landslides based on the TRIGRS and SCOOPS 3D coupling model.” J. Nat. Disasters 32 (2): 199–209.
Zhou, W., H. Qiu, L. Wang, Y. Pei, B. Tang, S. Ma, D. Yang, and M. Cao. 2022. “Combining rainfall-induced shallow landslides and subsequent debris flows for hazard chain prediction.” Catena 213 (Jun): 106199. https://doi.org/10.1016/j.catena.2022.106199.
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Published In
Natural Hazards Review
Volume 25 • Issue 2 • May 2024
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© 2024 American Society of Civil Engineers.
History
Received: Jun 21, 2023
Accepted: Nov 8, 2023
Published online: Jan 23, 2024
Published in print: May 1, 2024
Discussion open until: Jun 23, 2024
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