Predictive model of regional coseismic landslides’ permanent displacement considering uncertainty

Agterberg FP (1992) Combining indicator patterns in weights of evidence modeling for resource evaluation. Nonrenew Resour 1(1):39–50 Alejano LR, González J, Muralha J (2014) Comparison of different techniques of tilt testing and basic friction angle variability assessment. Rock Mech Rock Eng 45:1023–1035 Ambraseys NN, Menu JM (1988) Earthquake-induced ground displacements. Earthq Eng Struct Dyn 16:985–1006 Azarafza M, Akgün H, Ghazifard A, Asghari-Kaljahi E, Rahnamarad J, Derakhshani R (2021) Discontinuous rock slope stability analysis by limit equilibrium approaches–a review. Int J Digital Earth 14(12):1918–1941 Azarafza M, Azarafza M, Akgün H, Atkinson PM, Derakhshani R (2021) Deep learning-based landslide susceptibility mapping. Sci Rep 11(1):1–16 Azarafza M, Ghazifard A, Akgün H, Asghari-Kaljahi E (2018) Landslide susceptibility assessment of South Pars Special Zone, southwest Iran. Environ Earth Sci 77(24):1–29 Bandis SC, Lumsden AC, Barton NR (1983) Fundamentals of rock joint deformation. Int. J. Rock Mech. Min. 20:249–268 Barnhart KR, Hutton EWH, Tucker GE, Gasparini NM, Istanbulluoglu E, Hobley DEJ et al (2020) Short communication: Landlab v2.0: a software package for Earth-surface dynamics. Earth Surf Dynam 8(2):379-397 Bui DT, Hoang ND, Nguyen H, Tran XL (2019) Spatial prediction of shallow landslide using Bat algorithm optimized machine learning approach: A case study in Lang Son Province Vietnam. Adv Eng Inform 42:100978. https://doi.org/10.1016/j.aei.2019.100978 Bui DT, Tuan TA, Klempe H, Pradhan B, Revhaug I (2016) Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree. Landslides 13(2):361–378 Chang M, Zhou Y, Zhou C et al (2020) Coseismic landslides induced by the 2018 Mw 6.6 Iburi, Japan, earthquake: spatial distribution, key factors weight, and susceptibility regionalization. Landslides 18(1):755–772 Cherubini C (1997) Data and considerations on the variability of geotechnical properties of soils. Proc Int Conf Safety Reliab (ESREL 97) 2:1583–1591 Cherubini C (2000) Reliability evaluation of shallow foundation bearing capacity on c′, ϕ′ soils. Can Geotech J 37:264–269 Cho SE (2007) Effects of spatial variability of soil properties on slope stability. Eng Geol 92(3):97-109 Clough RW (1960) The finite element method in plane stress analysis. Proceedings of the 2nd Conference on Electronic Computation. Am Soc Civil Eng Struct Division. Pittsburgh, PA Delgado J, Rosa J, Peláez JA, Rodríguez-Peces MJ, Garrido J, Tsigé M (2020) On the applicability of available regression models for estimating Newmark displacements for low to moderate magnitude earthquakes. the case of the betic cordillera (sspain). Eng Geol 274:105710 Di Matteo L, Valigi D, Ricco R (2013) Laboratory shear strength parameters of cohesive soils: variability and potential effects on slope stability. Bull Eng Geol Environ 72(1):101–106 Dou HQ, Han TC, Gong XN, Zhang J (2014) Probabilistic slope stability analysis considering the variability of hydraulic conductivity under rainfall infiltration–redistribution conditions. Eng Geol 183:1–13 Dou J, Yunus AP, Merghadi A, Shirzadi A, Nguyen H et al (2020) Different sampling strategies for predicting landslide susceptibilities are deemed less consequential with deep learning. Sci Total Environ 720:137320 Du WQ, Huang D, Wang G (2018) Quantification of model uncertainty and variability in Newmark displacement analysis. Soil Dynam Earthquake Eng 109(201):286-298, ISSN 0267-7261 Du W, Wang G (2014) Fully probabilistic seismic displacement analysis of spatially distributed slopes using spatially correlated vector intensity measures. Earthquake Engineering and Structural Dynamics 43(5):661–679 Fan X, Scaringi G, Xu Q, Zhan W, Dai L, Li Y et al (2018) Coseismic landslides triggered by the 8th August 2017 Ms 7.0 Jiuzhaigou earthquake (Sichuan, China): factors controlling their spatial distribution and implications for the seismogenic blind fault identification. Landslides 15(5):967-983 Fang H, Chen YF, Hou Z, Xu G, Wu J (2020) Probabilistic analysis of a cohesion-frictional slope using the slip-line field theory in a Monte-Carlo framework. Comput. Geotech. 120:103398 Gameiro S, Riffel ES, Oliveira G, Guasselli LA (2021) Artificial neural networks applied to landslide susceptibility: the effect of sampling areas on model capacity for generalization and extrapolation. Appl Geograph 102598 Gigovi´c L, Drobnjak S, Pamučar D (2019) The application of the hybrid GIS spatial multi-criteria decision analysis best–worst methodology for landslide susceptibility mapping. ISPRS Int J Geo-Inf 8(2):79 Gironacci E, Nezhad M, Rezania M, Lancioni G (2018) A non-local probabilistic method for modeling of crack propagation. Int J Mech Sci 144:897–908 Gorsevski PV, Brown MK, Panter K, Onasch CM, Simic A, Snyder J (2016) Landslide detection and susceptibility mapping using LiDAR and an artificial neural network approach: a case study in the Cuyahoga Valley National Park. Ohio. Landslides 13(3):467–484 Griffiths DV, Huang J, Fenton GA (2011) Probabilistic infinite slope analysis. Comput Geotech 38(4):577–584 Hammond C, Hall D, Miller S, Swetik P (1992) Level 1 stability analysis (LISA), documentation for Version 2.0. USDA, For. Serv., Moscow, ID. Intermountain Res Sta Gen Tech Rep INT-285 He K, Liu B, Hu X, Zhou R, Xi C, Ma G, Han M, Li Y, Luo G (2022b) Rapid characterization of landslide-debris flow chains of geologic hazards using multimethod investigation: case study of the Tiejiangwan LDC. Rock Mech Rock Eng. https://doi.org/10.1007/s00603-022-02905-9 He K, Li Y, Ma G, Hu X, Liu B, Ma Z, Xu Z (2021a) Failure mode analysis of post-seismic rockfall in shattered mountains exemplified by detailed investigation and numerical modeling. Landslides 18(1):425–446 He K, Ma G, Hu X (2021b) Formation mechanisms and evolution model of the tectonic-related ancient giant basalt landslide in Yanyuan County. China Nat Hazards 106(3):2575–2597 He K, Ma G, Hu X, Liu B, Han M (2022a) The July 2, 2017, Lantian landslide in Leibo, China: mechanisms and mitigation measures. Geomech Eng 28(3):283–298 Hobley DE, Adams JM, Nudurupati SS, Hutton EW, Gasparini NM, Istanbulluoglu E, Tucker GE (2017) Creative computing with Landlab: an open-source toolkit for building coupling and exploring two dimensional numerical models of Earth-surface dynamics. Earth Surf Dyn 5(1) 21–46. https://doi.org/10.5194/esurf-5-21-2017 Hong H, Chen W, Xu C, Youssef AM, Pradhan B, Tien Bui D (2017) Rainfall-induced landslide susceptibility assessment at the Chongren area (China) using frequency ratio, certainty factor, and index of entropy. Geocarto Int 32(2):139–154 Hu Q, Zhou Y, Wang S, Wang F (2020) Machine learning and fractal theory models for landslide susceptibility mapping: case study from the Jinsha River Basin. Geomorphology 351:106975 Hua Y, Wang X, Li Y, Xu P, Xia W (2021) Dynamic development of landslide susceptibility based on slope unit and deep neural networks. Landslides 18:281–302 Huang Yang H (2014) Slope stability analysis by the limit equilibrium method. ASCE Publications, Reston Huang F, Zhang J, Zhou C et al (2020) A deep learning algorithm using a fully connected sparse autoencoder neural network for landslide susceptibility prediction. Landslides 17:217–229 Hsieh S, Chyi-Tyi Lee (2011) Empirical estimation of the Newmark displacement from the Arias intensity and critical acceleration. Eng Geol 122:34–42 Javadi A, Rezania M, Nezhad M (2006) Evaluation of liquefaction induced lateral displacements using genetic programming. Comput Geotech 33(4–5):222–233 Jibson RW (2007) Regression models for estimating coseismic landslide displacement. Eng Geol 91:209–218 Jibson RW (2011) Methods for assessing the stability of slopes during earthquakes—a retrospective. Eng Geol 122(1–2):43–50 Jibson RW, Harp EL, Michael JM (1998) A method for producing digital probabilistic seismic landslide hazard maps: an example from the Los Angeles, California area. US Geol Surv Open-File Rep 98-113 17 Jibson RW, Harp EL, Michael JA (2000) A method for producing digital probabilistic seismic landslide hazard maps. Eng Geol 58(3-4):271–289. https://doi.org/10.1016/S0013-7952(00)00039-9 Jibson RW, Michael JA (2009) Maps showing seismic landslide hazards in Anchorage, Alaska. In: U.S. Geological Survey Scientific Investigations Map 3077. Scale 1:25.000, (11-p) Kalatehjari R, Ali N (2013) A review of three-dimensional slope stability analyses based on limit equilibrium method. Electron J Geotech Eng 18:119–134 Kargel JS, Leonard GJ, Shugar DH, Haritashya UK, Bevington A et al (2016) Geomorphic and geologic controls of geohazards induced by Nepal’s 2015 Gorkha earthquake. Science 351(6269):aac8353 Keefer DK (1984) Landslides caused by earthquakes. Geol Soc Am Bull 95:406–421 Kumar S, Gupta V, Kumar P, Sundriyal YP (2021) Coseismic landslide hazard assessment for the future scenario earthquakes in the Kumaun Himalaya, India. Bullet Eng Geol Environ 80:5219–5235 Li L, Lan H, Guo C et al (2017) A modified frequency ratio method for landslide susceptibility assessment. Landslides 14:727–741 Li D, Wang M, Du W (2020) Influence of spatial variability of soil strength parameters on probabilistic seismic slope displacement hazard analysis. Eng Geol 276:105744 Ling S, Sun C, Li X, Ren Y, Xu J, Huang T (2021) Characterizing the distribution pattern and geologic and geomorphic controls on earthquake-triggered landslide occurrence during the 2017 M s 7.0 Jiuzhaigou earthquake, Sichuan, China. Landslides 18(4):1275-1291 Liu B, Hu X, He K et al (2020) The starting mechanism and movement process of the co-seismic rockslide: a case study of the Laoyingyan rockslide induced by the “5·12” Wenchuan earthquake. J Mountain Sci 17(5):1188–1205 Liu B, He K, Han M, Hu X et al (2021a) Dynamic process simulation of the Xiaogangjian rockslide occurred in shattered mountain based on 3DEC and DFN. Comput Geotech 134:104122 Liu B, Hu X, Ma G, He K, Wu M, Liu D (2021b) Back calculation and hazard prediction of a debris flow in Wenchuan meizoseismal area, China. Bulletin of Engineering Geology and the Environment 80(4):3457–3474 Luo N, Bathurst RJ (2018) Probabilistic analysis of reinforced slopes using RFEM and considering spatial variability of frictional soil properties due to compaction. Georisk 12(2):87–108 Luo LG, Pei XJ, H RQ (2020) Earthquake-triggered landslide occurrence probability in strong seismically mountainous area: a case study of Jiuzhaigou National Geopark. Chin J Rock Mech Eng 1000-6915, CN 42-1397/O3 (In Chinese) Ma G, Rezania M, Nezhad M (2022a) Effects of spatial autocorrelation structure for friction angle on the runout distance in heterogeneous sand collapse. Transport Geotech 33:100705 Ma G, Rezania M, Nezhad M (2022b) Stochastic assessment of landslide influence zone by material point method and generalized geotechnical random field theory. Int J Geomech 22(4):04022002 Ma G, Rezania M, Nezhad M (2022c) Uncertainty quantification of landslide runout motion considering soil interdependent anisotropy and fabric orientation. Landslides 19:1231–1247 Nanehkaran YA, Mao Y, Azarafza M, Kockar MK, Zhu HH (2021) Fuzzy-based multiple decision method for landslide susceptibility and hazard assessment: a case study of Tabriz. Iran Geomech Eng 24(5):407–418 Newmark NM (1965) Effects of earthquakes on dams and embankments. Géotechnique 15(2):139–160 Ng CWW, Yang B, Liu ZQ et al (2021) Spatiotemporal modelling of rainfall-induced landslides using machine learning. Landslides 18:2499–2514 Nguyen VB, Kim YT (2020) Rainfall-earthquake-induced landslide hazard prediction by Monte Carlo simulation: a case study of MT. Umyeon in Korea. KSCE J Civ Eng 24:73–86 Phoon K, Kulhawy FM (1999) Characterization of geotechnical variability. Can Geotech J 36:612–624 Pradel D, Smith PM, Stewart JP, Raad G (2005) Case history of landslide movement during 392the Northridge earthquake. J Geotech Geoenviron Eng 393131(11):1360–1369 Rahardjo H, Satyanaga A, Leong EC, Ng YS, Pang HTC (2012) Variability of residual soil properties. Eng Geol 141:124–140 Ramachandran P, Varoquaux G (2011) Mayavi: 3D visualization of scientific data. IEEE Comput Sci Eng 13(2):40–51 Rathje EM, Kottke AR, Trent WL (2010) The influence of input motion and site property uncertainties on seismic site response analyses. J Geotech Geoenviron Eng ASCE 136(4):607–619 Rathje EM, Saygili G (2008) Probabilistic seismic hazard analysis for the sliding displacement of slopes: Scalar and vector approaches. J Geotech Geoenviron Eng 134(6) 804-814. https://doi.org/10.1061/(ASCE)1090-0241(2008)134:6(804) Refice A, Capolongo D (2002) Probabilistic modeling of uncertainties in earthquake-induced landslide hazard assessment. Computers Geosciences 28(6):735–749 Regmi AD, Devkota KC, Yoshida K, Pradhan B, Pourghasemi HR, Kumamoto T, Akgun A (2014) Application of frequency ratio, statistical index, and weights-of-evidence models and their comparison in landslide susceptibility mapping in Central Nepal Himalaya. Arab J Geosci 7(2):725–742 Rezania M (2008) Evolutionary polynomial regression based constitutive modelling and incorporation in finite element analysis (Doctoral dissertation, University of Exeter) Rezania M, Ma G (2020) Stress-strain modelling of soils in drained and undrained conditions using a multi-model intelligent approach. In: Correia, A., Tinoco, J., Cortez, P., Lamas, L. (eds) Information Technology in Geo-Engineering. ICITG 2019. Springer Ser Geomechanics Geoeng (pp. 419-428). Springer, Cham Rodríguez-Peces MJ, Pérez-García JL, García-Mayordomo J, Azañón JM et al (2011) Applicability of Newmark method at regional, subregional and site scales: seismically induced Bullas and La Paca rock-slide cases (Murcia, SE Spain). Nat Hazards 59:1109–1124 Saygili G, Rathje EM (2008) Empirical predictive models for earthquake-Induced sliding displacements of slopes. J Geotech Geoenviron Eng 134(6):790–803 Saygili G, Rathje EM (2009) Probabilistically based seismic landslide hazard maps: an application in Southern California. Eng Geol 109(2009):183–194 Shahabi H, Khezri S, Ahmad BB, Hashim M (2014) Landslide susceptibility mapping at central Zab basin, Iran: a comparison between analytical hierarchy process, frequency ratio and logistic regression models. Catena 115:55–70 Singh TN, Kainthola A, Venkatesh A (2012) Correlation between point load index and uniaxial compressive strength for different rock types. Rock Mech Rock Eng 45:259–264 Strauch R, Istanbulluoglu E, Nudurupati SS, Bandaragoda C, Gasparini NM, Tucker GE (2018) A hydro-climatological approach to predicting regional landslide probability using Landlab, Earth Surf. Dynamics 6:49–75 Terzhagi K (1950) Mechanism of landslides. In: Paige S (ed) Application of Geology to Engineering Practice (Berkey Volume). Geological Society of America, New York, NY, pp 83–123 Tian Y, Xu C, Ma S et al (2019) Inventory and spatial distribution of landslides triggered by the 8th August 2017 MW 6.5 Jiuzhaigou earthquake. China J Earth Sci 30:206–217 Tien Bui D, Hoang ND, Martínez-Álvarez F, Ngo P-TT, Hoa PV, Pham TD, Samui P et al (2020) A novel deep learning neural network approach for predicting flash flood susceptibility: a case study at a high frequency tropical storm area. Sci Total Environ 701:134413 Wang Y, Akeju OV (2016) Quantifying the cross-correlation between effective cohesion and friction angle of soil from limited site-specific data. Soils Found 56(6):1055–1070 Wang Y, Rathje EM (2015) Probabilistic seismic landslide hazard maps including epistemic uncertainty. Eng Geol 196:313–324 Wang F, Fan X, Yunus AP, Subramanian SS, Huang R (2019) Coseismic landslides triggered by the 2018 Hokkaido, Japan (Mw6.6), earthquake: spatial distribution, controlling factors, and possible failure mechanism. Landslides 16:1551–1566 Wen H, Wu X, Liao X, Wang D, Huang K et al (2022) Application of machine learning methods for snow avalanche susceptibility mapping in the Parlung Tsangpo catchment, southeastern Qinghai-Tibet Plateau. Cold Regions Sci Technol 198:103535 Wilson RC, Keefer DK (1983) Dynamic analysis of a slope failure from the 6 August 1979 Coyote lake, California, earthquake. B Seismol Soc Am 73(3):863–877 Wilson RC, Keefer DK (1985) Predicting areal limits of earthquake-induced landsliding. Geol Surv Prof Pap 1360:317–345 Wolff TF (1985) Analysis and design of embankment dam slopes: a probabilistic approach (Ph.D. thesis). Purdue University, Lafayette, IN., USA Wong LNY, Zhou Y (2021) Boulder falls in Hong Kong-insights from power law relationships and supervised machine learning. Landslides 18:3227–3253 Wu XZ (2013) Trivariate analysis of soil ranking-correlated characteristics and its application to probabilistic stability assessments in geotechnical engineering problems. Soils Found 53(4):540–556 Xi C, Hu X, He K, Liu B (2021) GIS-based coseismic landslide susceptibility assessment using ensemble learning approach: a case of the 2017.8.8 Jiuzhaigou earthquake event. IOP Conf Ser Earth Environ Sci 861:062034 Xi C, Han M, Hu X et al (2022) Effectiveness of Newmark-based sampling strategy for coseismic landslide susceptibility mapping using deep learning, support vector machine, and logistic regression. Bull Eng Geol Environ 81:174. https://doi.org/10.1007/s10064-022-02664-5 Xiao T, Segoni S, Chen L, Yin K, Casagli N (2019) A step beyond landslide susceptibility maps: a simple method to investigate and explain the different outcomes obtained by different approaches. Landslides 1–14 Xu C, Xu X, Yao X, Dai F (2014) Three (nearly) complete inventories of landslides triggered by the May 12, 2008 Wenchuan Mw 7.9 earthquake of China and their spatial distribution statistical analysis. Landslides 11:441–461 Xu XW, Chen GH, Wang QX, Chen LC, Ren ZK, Xu C et al (2017) Discussion on seismogenic structure of Jiuzhaigou earthquake and its implication for current strain state in the southern Qinghai Tibet Plateau. Chin J Geophys 60:4018–4026 (In Chinese) Yiğit A (2020) Prediction of amount of earthquake-induced slope displacement by using Newmark method. Eng Geol 264(2020):105385 Yong R, Ye J, Liang QF, Huang M, Du SG (2018) Estimation of the joint roughness coefficient (JRC) of rock joints by vector similarity measures. B Eng Geol Environ 77:735–749 Young DS (1986) A generalized probabilistic approach for slope analysis: practical application to an open pit iron ore mine. Int J Min Geol Eng 4(1):3–13 Yue X, Wu S, Yin Y et al (2018) Risk identification of seismic landslides by joint newmark and rockfall analyst models: a case study of roads affected by the Jiuzhaigou earthquake. Int J Disaster Risk Sci 9:392–406 Zang M, Qi S, Zou Y, Sheng Z, Zamora BS (2020) An improved method of Newmark analysis for mapping hazards of coseismic landslides. Nat Hazards Earth Syst Sci 20:713–726 Zhu AX, Miao Y, Liu J, Bai S, Zeng C, Ma T, Hong H (2019) A similarity-based approach to sampling absence data for landslide susceptibility mapping using data-driven methods. Catena 183:104188