Articles | Volume 26, issue 5
https://doi.org/10.5194/nhess-26-2367-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-26-2367-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Constructing physical-based rainfall landslides prediction model: insights from rainfall threshold curves database of slope units
Kai Wang
CORRESPONDING AUTHOR
School of architecture and civil engineering, Zhongyuan University of Technology, Zhengzhou, 450007, China
Linmao Xie
School of architecture and civil engineering, Zhongyuan University of Technology, Zhengzhou, 450007, China
Shuailong Xie
School of architecture and civil engineering, Zhongyuan University of Technology, Zhengzhou, 450007, China
Shaojie Zhang
CORRESPONDING AUTHOR
Key Laboratory of Mountain Hazards and Earth Surface Process, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610041, China
Yongyang Jiang
Zhejiang Zhongnan Construction Group Steel Structure Co., Ltd, Hangzhou, 311400, China
Ji Zhang
Sichuan Institution of Geological Engineering Investigation Group Co.LTD, Chengdu, 610041, China
Lin Zhu
School of architecture and civil engineering, Zhongyuan University of Technology, Zhengzhou, 450007, China
Zhiliu Wang
School of architecture and civil engineering, Zhongyuan University of Technology, Zhengzhou, 450007, China
Fuzhou Qi
School of architecture and civil engineering, Zhongyuan University of Technology, Zhengzhou, 450007, China
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Shaojie Zhang, Xiaohu Lei, Hongjuan Yang, Kaiheng Hu, Juan Ma, Dunlong Liu, and Fanqiang Wei
Hydrol. Earth Syst. Sci., 28, 2343–2355, https://doi.org/10.5194/hess-28-2343-2024, https://doi.org/10.5194/hess-28-2343-2024, 2024
Short summary
Short summary
Antecedent effective precipitation (AEP) plays an important role in debris flow formation, but the relationship between AEP and the debris flow occurrence (Pdf) is still not quantified. We used numerical calculation and the Monte Carlo integration method to solve this issue. The relationship between Pdf and AEP can be described by the piecewise function, and debris flow is a small-probability event comparing to rainfall frequency because the maximum Pdf in Jiangjia Gully is only 15.88 %.
Shaojie Zhang, Hongjuan Yang, Dunlong Liu, Kaiheng Hu, and Fangqiang Wei
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-57, https://doi.org/10.5194/hess-2022-57, 2022
Manuscript not accepted for further review
Short summary
Short summary
We use a numerical model to find that the relationships of AEP-α and AEP-β can be respectively described by the specific function. The I-D threshold curve can regularly move in the I-D coordinate system rather than a conventional threshold curve stay the same regardless of AEP variation. This work is helpful to understand the influence mechanism of AEP on I-D threshold curve and are beneficial to improve the prediction capacity of the I-D threshold.
Cited articles
Alvioli, M., Guzzetti, F., and Marchesini, I.: Parameter-free delineation of slope units and terrain subdivision of Italy, Geomorphology, 358, 107124, https://doi.org/10.1016/j.geomorph.2020.107124, 2020.
Apip, Takara, K., Yamashiki, Y., Sassa, K., Bagiawan, I. A., and Fukuoka, H.: A distributed hydrological-geotechnical model using satellite-derived rainfall estimates for shallow landslide prediction system at a catchment scale, Landslides, 7, 237–258, https://doi.org/10.1007/s10346-010-0214-z, 2010.
Aristizábal, E., Vélez, J. I., Martínez, H. E., and Jaboyedoff, M.: SHIA_Landslide: a distributed conceptual and physically based model to forecast the temporal and spatial occurrence of shallow landslides triggered by rainfall in tropical and mountainous basins, Landslides, 13, 497–517, https://doi.org/10.1007/s10346-015-0580-7, 2016.
ASTM D6528-17: Standard test method for consolidated undrained direct simple shear testing of fine grain soils, ASTM International, West Conshohocken, PA, USA, https://www.astm.org/d6528-17.html (last access: 24 May 2026), 2017.
Baum, R. L., Savage, W. Z., and Godt, J.: TRIGRS – a Fortran program for transient rainfall infiltration and grid-based regional slope-stability analysis, US Geological Survey Open File Report 2008-1159, 2, https://doi.org/10.3133/ofr20081159, 2008.
Bezak, N., Šraj, M., and Matjaž, M.: Copula-based IDF curves and empirical rainfall thresholds for flash floods and rainfall-induced landslides, J. Hydrol., 541, 272–284, https://doi.org/10.1016/j.jhydrol.2016.02.058, 2016.
Bogaard, T. and Greco, R.: Invited perspectives: Hydrological perspectives on precipitation intensity-duration thresholds for landslide initiation: proposing hydro-meteorological thresholds, Nat. Hazards Earth Syst. Sci., 18, 31–39, https://doi.org/10.5194/nhess-18-31-2018, 2018.
Brunetti, M. T., Peruccacci, S., Rossi, M., Luciani, S., Valigi, D., and Guzzetti, F.: Rainfall thresholds for the possible occurrence of landslides in Italy, Nat. Hazards Earth Syst. Sci., 10, 447–458, https://doi.org/10.5194/nhess-10-447-2010, 2010.
Cuomo, S., Di Perna, A., and Martinelli, M.: Modelling the spatio-temporal evolution of a rainfall-induced retrogressive landslide in an unsaturated slope, Eng. Geol., 294, 106371, https://doi.org/10.1016/j.enggeo.2021.106371,2021.
Domènech, G., Alvioli, M., and Corominas, J.: Preparing first-time slope failures hazard maps: from pixel-based to slope unit-based, Landslides, 17, 249–265, https://doi.org/10.1007/s10346-019-01279-4, 2019.
Fawcett, T.: Introduction to ROC analysis, Pattern. Recogn. Lett., 27, 861–874, https://doi.org/10.1016/j.patrec.2005.10.010, 2006.
Greco, V.: Efficient Monte Carlo Technique for Locating Critical Slip Surface, J. Geotech. Eng., 122, 517–525, https://doi.org/10.1061/(ASCE)0733-9410(1996)122:7(517), 1996.
Gu, T., Wang, J., Fu, X., and Liu, Y.: GIS and limit equilibrium in the assessment of regional slope stability and mapping of landslide susceptibility, B. Eng. Geol. Environ.,74, 1–11, https://doi.org/10.1007/s10064-014-0689-2, 2014.
Guo, Z., Torra, O., Hürlimann, M., Abancó, C., and Medina, V.: FSLAM: A QGIS plugin for fast regional susceptibility assessment of rainfall-induced landslides, Environ. Modell. Softw., 150, 105354, https://doi.org/10.1016/j.envsoft.2022.105354, 2022.
Hong, M., Kim, J., and Jeong, S.: Rainfall intensity-duration thresholds for landslide prediction in South Korea by considering the effects of antecedent rainfall, Landslides, 15, https://doi.org/10.1007/s10346-017-0892-x, 2017.
Hong, Y., Hiura, H., Shino, K., Sassa, K., Suemine, A., Fukuoka, H., and Wang, G.: The influence of intense rainfall on the activity of large-scale crystalline schist landslides in Shikoku Island, Japan, Landslides, 2, 97–105, https://doi.org/10.1007/s10346-004-0043-z, 2005.
Huang, F., Tao, S., Chang, Z., Huang, J., Fan, X., Jiang, S. H., and Li, W.: Efficient and automatic extraction of slope units based on multi-scale segmentation method for landslide assessments, Landslides, 18, https://doi.org/10.1007/s10346-021-01756-9,2021.
Kanungo, D. and Sharma, S.: Rainfall thresholds for prediction of shallow landslides around Chamoli-Joshimath region, Garhwal Himalayas, India, Landslides, 11, 629–638, https://doi.org/10.1007/s10346-013-0438-9, 2014.
Kim, S., Chun, K., Kim, M., Catani, F., Choi, B., and Seo, J. I.: Effect of antecedent rainfall conditions and their variations on shallow landslide-triggering rainfall thresholds in South Korea, Landslides, 18, https://doi.org/10.1007/s10346-020-01505-4, 2020.
Li, D., Wang, Z., Guo, H., Zhang, Y., Cheng, X., and Yu, Q.: Deep Learning in Slope Stability Analysis: Evolution, Challenges, and Future Directions, Geotech. Geol. Eng., 43, 1–48, https://doi.org/10.1007/s10706-025-03424-4, 2025.
Liang, W. L. and Uchida, T.: Performance and topographic preferences of dynamic and steady models for shallow landslide prediction in a small catchment, Landslides, 19, https://doi.org/10.1007/s10346-021-01771-w, 2021.
Liu, S. H., Du, J., Yin, K. L., Zhou, C., Huang, C. C., Jiang, J., and Yu, J.: Regional early warning model for rainfall induced landslide based on slope unit in Chongqing, China, Eng. Geol., 333, 107464, https://doi.org/10.1016/j.enggeo.2024.107464, 2024.
Ma, T., Changjiang, L., Lu, Z., and Bao, Q.: Rainfall intensity–duration thresholds for the initiation of landslides in Zhejiang Province, China, Geomorphology, 245, https://doi.org/10.1016/j.geomorph.2015.05.016, 2015.
Marra, F.: Rainfall thresholds for landslide occurrence: systematic underestimation using coarse temporal resolution data, Nat. Hazards, 95, https://doi.org/10.1007/s11069-018-3508-4, 2018.
Medina, V., Hürlimann, M., Guo, Z., Lloret, A., and Vaunat, J.: Fast physically-based model for rainfall-induced landslide susceptibility assessment at regional scale, Catena, 201, 105213, https://doi.org/10.1016/j.catena.2021.105213, 2021.
Moeineddin, A., Seguí, C., Dueber, S., and Fuentes, R.: Physics-informed neural networks applied to catastrophic creepping landslides, Landslides, 20, 1853–1863, https://doi.org/10.1007/s10346-023-02072-0, 2023.
Montgomery, D. and Dietrich, W. :A Physically Based Model for the Topographic Control on Shallow Landsliding, Water. Resour. Res., 30, 1153–1172, https://doi.org/10.1029/93WR02979, 1994.
Montrasio, L. and Valentino, R.: Modelling Rainfall-induced Shallow Landslides at Different Scales Using SLIP – Part I, Proced. Eng., 158, 476–481, https://doi.org/10.1016/j.proeng.2016.08.475, 2016.
Pinho, T. and Augusto Filho, O.: Landslide susceptibility mapping using the infinite slope, SHALSTAB, SINMAP, and TRIGRS models in Serra do Mar, Brazil, J. Mt. Sci.-Engl., 19, 1018–1036, https://doi.org/10.1007/s11629-021-7057-z, 2022.
Pradhan, A., Lee, S. R., and Kim, Y. T.: A shallow slide prediction model combining rainfall threshold warnings and shallow slide susceptibility in Busan, Korea, Landslides, 16, 647–659, https://doi.org/10.1007/s10346-018-1112-z, 2018.
Rigon, R., Bertoldi, G., and Over, T.: GEOtop: A Distributed Hydrological Model with Coupled Water and Energy Budgets, J. Hydrometeorol., 7, 371–388, https://doi.org/10.1175/JHM497.1, 2006.
Rosi, A., Segoni, S., Canavesi, V., Monni, A., Gallucci, A., and Casagli, N.: Definition of 3D rainfall thresholds to increase operative landslide early warning system performances, Landslides, 18, https://doi.org/10.1007/s10346-020-01523-2, 2020.
Rossi, G., Catani, F., Leoni, L., Segoni, S., and Tofani, V.: HIRESSS: a physically based slope stability simulator for HPC applications, Nat. Hazards Earth Syst. Sci., 13, 151–166, https://doi.org/10.5194/nhess-13-151-2013, 2013.
Spiker, E. C. and Gori, P.: National landslide hazards mitigation strategy: a framework for loss reduction, US Geological Survey Circular 1244, https://doi.org/10.3133/cir1244, 2003.
Tarboton, D. and Goodwin, C.: The SINMAP approach to terrain stability mapping, in: Proceedings of the 8th Congress of the International Association of Engineering Geology and the Environment, edited by: Moore, D. and Hungr, O., Vancouver, Canada, 21–25 September 1998, A. A. Balkema, Rotterdam, 2, 1157–1166, ISBN 90-5410-990-4, 1998.
Tufano, R., Formetta, G., Calcaterra, D., and De Vita, P.: Hydrological control of soil thickness spatial variability on the initiation of rainfall-induced shallow landslides using a three-dimensional model, Landslides, 18, https://doi.org/10.1007/s10346-021-01681-x, 2021.
Turel, M. and Frost, J.: Delineation of Slope Profiles from Digital Elevation Models for Landslide Hazard Analysis, Geo-Risk 2011: Risk Assessment and Management, Atlanta, Georgia, USA, 26–28 June 2011, ASCE, Reston, VA, 829–836, https://doi.org/10.1061/41183(418)87, 2011.
Van Genuchten, M.: A Closed-form Equation for Predicting the Hydraulic Conductivity of Unsaturated Soils, Soil Sci. Soc. Am. J., 44, https://doi.org/10.2136/sssaj1980.03615995004400050002x, 1980.
Wang, K. and Zhang, S.: Rainfall-induced landslides assessment in the Fengjie County, Three-Gorge reservoir area, China, Nat. Hazards, 108, 1–28, https://doi.org/10.1007/s11069-021-04691-z, 2021.
Wang, K., Zhang, S., Delgado Téllez, R., and Wei, F.: A new slope unit extraction method for regional landslide analysis based on morphological image analysis, Bull. Eng. Geol. Environ., 78, 4139–4151, https://doi.org/10.1007/s10064-018-1389-0, 2019.
Wang, K., Zhang, S., Xie, W. L., and Guan, H.: Prediction of the instability probability for rainfall induced landslides: the effect of morphological differences in geomorphology within mapping units, J. Mt. Sci-Engl., 20, 1249–1265, https://doi.org/10.1007/s11629-022-7789-4, 2023.
Wang, K., Xie, S., Zhang, S., Zhu, L., Ma, J., Liu, D., and Yang, H.: Creating a big data source of landslide deformation stages: New thoughts on identifying displacement warning thresholds, J. Asian. Earth. Sci., 266, 106120, https://doi.org/10.1016/j.jseaes.2024.106120, 2024.
Wang, K., Xie, S., Xie, L., Zhang, S., Zhu, L., Qi, F., Luo, H., and Zhao, X.: Research on the Impact of Regional-Scale Soil Mechanics Parameter Disturbances on Rainfall Landslides Warning, Geosciences, 15, 449, https://doi.org/10.3390/geosciences15120449, 2025.
Wang, X., Zhang, L., Wang, S., and Lari, S.: Regional landslide susceptibility zoning with considering the aggregation of landslide points and the weights of factors, Landslides, 11, https://doi.org/10.1007/s10346-013-0392-6, 2013.
Yan, G., Cheng, H., Jiang, Z., Teng, L., Tang, M., Shi, T., Jiang, Y., Yang, G., and Zhou, Q.: Recognition of Fluvial Bank Erosion Along the Main Stream of the Yangtze River, Engineering, 19, https://doi.org/10.1016/j.eng.2021.03.027, 2021.
Zhang, L. Y. and Zhang, J. M.: Extended algorithm using Monte Carlo techniques for searching general critical slip surface in slope stability analysis, Chinese Journal of Geotechnical Engineering, 28, 857–862, https://www.cgejournal.com/en/article/id/12113 (last access: 24 May 2026), 2006 (in Chinese).
Zhang, S., Zhao, L., Delgado-Tellez, R., and Bao, H.: A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale, Nat. Hazards Earth Syst. Sci., 18, 969–982, https://doi.org/10.5194/nhess-18-969-2018, 2018.
Zhang, S., Xu, C. X., Wei, F., Hu, K., Xu, H., Zhao, L. Q., and Zhang, G. P.: A physics-based model to derive rainfall intensity-duration threshold for debris flow, Geomorphology, 351, 106930, https://doi.org/10.1016/j.geomorph.2019.106930, 2019.
Zhang, S., Ma, Z., Li, Y., Hu, K., Zhang, Q., and Li, L.: A grid-based physical model to analyze the stability of slope unit, Geomorphology, 391, 107887, https://doi.org/10.1016/j.geomorph.2021.107887, 2021.
Zhuang, J., Iqbal, J., Jianbing, P., and Tieming, L.:Probability Prediction Model for Landslide Occurrences in Xi'an, Shaanxi Province, China, J. Mt Sci.-Engl., 11, 345–359, https://doi.org/10.1007/s11629-013-2809-z, 2014.
Zhuang, J., Peng, J., Xu, Y., Xu, Q., Zhu, X., and Li, W.: Assessment and mapping of slope stability based on slope units: A case study in Yan'an, China, J. Earth. Syst. Sci., 125, https://doi.org/10.1007/s12040-016-0741-7, 2016.
Short summary
This manuscript integrates physical methods, rainfall threshold warning methods, and slope units to develop a rapid forecasting model for rainfall landslides at a regional scale. The application results indicate that the model runs in less than 12 min, with missing alarm and false alarm rates of 11.8 % and 21.1 %, respectively. This study is expected to provide insights for the rapid forecasting of rainfall landslides in the impoverished mountainous regions of developing countries.
This manuscript integrates physical methods, rainfall threshold warning methods, and slope units...
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