Articles | Volume 28, issue 11
https://doi.org/10.5194/hess-28-2343-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-2343-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Jun 2024
Research article |
| 04 Jun 2024
| 04 Jun 2024
Investigation of the functional relationship between antecedent rainfall and the probability of debris flow occurrence in Jiangjia Gully, China
Shaojie Zhang
Key Laboratory of Mountain Hazards and Engineering Resilience, Chinese Academy of Sciences, Chengdu, 610041, China
Xiaohu Lei
Key Laboratory of Mountain Hazards and Engineering Resilience, Chinese Academy of Sciences, Chengdu, 610041, China
Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, China
Chongqing School, University of Chinese Academy of Sciences, Chongqing 400714, China
Hongjuan Yang
Key Laboratory of Mountain Hazards and Engineering Resilience, Chinese Academy of Sciences, Chengdu, 610041, China
Key Laboratory of Mountain Hazards and Engineering Resilience, Chinese Academy of Sciences, Chengdu, 610041, China
Juan Ma
China Institute for Geo-Environment Monitoring, Beijing, 100081, China
Dunlong Liu
College of Software Engineering, Chengdu University of Information and Technology, Chengdu, 610225, China
Fanqiang Wei
CORRESPONDING AUTHOR
Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, China
Chongqing School, University of Chinese Academy of Sciences, Chongqing 400714, China
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Cited articles
Abraham, M. T., Satyam, N., Pradhan, B., and Alamri, A. M.: Forecasting of landslides using rainfall severity and soil wetness: A probabilistic approach for Darjeeling Himalayas, Water (Switzerland), 12, 1–19, 2020.
Abraham, M. T., Satyan, N., Rosi, A., Pradhan, B., and Segoni, S.: Usage of antecedent soil moisture for improving the performance of rainfall thresholds for landslide early warning, Catena, 200, 105147, https://doi.org/10.1016/j.catena.2021.105147, 2021.
Adams, B., Fraser, H., Howard, C., and Hanafy, M.: Meteorological data analysis for drainage system design, J. Environ. Eng., 112, 827–848, https://doi.org/10.1061/(ASCE)0733-9372(1986)112:5(827), 1986.
Albert, G. E.: A general theory of stochastic estimates of the Neumann series for solution of certain Fredholm integral equations and related series, in: Symposium of Monte Carlo Methods, edited by: Meyer, M. A., Wiley, New York, https://www.osti.gov/servlets/purl/4427633 (last access: 29 May 2024), 1956.
Bel, C., Liébault, F., Navratil O., Eckert N., Bellot H., Fontaine, F., and Laigle, D.: Rainfall control of debris-flow triggering in the Réal Torrent, Southern French Prealphs, 291, 17–32, 2017.
Bennett, G. L., Molnar, P., Mcardell, B. W., and Burlando, P.: A probabilistic sediment cascade model of sediment transfer in the Illgraben, Water Resour. Res., 50, 1225–1244, 2014.
Bernard, M. and Gregoretti, C.: The use of rain gauge measurements and radar data for the model-based prediction of runoff-generated debris flow occurrence in early warning systems, Water Resour. Res., 57, e2020WR027893, https://doi.org/10.1029/2020WR027893, 2021.
Berti, M. and Simoni, A.: Experimental evidences and numerical modelling of debris flow initiated by channel runoff, Landslides, 3, 171–182, 2005.
Calvo, B. and Savi, F.: A real-world application of Monte Carlo procedure for debris flow risk assessment, Comput. Geosci., 35, 967–977, 2009.
Castillo, V. M., Gómez-Plaza, A., and Martínez-Mena, M.: The role of antecedent soil water content in the runoff response of semiarid catchments: a simulation approach, J. Hydrol., 284, 114–130, 2003.
Chen, C. W., Oguchi, T., Chen, H., and Lin, G. W.: Estimation of the antecedent rainfall period for mass movements in Taiwan, Environ. Earth Sci., 77, 184, https://doi.org/10.1007/s12665-018-7377-7, 2018.
Chen, C. W., Saito, H., and Oguchi, T.: Analyzing rainfall-induced mass movements in Taiwan using the soil water index, Landslides, 14, 1031–1041, 2017.
Coe, J. A., Kinner, D. A., and Godt, J. W.: Initiation conditions for debris flows generated by runoff at Chalk Cliffs, central Colorado, Geomorphology, 3, 270–297, 2008.
Crozier, M. J.: Landslides: causes, consequences & environment, Croom Helm, London, p. 25, https://www.cabidigitallibrary.org/doi/full/10.5555/19871915008 (last access: 29 May 2024), 1986.
Cui, P., Zhu, Y. Y., Chen, J., Han, Y. S., and Liu, H. J.: Relationships between antecedent rainfall and debris flows in Jiangjia Ravine, China, in: Debris-Flow Hazards Mitigation: Mechanics, Prediction, and Assessment, edited by: Chen, C. and Major, J., Millpress, Netherlands, 3–10, https://webofscience.clarivate.cn/wos/alldb/summary/c8412688-7797-4f83-adb1-214f3747ca8f-ed3972c7/relevance/1 (last access: 30 May 2024), 2007.
De Paola, F., De Risi, R., Di Crescenzo, G., Giugni, M., Santo, A., and Speranza, G.: Probabilistic Assessment of Debris Flow Peak Discharge by Monte Carlo Simulation, Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 3, A4015002, https://doi.org/10.1061/AJRUA6.0000855, 2017.
De Vita, P.: Fenomeni d'instabilita` delle coperture piroclastiche dei Monti Lattari, di Sarno e di Salerno (Campania) ed analisi degli eventi pluviometrici determinanti, Quad. Geol. Appl., 7, 213–239, 2000.
Donovan, I. P. and Santi, P. M.: A probabilistic approach to post-wildfire debris-flow volume modeling, Landslides, 14, 1345–1360, 2017.
Fiorillo, F. and Wilson, R. C.: Rainfall induced debris flows in pyroclastic deposits, Campania (southern Italy), Eng. Geol., 75, 263–289, 2004.
Gabet, E. J. and Mudd, S. M.: The mobilization of debris flows from shallow landslides, Geomorphology, 1, 207–218, 2006.
Han, Z., Chen, G. Q., Li, Y. G., and He, Y.: Assessing entrainment of bed material in a debris-flow event: a theoretical approach incorporating Monte Carlo method: Assessing Entrainment of Bed Material by Debris Flow, Earth Surf. Proc. Land., 40, 1877–1890, 2015.
Hirschberg, J., Badoux, A., McArdell, B. W., Leonarduzzi, E., and Molnar, P.: Evaluating methods for debris-flow prediction based on rainfall in an Alpine catchment, Nat. Hazards Earth Syst. Sci., 21, 2773–2789, https://doi.org/10.5194/nhess-21-2773-2021, 2021.
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, 523–534, 2018.
Hu, W., Xu, Q., Wang, G. H., van Asch, T. W. J., and Hicher, P. Y.: Sensitivity of the initiation of debris flow to initial soil moisture, Landslides, 12, 1139–1145, 2015.
Huang, C. H.: Critical rainfall for typhoon-induced debris flows in the Western Foothills, Taiwan, Geomorphology, 185, 87–95, 2013.
Hürlimann, M., Coviello, V., Bel, C., Guo, X. J., Berti, M., Graf, C., Hübl, J., Miyata, S., Smith, J. B., and Yin, H. Y.: Debris-flow monitoring and warning, Review and examples, Earth-Sci. Rev., 199, 102981, https://doi.org/10.1016/j.earscirev.2019.102981, 2019.
Iverson, R. M., Reid, M. E., and LaHusen, R. G.: Debris Flow Mobilization from Landslides, Annu. Rev. Earth Pl. Sc., 25, 85–138, 1997.
Jones, R., Thomas, R. E., Peakall, J., and Manville, V.: Rainfall-runoff properties of tephra: Simulated effects of grain-size and antecedent rainfall, Geomorphology, 282, 39–51, 2017.
Kim, S. W., Chun, K. W., Kim, M., Catani, F., Choi, B., and Seo, J.: Effect of antecedent rainfall conditions and their variations on shallow landslide-triggering rainfall thresholds in South Korea, Landslides, 18, 569–582, 2021.
Kohler, M. A. and Linsley, R. K.: Predicting the runoff from Storm Rainfall, US Department of Commerce, Weather Bureau, Washington, D.C., https://www.nrc.gov/docs/ML0819/ML081900279.pdf (last access: 29 May 2024), 1951.
Le Bissonnais, Y., Renaux, B., and Delouche, H.: Interactions between soil properties and moisture content in crust formation, runoff and interrill erosion from tilled loess soils, Catena, 25, 33–46, 1995.
Li, L., Zhang, S. X., Li, S. H., Qiang, Y., Zheng, Z., and Zhao, D. S.: Debris Flow Risk Assessment Method Based on Combination Weight of Probability Analysis, Advances in Civil Engineering, 2021, 1–12, https://doi.org/10.1155/2021/6640614, 2021.
Liu, D. L., Zhang, S. J., Yang, H. J., Zhao, L. Q., Jiang, Y. H., Tang, D., and Leng, X. P.: Application and analysis of debris-flow early warning system in Wenchuan earthquake-affected area, Nat. Hazards Earth Syst. Sci., 16, 483–496, https://doi.org/10.5194/nhess-16-483-2016, 2016.
Liu, X. L., Wang, F., Nawnit, K., Lv, X. F., and Wang, S. J.: Experimental study on debris flow initiation, B. Eng. Geol. Environ., 79, 1565–1580, 2020.
Long, K., Zhang, S. J., Wei, F. Q., Hu, K. H., Zhang, Q., and Luo, Y.: A hydrology-process based method for correlating debris flow density to rainfall parameter and its application on debris flow prediction, J. Hydrol., 589, 125124, https://doi.org/10.1016/j.jhydrol.2020.125124, 2020.
Luk, S. H.: Effect of antecedent soil moisture content on rainwash erosion, Catena, 12, 129–139, 1985.
Marra, F., Destro, E., Nikolopoulos, E. I., Zoccatelli, D., Creutin, J. D., Guzzetti, F., and Borga, M.: Impact of rainfall spatial aggregation on the identification of debris flow occurrence thresholds, Hydrol. Earth Syst. Sci., 21, 4525–4532, https://doi.org/10.5194/hess-21-4525-2017, 2017.
Papa, M. N., Medina, V., Ciervo, F., and Bateman, A.: Derivation of critical rainfall thresholds for shallow landslides as a tool for debris flow early warning systems, Hydrol. Earth Syst. Sci., 17, 4095–4107, https://doi.org/10.5194/hess-17-4095-2013, 2013.
Peres, D. J. and Cancelliere, A.: Derivation and evaluation of landslide-triggering thresholds by a Monte Carlo approach, Hydrol. Earth Syst. Sci., 18, 4913–4931, https://doi.org/10.5194/hess-18-4913-2014, 2014.
Peres, D. J. and Cancelliere, A.: Modeling impacts of climate change on return period of landslide triggering, J. Hydrol., 567, 420–434, 2018.
Richards, L. A.: Capillary condition of liquids in porous mediums, Physics, 1, 318–333, 1931.
Schoener, G. and Stone, M. C.: Monitoring soil moisture at the catchment scale-A novel approach combing antecedent precipitation index and rader-derived rainfall data, J. Hydrol., 589, 125155, https://doi.org/10.1016/j.jhydrol.2020.125155, 2020.
Segoni, S., Rosi, A., Lagomarsino, D., Fanti, R., and Casagli, N.: Brief communication: Using averaged soil moisture estimates to improve the performances of a regional-scale landslide early warning system, Nat. Hazards Earth Syst. Sci., 18, 807–812, https://doi.org/10.5194/nhess-18-807-2018, 2018.
Senthilkumar, V., Chandrasekaran, S. S., and Maji, V. B.: Geotechnical characterization and analysis of rainfall-induced 2009 landslide at Marappalam area of Nilgiris district, Tamil Nadu state, India, Landslides, 14, 1803–1814, 2017.
Tang, H., Mcguire, L. A., Kean, J. W., and Smith, J. B.: The impact of sediment supply on the initiation and magnitude of runoff-generated debris flows, Geophys. Res. Lett., 47, e2020GL087643, https://doi.org/10.1029/2020GL087643, 2020.
Thomas, M. A., Collins, B. D., and Mirus, B. B.: Assessing the feasibility of satellite-based thresholds for hydrologically driven landsliding, Water Resour. Res., 55, 9006–9023, 2019.
Tisdall, A.: Antecedent soil moisture and its relation to infiltration, Aust. J. Agr. Res., 2, 342–348, 1951.
Van Genuchten, M.: A closed form equation for predicting the hydraulic conductivity of unsaturated soils, Soil Sci. Soc. Am. J., 44, 892–898, 1980.
Wei, F. Q., Hu, K. H., Zhang, J., Jiang, Y. H., and Chen, J.: Determination of effective antecedent rainfall for debris flow forecast based on soil moisture content observation in Jiangjia Gully, China, in: Monitoring, Simulation, Prevention and Remediation of dense debris flows II, edited by: DeWrachien, D., Brebbia, C. A., and Lenzi, M. A., WIT Transactions on Engineering Sciences, England, 13–22, https://doi.org/10.2495/DEB080021, 2008.
Yan, Z. Z. and Hong, Z. M.: Using the Monte Carlo method to solve integral equations using a modified control variate, Appl. Math. Comput., 242, 764–777, 2014.
Yang, H. J., Zhang, S. J., Hu, K. H., Wei, F. Q., Wang, K., and Liu, S.: Field observation of debris flow activities in the initiation area of Jiangjia Gully, Yunnan Province, China, J. Mt. Sci., 19, 1602–1617, 2022.
Zeng, Q. L., Yue, Z. Q., Yang, Z. F., and Zhang, X. J.: A case study of long-term field performance of check-dams in mitigation of soil erosion in Jiangjia stream, China, Environ. Geol., 58, 897–911, 2009.
Zhang, S.: JJG, DENS-ID [code], https://pan.baidu.com/disk/main?from=homeFlow#/index?category=all&path=%2F, last access: 28 May 2024.
Zhang, S. J., Xu, C. X., Wei, F. Q., Hu, K. H., 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, 2020.
Zhang, S. J., Yang, H. J., Wei, F. Q., Jiang, Y. H., and Liu, D. L.: A model of debris flow forecast based on the water-soil coupling mechanism, J. Mt. Sci., 25, 757–763, 2014.
Zhang, S. J., Xia, M. Y., Li, L., Yang, H. J., Liu, D. L., and Wei, F. Q.: Quantify the effect of antecedent effective precipitation on rainfall intensity-duration threshold of debris flow, Landslides, 20, 1719–1730, 2023.
Zhao, B. R., Dai, Q., Han, D. W., Dai, H. C., Mao, J. Q., and Zhuo, L.: Probabilistic thresholds for landslides warning by integrating soil moisture conditions with rainfall thresholds, J. Hydrol., 574, 276–287, 2019a.
Zhao, B. R., Dai, Q., Han, D., Dai, H., Mao, J., Zhuo, L., and Rong, G.: Estimation of soil moisture using modified antecedent precipitation index with application in landslide predictions, Landslides, 16, 2381–2393, 2019b.
Zhu, Y. J. and Shao, M. G.: Variability and pattern of surface moisture on a small-scale hillslope in Liudaogou catchment on the northern Loess Plateau of China, Geoderma, 147, 185–191, 2008.
Zhuang, J. Q., Cui, P., Wang, G. H., Chen, X. Q., Iqbal, J., and Guo, X. J.: Rainfall thresholds for the occurrence of debris flows in Jiangjia Gully, Yunnan Province, China, Eng. Geol., 195, 335–346, 2015.
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 %.
Antecedent effective precipitation (AEP) plays an important role in debris flow formation, but...
