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fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Zhang, Shaojie; Zhao, Luqiang; Delgado-Tellez, Ricardo; Bao, Hongjun (2018)
Publisher: Copernicus Publications
Languages: English
Types: Article
Subjects: G, GE1-350, Geography. Anthropology. Recreation, QE1-996.5, Environmental technology. Sanitary engineering, Environmental sciences, Geology, TD1-1066
Conventional outputs of physics-based landslide forecasting models are presented as deterministic warnings by calculating the safety factor (Fs) of potentially dangerous slopes. However, these models are highly dependent on variables such as cohesion force and internal friction angle which are affected by a high degree of uncertainty especially at a regional scale, resulting in unacceptable uncertainties of Fs. Under such circumstances, the outputs of physical models are more suitable if presented in the form of landslide probability values. In order to develop such models, a method to link the uncertainty of soil parameter values with landslide probability is devised. This paper proposes the use of Monte Carlo methods to quantitatively express uncertainty by assigning random values to physical variables inside a defined interval. The inequality Fs < 1 is tested for each pixel in n simulations which are integrated in a unique parameter. This parameter links the landslide probability to the uncertainties of soil mechanical parameters and is used to create a physics-based probabilistic forecasting model for rainfall-induced shallow landslides. The prediction ability of this model was tested in a case study, in which simulated forecasting of landslide disasters associated with heavy rainfalls on 9 July 2013 in the Wenchuan earthquake region of Sichuan province, China, was performed. The proposed model successfully forecasted landslides in 159 of the 176 disaster points registered by the geo-environmental monitoring station of Sichuan province. Such testing results indicate that the new model can be operated in a highly efficient way and show more reliable results, attributable to its high prediction accuracy. Accordingly, the new model can be potentially packaged into a forecasting system for shallow landslides providing technological support for the mitigation of these disasters at regional scale.
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    • Aleotti, P.: A warning system for rainfall-induced shallow failures, Eng. Geol., 73, 247-265, 2004.
    • Apip, Takara, K., Yamashiki, Y., Sassa, K., Bagiawan Ibrahim, 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, 2010.
    • Baum, R. L., Savage, W. Z., and Godt, J. W.: TRIGRS-a FORTRAN program for transient rainfall infiltration and grid-based regional slopestability analysis, Virginia, US Geological Survey Open file report, 02-424, 2002.
    • Baum, R. L., Savage, W. Z., and Godt, J. W.: TRIGRS-a FORTRAN program for transient rainfall infiltration and grid-based regional slopestability analysis, Virginia, US Geological Survey Open file report, 2008-1159, 2008.
    • Blondeau, F.: The residual shear strength of some French clays: measurement and application to a natural slope landslide, Geol. Appl. Idrogeol., 8, 125-141, 1973.
    • Caine, N.: The rainfall intensity - duration control of shallow landslides and debris flows, Geogr. Ann. A., 62, 23-27, 1980.
    • Cardinali, M., Galli, M., Guzzetti, F., Ardizzone, F., Reichenbach, P., and Bartoccini, P.: Rainfall induced landslides in December 2004 in south-western Umbria, central Italy: types, extent, damage and risk assessment, Nat. Hazards Earth Syst. Sci., 6, 237- 260, https://doi.org/10.5194/nhess-6-237-2006, 2006.
    • Chang, K., Chiang, S. H., and Lei, F.: Analysing the relationship between typhoon-triggered landslides and critical rainfall conditions, Earth Surf Proc. Land, 33, 1261-1271, 2008.
    • Crosta, G.: Regionalization of rainfall thresholds: an aid to landslide hazard evaluation, Environ. Geol., 35, 131-145, 1998.
    • Crosta, G. B. and Frattini, P.: Rainfall thresholds for triggering soil slips and debris flow, edited by: Mugnai, A., Guzzetti, F., and Roth, G., Mediterranean storms, Proceedings of the 2nd EGS Plinius Conference on Mediterranean Storms, Siena, Italy, 463- 487, 2001.
    • Crosta, G. B. and Frattini, P.: Distributed modelling of shallow landslides triggered by intense rainfall, Nat. Hazards Earth Syst. Sci., 3, 81-93, https://doi.org/10.5194/nhess-3-81-2003, 2003.
    • Cruden, D. M. and Varnes, D. J.: Landslides types and processes, Landslides: investigation and mitigation, Transportation Research Board Special Report 247, edited by: Truner A. K., and Schuster, R. L., National Acadmy Press, Washington, 36- 75, 1996.
    • Cui, P., Yang, K., and Chen, J.: Relationship between occurrence of debris flow and antecedent precipitation: Taking the Jiangjia Gully as an example, China, J. Soil Water Conserv., 1, 11-15, 2003 (in Chinese).
    • Dai, F. C. and Lee, C. F.: A spatiotemporal probabilistic modeling of storm-induced shallow landsliding using aerial photographs and logistic regression, Earth Surf Proc. Land, 25, 527-545, 2003.
    • Davide, T. and David, R.: Estimation of rainfall thresholds triggering shallow landslides for an operational warning system, Landslides, 7, 471-481, 2010.
    • Fredlund, D. G. and Rahardjo, H.: Soil Mechanics for Unsaturated Soils. A Wiley-Interscience Publication, New York, USA, 1993.
    • Gao, K. C., Wei, F. Q., Cui, P., Hu, K. H., Xu, J., and Zhang, G. P.: Probability forecast of regional landslide based on numerical weather forecast, Wuhan University, J. Nat. Sci., 11, 853-858, 2006.
    • Iverson, R. M.: Landslide triggering by rain infiltration, Water Resour. Res., 36, 1897-1910, 2000.
    • Jacob, M., Holm, K., Lange, O., and Schwab, J. W.: Hydrometeorological thresholds for landslide initiation and forest operation shutdowns on the north coast of British Columbia, Landslides, 3, 228-238, 2006.
    • Jia, G. Y., Tian, Y., Liu, Y., and Zhang Y.: A static and dynamic factors-coupled forecasting model of regional rainfall-induced landslides: A case study of Shenzhen, Sci. China Ser. E., 51, 164-175, 2008.
    • Lei, Z. D., Yang, S. X., and Xie, S. C.: Soil water dynamics, Beijing, Tsinghua University, 1988 (in Chinese).
    • Li, W. C., Lee, L. M., Cai, H., Li, H. J., Dai, F. C., and Wang, M. L.: Combined roles of saturated permeability and rainfall characteristics on surficial failure of homogeneous soil slope, Eng. Geol., 153, 105-113, 2013.
    • 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 earthquakeaffected area, Nat. Hazards Earth Syst. Sci., 16, 483-496, https://doi.org/10.5194/nhess-16-483-2016, 2016.
    • Montgomery, D. R. and Dietrich, W. E.: A physically based model for the topographic control on shallow landsliding, Water Resour. Res., 30, 1153-1171, 1994.
    • Montgomery, D. R., Sullivan, K., and Greenberg, M.: Regional test of a model for shallow landsliding, Hydrol. Proc., 12, 943-955, 1998.
    • Montrasio, L., Valentino, R., and Losi, G. L.: Towards a real-time susceptibility assessment of rainfall-induced shallow landslides on a regional scale, Nat. Hazards Earth Syst. Sci., 11, 1927-1947, https://doi.org/10.5194/nhess-11-1927-2011, 2011.
    • Richards, L. A.: Capillary condition of liquids in porous mediums, Physics, 1, 318-333, 1931.
    • Raia, S., Alvioli, M., Rossi, M., Baum, R. L., Godt, J. W., and Guzzetti, F.: Improving predictive power of physically based rainfall-induced shallow landslide models: a probabilistic approach, Geosci. Model Dev., 7, 495-514, https://doi.org/10.5194/gmd-7-495-2014, 2014.
    • 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.
    • Salciarini, D., Godt, J. W., Savage, W. Z., Conversini, P., Baum, R. L., and Michael, J. A.: Modeling regional initiation of rainfallinduced shallow landslides in the eastern Umbria Region of central Italy, Landslides, 3, 181-194, 2006.
    • Schmidt, J., Turek, G., Clark, M. P., Uddstrom, M., and Dymond, J. R.: Probabilistic forecasting of shallow, rainfall-triggered landslides using real-time numerical weather predictions, Nat. Hazards Earth Syst. Sci., 8, 349-357, https://doi.org/10.5194/nhess8-349-2008, 2008.
    • Tang, C.: Activity tendency prediction of rainfall induced landslides and debris flows in the Wenchuan earthquake areas, J. Mountain Sci., 28, 341-349, 2010 (in Chinese).
    • Tsai, T. L. and Chiang, S. J.: Modeling of layered infinite slope failure triggered by rainfall, Environ. Earth Sci., 68, 1429-1434, 2012.
    • Van Genuchten, M.: A closed form equation for predicting the hydraulic conductivity of unsaturated soils, Soil Sci. Soc. Am. J., 44, 892-898, 1980.
    • Varnes, D. J.: Slope movements types and process, Landslides: analysis and control, edited by: Schuster, R. L. and Krizeck, R. J., Nat. Acad. Sci., Washington, D. C., 11-30, 1978.
    • Wei, F. Q., Tang, J. F., Xie, H., and Zhong, D. L.: Debris flow forecast combined regions and valleys and its application, J. Mountain Sci., 22, 321-325, 2004 (in Chinese).
    • Wei, F. Q., Gao, K. C., Cui, P., Hu, K. H., Xu, J., Zhang, G., and Bi, B.: Method of Debris Flow Prediction Based on a Numerical Weather Forecast and Its Application, WIT Trans Ecol Envir., 90, 37-46, doi:10.2495/DEB060041, 2006.
    • Wei, F. Q., Gao, K. C., Jiang, Y. H., Jia, S. W., Cui, P., Xu, J., Zhang, G. P., and Bi, B. G.: GIS-based prediction of debris flows and landslides in Southwestern China, in: Debris-Flow Hazards Mitigation: Mechanics, Prediction, and Assessment, edited by: Chen, C. L. and Major, J. J., Millpress Science Publishers, Rotterdam, 479-490, 2007a.
    • Wei, F. Q., Xu, J., Jiang, Y. H., and Zhang, J.: The system of debris flow prediction with different time and space sacles, J. Mountain Sci., 25, 616-621, 2007b (in Chinese).
    • Wieczorek, G. F. and Glade, T.: Climatic factors influencing occurrence of debris flows, edited by: Jakob, M. and Hungr, O., Debris flow hazards and related phenomena, Berlin, Springer, 325-362, 2005.
    • Wilkinson, P. L., Anderson, M. G., and Lloyd, D. M.: An integrated hydrological model for rain-induced landslides prediction, Earth Surf Proc. Land, 27, 1285-1297, 2002.
    • Wu, W. and Sidle, R. C.: A distributed slope stability model for steep forested basins, Water Resour. Res., 31, 2097-2110, 1995.
    • Xu, J. J.: Application of a distributed hydrological Model of Yangtze River basin, Beijing: Tsinghua University, 2007 (in Chinese).
    • Yang, D. W., Herath, S., and Musiake, K.: A hillslope-based hydrological model using catchment area and width function, Hydrol. Sci. J., 47, 231-243, 2002.
    • Ye, J. H., Xi, Q. X., and Xia, W. R.: Handbook of rock mechanics parameters, Beijing, China Waterpower Press, 1991.
    • 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. Earth Sci., 25, 757-763, 2014a.
    • Zhang, S. J., Wei, F. Q., Liu, D. L., Yang, H. J., and Jiang, Y. H.: A regional-scale method of forecasting debris flow events based on water-soil coupling mechanism, J. Mountain Sci., 11, 1531- 1542, 2014b.
    • Zhang, S. J., Jiang, Y. H., Yang, H. J., and Liu, D. L.: A hydrologyprocess based method for antecedent effect rainfall determination in debris flow forecasting, Adv. Water Sci., 26, 35-43, 2015 (in Chinese).
    • Zhang, S. J., Wei, F. Q., Liu, D. L., and Jiang, Y. H.: Analysis of slope stability based on the limit equilibrium equation and the hydrological simulation, J. Basic Sci. Eng., 24, 1182-1192, 2016 (in Chinese).
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