Dynamic Analysis and Hazard Assessment of Debris Flows in Donghaolitaogao

Authors

  • Zijian Chen College of Construction Engineering, Jilin University, Changchun 130026, Jilin, China
  • Shengyuan Song College of Construction Engineering, Jilin University, Changchun 130026, Jilin, China
  • Baotian Li China Railway Third Bureau Group Sixth Engineering Co., Ltd, Jinzhong 030600, Shanxi, China
  • Ze Yang College of Construction Engineering, Jilin University, Changchun 130026, Jilin, China
  • Muye Ma College of Construction Engineering, Jilin University, Changchun 130026, Jilin, China

DOI:

https://doi.org/10.53469/jrse.2024.06(10).06

Keywords:

Dynamic analysis of debris flow, Hazard assessment, FLO-2D

Abstract

Utilizing the FLO-2D software, the motion processes of debris flows in Donghaolitaogao under 20-year, 50-year, and 100-year return periods of rainfall are analyzed, revealing that as the rainfall return period increases, the debris flow velocity, accumulation depth, and accumulation area all significantly expand. Specifically, under the 20-year, 50-year, and 100-year rainfall conditions, the maximum debris flow velocities are 1.85 m/s, 1.95 m/s, and 1.99 m/s, respectively, while the maximum accumulation depths are 1.31 m, 1.33 m, and 1.35 m, and the total accumulation areas are 27,267.8 m2, 31,500.6 m2, and 33,901.3 m2, respectively. Using the depth of debris flow and the product of debris flow depth and velocity as evaluation indicators, the debris flow hazard assessment indicates that the Donghaolitaogao debris flow is primarily characterized by low- and medium-risk areas, with high-risk areas scattered sporadically along the central part of the channel. Moreover, as the rainfall return period increases, the area of high-risk zones continues to expand, gradually accounting for a larger proportion of the total hazard zone.

References

Chen HX, Zhang LM, Gao L, et al. Simulation of interactions among multiple debris flows. Landslides. 2017;14(2):595-615. doi:10.1007/s10346-016-0710-x

Blackwelder E. Mudflow as a Geologic Agent in Semiarid Mountains. Geological Society of America Bulletin. 1928; 39(2): 465-484. doi:10.1130/ GSAB-39- 465

Breiman L. Random Forests. Machine Learning. 2001; 45(1):5-32. doi:10.1023/A:1010933404324

Experiments on a gravity-free dispersion of large solid spheres in a Newtonian fluid under shear. Proc R Soc Lond A. 1954;225(1160):49-63. doi:10.1098/rspa.1954. 0186

Gabet EJ, Mudd SM. The mobilization of debris flows from shallow landslides. Geomorphology. 2006; 74(1-4): 207-218. doi:10.1016/j.geomorph.2005.08.013

Federico F, Cesali C. An energy-based approach to predict debris flow mobility and analyze empirical relationships. Can Geotech J. 2015;52(12):2113-2133. doi:10.1139/cgj-2015-0107

Takahashi T. Mechanics-Based Approach Toward the Mitigation of Debris Flow Disasters. In: Sassa K, Canuti P, eds. Landslides – Disaster Risk Reduction. Springer Berlin Heidelberg; 2009:89-113. doi:10.1007/978-3-540 -69970-5_5

O’Brien JS, Julien PY, Fullerton WT. Two‐Dimensional Water Flood and Mudflow Simulation. J Hydraul Eng. 1993;119(2):244-261. doi:10.1061/(ASCE)0733-9429 (1993)119:2(244)

Savage SB, Hutter K. The dynamics of avalanches of granular materials from initiation to runout. Part I: Analysis. Acta Mechanica. 1991;86(1-4):201-223. doi: 10.1007/BF01175958

Brufau P, Garcia-Navarro P, Ghilardi P, Natale L, Savi F. 1D Mathematical modelling of debris flow. Journal of Hydraulic Research. 2000;38(6):435-446. doi:10.1080/ 00221680009498297

Iverson RM, Denlinger RP. Flow of variably fluidized granular masses across three‐dimensional terrain: 1. Coulomb mixture theory. J Geophys Res. 2001; 106(B1): 537-552. doi:10.1029/2000JB900329

Bertolo P, Wieczorek GF. Calibration of numerical models for small debris flows in Yosemite Valley, California, USA. Nat Hazards Earth Syst Sci. 2005; 5(6):993-1001. doi:10.5194/nhess-5-993-2005

Zhao M, Chen J, Song S, et al. Proposition of UAV multi-angle nap-of-the-object image acquisition framework based on a quality evaluation system for a 3D real scene model of a high-steep rock slope. International Journal of Applied Earth Observation and Geoinformation. 2023;125:103558. doi:10.1016/ j.jag. 2023.103558

Song Shengyuan, Wang Qing, Pan Yuzhen, et al. Landslide Risk Assessment Based on Catastrophe Theory [J]. Rock and Soil Mechanics, 2014, 35(S2): 422-428. doi: 10.16285/j.rsm.2014.s2.015

Song Shengyuan, Pan Yuzhen, Chen Jianping, et al. Debris Flow Risk Assessment Along Reservoir Banks Based on Connection Expectation: A Case Study of Wudongde Reservoir Area [J]. Journal of Engineering Geology, 2015, 23(04): 719-724. doi: 10.13544/j.cnki.jeg.2015.04.020.

D’Agostino V, Tecca PR. Some considerations on the application of the FLO-2D model for debris flow hazard assessment. In: Monitoring, Simulation, Prevention and Remediation of Dense and Debris Flows. Vol 1. WIT Press; 2006:159-170. doi:10.2495/DEB060161

Downloads

Published

2024-10-30

How to Cite

Chen, Z., Song, S., Li, B., Yang, Z., & Ma, M. (2024). Dynamic Analysis and Hazard Assessment of Debris Flows in Donghaolitaogao. Journal of Research in Science and Engineering, 6(10), 22–30. https://doi.org/10.53469/jrse.2024.06(10).06