Abstract
Debris flows, often the result of environmental degradation in mountainous areas, can be an extreme geological catastrophe. The concept of building detention dams to control debris flows has emerged after numerous deaths and huge economic losses have accumulated due to the destruction of infrastructure. Detention dams are well known for their efficient flow control and relatively low installation cost. However, their efficiency in decreasing peak flow is adversely affected by sedimentation, which not only decreases the effective lifetime of dams but also causes obstruction of outlets. In this research, the capability of GSTARS3.0 (Generalized Sediment Transport model for Alluvial River Simulation) was evaluated for a semi-three-dimensional simulation of sedimentation and flow routing in the reservoirs of two different kinds of detention dams: a classic detention dam and a slit dam. Sediment transport, scour, and deposition processes were simulated and calibrated along an experimental flume that represented the reservoirs of the detention dams to give a semi-three-dimensional variation of the bed geometry after debris flow events. Finally, models were applied to the Mojen River, Iran, as a real case. The model results convincingly show the capability of the GSTARS3.0 model to simulate sedimentation in reservoirs and the superiority of slit dams in controlling debris flow.
Similar content being viewed by others
References
Altunkaynak A (2009) Sediment load prediction by genetic algorithms. Adv Eng Softw 40:928–934
Banihabib ME, Mokhtari A (2012) Numerical Simulation of Sedimentation in Detention Basins due to a High Concentrated Flow. Am J Sci Res 48
Bertolo P, Wieczorek GF (2005) Calibration of numerical models for small debris flows in Yosemite Valley, California, USA. Nat Hazards and Earth Syst Sci 5:993–1001
Brufau P, Garcia-Navarro P, Ghilardi P, Natale L, Savi F (2000) 1D mathematical modelling of debris flow. J Hydraul Res 38:435–446
Cannon SH, Kirkham RM, Parise M (2001a) Wildfire-related debris-flow initiation processes, Storm King Mountain, Colorado. Geomorphology 39:171–188
Cannon SH, Bigio ER, Mine E (2001b) A process for fire-related debris flow initiation, Cerro Grande fire, New Mexico. Hydrol Process 15:3011–3023
Chang TC, Wang ZY, Chien YH (2010) Hazard assessment model for debris flow prediction. Environ Earth Sci 60(8):1619–1630
Chen JC (2011) Variability of impact of earthquake on debris-flow triggering conditions: case study of Chen-Yu-Lan watershed, Taiwan. Environ Earth Sci 64(7):1787–1794
Cigizoglu HK, Alp M (2006) Generalized regression neural network in modelling river sediment yield. Adv Eng Softw 37:63–68
Coussot P, Meunier M (1996) Recognition, classification and mechanical description of debris flows. Earth-Sci Rev 40:209–227
Crosta GB, Dal Negro P (2003) Observations and modelling of soil slip-debris flow initiation processes in pyroclastic deposits: the Sarno 1998 event. Nat Hazards and Earth Syst Sci 3:53–69
Elkadiri R, Sultan M, Youssef AM, Elbayoumi T, Chase R, Bulkhi AB, Al-Katheeri MM (2014) A remote sensing-based approach for debris-flow susceptibility assessment using artificial neural networks and logistic regression modeling. IEEE J Sel Top Appl Earth Obs Remote Sens. doi:10.1109/JSTARS.2014.2337273
Ghilardi P, Natale L, Savi F (2001) Modeling debris-flow propagation and deposition. Hys Chem Earth, Part C 26(9):651–656
Glover DM, Jenkins WJ, Doney SC (2008) Least squares and regression techniques, goodness of fit and tests, non-linear least squares techniques. Woods Hole Oceanographic Institute, Woods Hole
Goings D, Lerner BKL, Wilmoth Lerner B (2004) The Gale encyclopedia of science (Web), 3rd edn. Gale, Detroit, pp 1149–1152
Han Q (1980) A study on the non-equilibrium transportation of suspended load. In: Proceedings of the International Symposium, On river sedimentation, Beijing, China, pp 793–802 (in Chinese)
Hashimoto H, Park K, Hirano M (2000) Numerical simulation of small-discharge debris-flow at Mt. Unzendake Volcano, Japan. In: Proceedings of the Second International Conference on Debris-Flow Hazards Mitigation, Taipei, Taiwan, pp 177–184
Hassan-Esfahani L, Banihabib ME, Hassanzadeh Y (2008) Evaluation of GSTARS3.0 model for simulation of sedimentation in detention basins (Master’s thesis). Retrieved from ProQuest Dissertations and Theses. University of Tabriz, Iran, p 108
Huang J, Greimann B, Yang C (2004) Development and validation of GSTARS3.0-1D, a general sediment transport model for Alluvial River simulation—one dimensional. In: Critical transitions in water and environmental resources management. pp 1–9
Hui-Pang L (2003) Design of slit dams for controlling stony debris flows. Int J of Sediment Res 18(1):74–87
Innes JL (1983) Debris flows. Prog Phys Geog 7(4):469–501
Iverson RM (1997) The physics of debris flows. Rev of Geophysics 35:245–296
Jaafari A, Najafi A, Pourghasemi HR, Rezaeian J, Sattarian A (2013) GIS-based frequency ratio and index of entropy models for landslide susceptibility assessment in the Caspian forest, northern Iran. Int J Environ Sci Technol. doi:10.1007/s13762-013-0464-0
Johnson KA, Sitar N (1990) Hydrologic conditions leading to debris-flow initiation. Can Geotech J 27:789–801
Kaki T (1954) The experimental research for mud-flow. J Jpn Soc of Eros Control Eng 19:1–6 (in Japanese)
Klenov VI (2000) 2-D debris-flow simulation. In: Proceedings of the Second International Conference on Debris-Flow Hazards Mitigation, Taipei, Taiwan. pp 547–552
Koide H (1955) Landslide in Japan. Toyokeizai News Press, Tokyo (in Japanese)
Liang WJ, Zhuang DF, Jiang D, Pan JJ, Ren HY (2012) Assessment of debris flow hazards using a Bayesian Network. Geomorphology 171–172:94–100
Lin J, Chen C, Peng C (2012) Potential hazard analysis and risk assessment of debris flow by fuzzy modeling. Nat Hazards 64:273–282
Luna BQ, Blahut J, Camera C, Van Westen C, Apuani T, Jetten V, Sterlacchini S (2014) Physically based dynamic run-out modelling for quantitative debris flow risk assessment: a case study in Tresenda, northern Italy. Environ Earth Sci 72(3):645–661
Ni HY (2014) Experimental study on initiation of gully-type debris flow based on artificial rainfall and channel runoff. Environ Earth Sci, pp 1–15 (published online)
Sattari MT, Apaydin H, Ozturk F (2012) Flow estimations for the Sohu Stream using artificial neural networks. Environ Earth Sci 66(7):2031–2045
Yang CT, Simoes, FJM (2002) User’s manual for GSTARS3.03 (Generalized Sediment Transport model for Alluvial River Simulation version 3.0). US Department of the Interior Bureau of Reclamation Technical Service Center Denver, Colorado
Takahashi T (2009) A review of Japanese debris flow research. Int J Eros Control Eng 2(1):1–14
Tang CL, Hu JC, Lin ML, Yuan RM, Cheng CC (2013) The mechanism of the 1941 Tsaoling landslide, Taiwan: insight from a 2D discrete element simulation. Environ Earth Sci 70:1005–1019
Tani I (1968) On debris flow (Yamatsunami). Water Science 60:106–126 (in Japanese)
Tie YB, Xu RG, Ba RJ (2014) The formation of runoff-generated debris flow in Southwestern of China: take Gangou as an example. Environ Earth Sci 72(5):1479–1490
Turconi L, De SK, Demurtas F, Demurtas L, Pendugiu B, Tropeano D, Savio G (2013) An analysis of debris-flow events in the Sardinia Island (Thyrrenian Sea, Italy). Environ Earth Sci 69(5):1509–1521
USGS (2014) Geologic Hazards Science Center. http://geohazards.cr.usgs.gov/. Accessed 11 Jul 2014
Wu JH, Chen CH (2011) Application of DDA to simulate characteristics of the Tsaoling Landslide. Comput Geotech 38(5):741–750
Xu FG, Yang XG, Zhou JW (2014) An empirical approach for evaluation of the potential of debris flow occurrence in mountainous areas. Environ Earth Sci 71(7):2979–2988
Yang CT (1996) Sediment transport: theory and practice. McGraw-Hill Companies, New York, p 2003 (reprint by Krieger Publishing Company, Malabar, FL, 2003)
Yang CT (2008) GSTARS3.0 Computer models and sedimentation control in surface water systems. The 3rd International Conference on Water Resources and Arid Environments and the 1st Arab Water Forum. URL:http://faculty.ksu.edu.sa/72005/Papers%20of%20Interest%20Water/GSTARS%20Computer%20Models%20and%20Sedimentation%20Control%20in%20Surface%20Water.pdf
Yang X, Lu XX (2014) Estimate of cumulative sediment trapping by multiple reservoirs in large river basins: an example of the Yangtze River basin. Geomorphology. doi:10.1016/j.geomorph.2014.01.014. URL:http://www.engr.colostate.edu/ce/facultystaff/yang/gstars.html
Yuanfan T (2007) A debris-flow simulation model for the evaluation of protection structures. J Mt Sci 4(3):193–202
Acknowledgments
The authors express their appreciation to the developer of GSTARS3.0. We appreciate the joint support of Utah State University and the University of Tehran.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Hassan-Esfahani, L., Banihabib, M.E. The impact of slit and detention dams on debris flow control using GSTARS 3.0. Environ Earth Sci 75, 328 (2016). https://doi.org/10.1007/s12665-015-5183-z
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s12665-015-5183-z