Abstract and Applied Analysis

Reservoir Sedimentation Based on Uncertainty Analysis

Farhad Imanshoar, Afshin Jahangirzadeh, Hossein Basser, Shatirah Akib, Babak Kamali, Mohammad Reza M. Tabatabaei, and Masoud Kakouei

Full-text: Open access

Abstract

Reservoir sedimentation can result in loss of much needed reservoir storage capacity, reducing the useful life of dams. Thus, sufficient sediment storage capacity should be provided for the reservoir design stage to ensure that sediment accumulation will not impair the functioning of the reservoir during the useful operational-economic life of the project. However, an important issue to consider when estimating reservoir sedimentation and accumulation is the uncertainty involved in reservoir sedimentation. In this paper, the basic factors influencing the density of sediments deposited in reservoirs are discussed, and uncertainties in reservoir sedimentation have been determined using the Delta method. Further, Kenny Reservoir in the White River Basin in northwestern Colorado was selected to determine the density of deposits in the reservoir and the coefficient of variation. The results of this investigation have indicated that by using the Delta method in the case of Kenny Reservoir, the uncertainty regarding accumulated sediment density, expressed by the coefficient of variation for a period of 50 years of reservoir operation, could be reduced to about 10%. Results of the Delta method suggest an applicable approach for dead storage planning via interfacing with uncertainties associated with reservoir sedimentation.

Article information

Source
Abstr. Appl. Anal., Volume 2014, Special Issue (2013), Article ID 367627, 6 pages.

Dates
First available in Project Euclid: 2 October 2014

Permanent link to this document
https://projecteuclid.org/euclid.aaa/1412277416

Digital Object Identifier
doi:10.1155/2014/367627

Zentralblatt MATH identifier
07022237

Citation

Imanshoar, Farhad; Jahangirzadeh, Afshin; Basser, Hossein; Akib, Shatirah; Kamali, Babak; Tabatabaei, Mohammad Reza M.; Kakouei, Masoud. Reservoir Sedimentation Based on Uncertainty Analysis. Abstr. Appl. Anal. 2014, Special Issue (2013), Article ID 367627, 6 pages. doi:10.1155/2014/367627. https://projecteuclid.org/euclid.aaa/1412277416


Export citation

References

  • F. Imanshoar, Y. Hassanzadeh, M. T. Aalami, and A. Danandeh-mehr, “Uncertainty analysis for determining density of deposits in dams' reservoirs,” Journal of Water and Soil Science, vol. 23, pp. 27–38, 2013 (Persian).
  • United States Bureau of Reclamation (USBR), Design of Small Dams, United States Bureau of Reclamation (USBR), Denver, Colo, USA, 3rd edition, 1987.
  • J. D. Salas and H. Shin, “Uncertainty analysis of reservoir sedimentation,” Journal of Hydraulic Engineering, vol. 125, no. 4, pp. 339–350, 1999.
  • S. W. Fleming, A. Marsh Lavenue, A. H. Aly, and A. Adams, “Practical applications of spectral analysis of hydrologic time series,” Hydrological Processes, vol. 16, no. 2, pp. 565–574, 2002.
  • M. V. Tehrani, J. M. V. Samani, and M. Montaseri, “Uncertainty analysis of reservoir sedimentation using Latin Hypercube sampling and Harr's method: Shahar Chai Dam in Iran,” Journal of Hydrology New Zealand, vol. 47, no. 1, pp. 25–42, 2008.
  • Y. K. Tung and B. C. Yen, Hydrosystems Engineering Uncertainty Analysis, McGraw-Hill, New York, NY, USA, 2005.
  • S. Franceschini and C. W. Tsai, “Assessment of uncertainty sources in water quality modeling in the Niagara River,” Advances in Water Resources, vol. 33, no. 4, pp. 493–503, 2010.
  • O. O. Osidele, W. Zeng, and M. B. Beck, “Coping with uncertainty: a case study in sediment transport and nutrient load analysis,” Journal of Water Resources Planning and Management, vol. 129, no. 4, pp. 345–355, 2003.
  • R. L. Tobin and C. P. Hollowed, “Water quality and sediment transport Characteristics in Kenney reservoir, White river basin,” Northwestern Colorado Report, U.S. Geological Survey, Denver, Colo, USA, 1990.
  • R. I. Strand and E. L. Pemberton, “Reservoir sedimentation,” Technical Guideline for Bureau of Reclamation, U.S. Department of Interior Bureau of Reclamation, Denver, Colo, USA, 1982.
  • G. L. Morris and J. Fan, Reservoir Sedimentation Handbook: Design and Management of Dams, Reservoirs and Watersheds for Sustainable Use, McGraw-Hill, New York, NY, USA, 1997.
  • V. Jothiprakash and V. Garg, “Re-look to conventional techniques for trapping efficiency estimation of a reservoir,” International Journal of Sediment Research, vol. 23, no. 1, pp. 76–84, 2008.
  • C. R. Miller, Determination of the Unit Weight of Sediment for Use in Sediment Volume Computations, U.S. Department of Interior Bureau of Reclamation, Denver, Colo, USA, 1953.
  • J. W. Hall, “Handling uncertainty in the hydroinformatic process,” Journal of Hydroinformatics, vol. 5, pp. 215–232, 2003.
  • J. D. Salas, Analysis and Modelling of Hydrologic Time Series, McGraw-Hill, New York, NY, USA, 1993.
  • J. M. V. Samani, M. Tehrani, and M. Montaseri, “The evaluation of three methods of uncertainty (MCS, LHS and Harr) in dam reservoir sedimentation,” Journal of Engineering and Applied Sciences, vol. 2, pp. 1074–1084, 2007.
  • L. W. Mays, Water Resources Engineering, John Wiley & Sons, New York, NY, USA, 2nd edition, 2005.
  • F. Imanshoar, Y. Hassanzadeh, and M. R. M. Tabatabai, “Analysis of trophic state uncertainty and its Variation: Miyun Reservoir, Beijing, China,” in Proceedings of the 1st International Conference on Dams & Hydropower (ICDHP '12), Tehran, Iran, February 2012.
  • C. B. Resende, C. G. Heckmann, and J. J. Michalek, “Robust design for profit maximization under uncertainty of consumer choice model parameters using Delta method,” in Proceedings of the ASME, 2011 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, Washington, DC, USA, 2011.
  • H. L. Chen, Stochastic characteristics of environmental and hydrologic time series [dissertation], Purdue University, Stillwater, Okla, USA, 1999. \endinput