Advertisement

Simulated annealing for calibrating the Manning’s roughness coefficients for general channel networks on a basin scale

  • Tri Dinh Bao OngEmail author
  • Crile Doscher
  • Magdy Mohssen
Original Paper
  • 101 Downloads

Abstract

The practical application of simultaneous solutions to the problem of steady state gradually varied flow in a general channel network depends significantly on the reliability of the estimated Manning roughness coefficients based on the calibration of the flow models against observed data. Manning roughness coefficients are needed for all the cross sections of the channel network. Systematic approaches for the calibration of Manning roughness coefficients for such a flow model are very sparse in the literature. This study proposes simulated annealing as an optimizer to the problem of calibrating Manning’s roughness coefficients for a steady state varied flow in a general channel network and presents its application to a case study in Quangnam basin of Vietnam.

Keywords

Simulated annealing Model calibration Manning’s roughness coefficient General channel network Steady state gradually varied flow Similarity test Quangnam basin 

References

  1. Chaudhry MH (1993) Open-channel flow. Prentice Hall, Englewood CliffsGoogle Scholar
  2. Das A (2004) Parameter estimation for flow in open-channel networks. J Irrig Drain Eng 130(2):160–165.  https://doi.org/10.1061/(ASCE)0733-9437(2004)130:2(160) CrossRefGoogle Scholar
  3. Dougherty DE, Marryott RA (1991) Optimal groundwater management: 1. Simulated annealing. Water Resour Res 27(10):2493–2508.  https://doi.org/10.1029/91WR01468 CrossRefGoogle Scholar
  4. Dréo J, Petrowski A, Siarry P, Taillard E (2006) Metaheuristics for hard optimization: methods and case studies: Springer Science & Business MediaGoogle Scholar
  5. Fread DL, Smith GG (1978) Calibration technique for 1-D unsteady flow models. J Hydr Div ASCE 104(7):1027–1043Google Scholar
  6. Gonzalez-Abril L, Gavilan JM, Morente FV (2014) Three similarity measures between one-dimensional data sets. Revista Colombiana de Estadistica, volume 37(no. 1), pp.77–92Google Scholar
  7. Hameed LK, Ali ST (2013) Estimating of Manning’s roughness coefficient for Hilla River through calibration using HEC-RAS model. Jordan J Civ Eng 7(1)Google Scholar
  8. Kidson R, Richards K, Carling P (2002) Hydraulic model calibration using a modern flood event: the Mae Chaem River, Thailand Proceedings of the PHEFRA Workshop, Barcelona, 16-19 October 2002, pp. 171–176Google Scholar
  9. Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220(4598):671–680.  https://doi.org/10.1126/science.220.4598.671 CrossRefGoogle Scholar
  10. Kumar E (2008) Artificial intelligence: I.K. International Publishing House Pvt. Limited. Retrieved from https://books.google.co.nz/books?id=rNmAY-RcGKYC
  11. Laarhoven VJP, Aarts HE (1987) Simulated annealing: theory and applications (vol. 37): Springer Science & Business MediaGoogle Scholar
  12. Luce CH, Cundy TW (1994) Parameter identification for a runoff model for forest roads water. Resour Res 30(4):1057–1069CrossRefGoogle Scholar
  13. Marryott RA, Dougherty DE, Stollar RL (1993) Optimal groundwater management: 2. Application of simulated annealing to a field-scale contamination site. Water Resour Res 29(4):847–860.  https://doi.org/10.1029/92WR02801 CrossRefGoogle Scholar
  14. Mauldon AD, Karasaki K, Martel SJ, Long JC, Landsfeld M, Mensch A, Vomvoris S (1993) An inverse technique for developing models for fluid flow in fracture systems using simulated annealing. Water Resour Res 29(11):3775–3789.  https://doi.org/10.1029/93WR00664 CrossRefGoogle Scholar
  15. Metropolis N, Rosenbluth AW, Rosenbluth MN, Teller AH, Teller E (1953) Equation of state calculations by fast computing machines. J Chem Phys 21(6):1087–1092.  https://doi.org/10.1063/1.1699114 CrossRefGoogle Scholar
  16. Muleta MK, Nicklow JW (2005) Sensitivity and uncertainty analysis coupled with automatic calibration for a distributed watershed model. J Hydrol 306(2005):127–145.  https://doi.org/10.1016/j.jhydrol.2004.09.005 CrossRefGoogle Scholar
  17. Nabi G, Reddy H, Habib-ur-Rehman (2012) Gradually varied flow computation in series, tree type and looped compound channel networks. Pak J Eng Appl Sci 11:47–59Google Scholar
  18. Parhi PK, Sankhua RN, Roy GP (2012) Calibration of channel roughness for Mahanadi River, (India) using HEC-RAS model. J Water Resour Prot 04(10):847–850CrossRefGoogle Scholar
  19. Picard E (1929) Traité d’analyse. Gauthier-Villars, ParisGoogle Scholar
  20. Powell MJD (1974) Introduction to constrained optimization. In: Gill PE, Murray W (eds) Numerical methods for constrained optimization. Academic Press, London and New YorkGoogle Scholar
  21. Prasuhn AL (1992) Fundamentals of hydraulic engineering. Oxford University Press, New YorkGoogle Scholar
  22. Ramesh R, Datta B, Bhallamudi S, Narayana A (2000) Optimal estimation of roughness in open-channel flows. J Hydraul Eng 126(4):299–303.  https://doi.org/10.1061/(ASCE)0733-9429(2000)126:4(299) CrossRefGoogle Scholar
  23. Reshma T, Reddy KV, Pratap D, Agilan V (2015, 28–29 December 2014). Optimization of Manning’s roughness coefficients for a watershed using multi-objective genetic algorithm. Paper presented at the meeting of the International Conference on Modeling Tools for Sustainable Water Resources Management Department of Civil Engineering, HyderabadGoogle Scholar
  24. Subramanya K (1991) Flow in open channels. Tata McGraw-Hill Publishing Co. Ltd., New DelhiGoogle Scholar
  25. Szymkiewicz R (2010) Numerical modeling in open channel hydraulics.  https://doi.org/10.1007/978-90-481-3674-2 CrossRefGoogle Scholar
  26. Timbadiya PV, Patel PL, Porey PD (2011) Calibration of HEC-RAS model on prediction of flood for lower Tapi River, India. J Water Resour Prot (JWARP) 3(11):805CrossRefGoogle Scholar
  27. Usul N, Turan B (2006) Flood forecasting and analysis within the Ulus Basin, Turkey, using geographic information systems. Nat Hazards 39(2):213–229.  https://doi.org/10.1007/s11069-006-0024-8 CrossRefGoogle Scholar

Copyright information

© Saudi Society for Geosciences 2017

Authors and Affiliations

  • Tri Dinh Bao Ong
    • 1
    Email author
  • Crile Doscher
    • 1
  • Magdy Mohssen
    • 2
  1. 1.Department of Informatics and Enabling Technologies (DIET)Lincoln UniversityChristchurchNew Zealand
  2. 2.Department of Environmental Management (DEM)Lincoln UniversityChristchurchNew Zealand

Personalised recommendations