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Field Investigation and Numerical Simulation of Wind-Wave Interaction at the Middle-Sized Inland Reservoirs

  • G. A. Baydakov
  • A. M. Kuznetsova
  • V. V. Papko
  • A. A. Kandaurov
  • M. I. Vdovin
  • D. A. Sergeev
  • Yu. I. Troitskaya
Conference paper
Part of the Springer Geology book series (SPRINGERGEOL)

Abstract

An attempt is made to apply the modern methods of surface wave simulation developed for oceanic conditions to the modeling of waves in medium-size inland reservoirs (10–100 km). The results of field measurements of wind speed and waves are described, and on their basis the parameterization \( C_{D} \left( {U_{10} } \right) \) is proposed. WAVEWATCH III spectral wave model was adapted to the conditions of a medium-size inland reservoir. The simulated data are compared with the field data. The use of the new parameterization \( C_{D} \left( {U_{10} } \right) \) allowed reducing the values of the wind wave growth rate that improved consistency in data from the field experiment and numerical modeling concerning the height of significant waves. Further steps towards improving the quality of prediction of the adapted WAVEWATCH III model are discussed.

Keywords

Field experiment Numerical simulation Wind-wave interaction WAVEWATCH III 

Notes

Acknowledgments

The research was supported by the Russian Foundation for Basic Research (grants 17-05-41117 and 15-45-02580). The field experiments were supported by the Russian Scientific Foundation (grant 15-17-20009).

References

  1. 1.
    Tolman H.L., WAVEWATCH III Development Group: User Manual and System Documentation of WAVEWATCH III Version 4.18. Environmental Modeling Center, Marine Modeling and Analysis Branch (2014)Google Scholar
  2. 2.
    Poddubnyi, S.A., Sukhova, E.V.: Modeling the Effects of Hydrodynamic and Anthropogenic Factors on the Distribution of Hydrobionts in Reservoirs. User’s Manual. Rybinskii Dom Pechati, Rybinsk (2002). (in Russian)Google Scholar
  3. 3.
    Sutyrina, E.N.: Determination of Wave Characteristics in the Bratsk Reservoir. Izvestiya Irkutskogo Gosudarstvennogo Universiteta, vol. 2, no. 4 (2011). (in Russian)Google Scholar
  4. 4.
    Newton-Matza, M.: Disasters and Tragic Events: An Encyclopedia of Catastrophes in American History. ABC-CLIO, Santa Barbara (2014)Google Scholar
  5. 5.
    Alves, J.-H.G.M., Chawla, A., Tolman, H.L., et al.: The great lakes wave model at NOAA/NCEP: challenges and future developments. In: 12th International Workshop on Wave Hindcasting and Forecasting, Kohala Coast, Hawaii (2011)Google Scholar
  6. 6.
    Alves, J.-H.G.M., Chawla, A., Tolman, H.L., et al.: The operational implementation of a great lakes wave forecasting system at NOAA/NCEP. Weather Forecast. 29, 1473–1497 (2014)ADSCrossRefGoogle Scholar
  7. 7.
    NWW3 Product Viewer. http://polar.ncep.noaa.gov/waves/viewer.shtml7-glw-latest-hs-grl. Accessed 27 Nov 2017
  8. 8.
    SWAN Team: SWAN - User Manual. Delft University of Technology, Environmental Fluid Mechanics Section (2006)Google Scholar
  9. 9.
    Lopatoukhin, L.J., Boukhanovsky, A.V., Chernyshova, E.S., Ivanov, S.V.: Hindcasting of wind and wave climate of seas around Russia. In: Proceedings of the 8th International Workshop on Waves Hindcasting and Forecasting, North Shore, Oahu, Hawaii (2004)Google Scholar
  10. 10.
    Gunter, H., Hasselmann, S., Janssen, P.A.E.M.: The WAM model cycle 4. Technical report no. 4. DKRZ WAM4 Model Documentation, Hamburg (1992)Google Scholar
  11. 11.
    Hesser, T.J., Cialone, M.A., Anderson, M.E.: Lake St. Clair: Storm Wave and Water Level Modeling. The US Army Research and Development Center (ERDC) (2013)Google Scholar
  12. 12.
    Atakturk, S.S., Katsaros, K.B.: Wind stress and surface waves observed on lake Washington. J. Phys. Oceanogr. 29, 633–650 (1999)ADSCrossRefGoogle Scholar
  13. 13.
    Babanin, A.V., Makin, V.K.: Effects of wind trend and gustiness on the sea drag: lake George Study. J. Geophys. Res. 113, C02015 (2008)ADSCrossRefGoogle Scholar
  14. 14.
    Miles, J.W.: On the generation of surface waves by shear flows. J. Fluid Mech. 3(2), 185–204 (1957)ADSMathSciNetCrossRefzbMATHGoogle Scholar
  15. 15.
    Weber, R.O.: Remarks on the definition and estimation of friction velocity. Bound. Layer Meteorol. 93, 197–209 (1999)ADSCrossRefGoogle Scholar
  16. 16.
    Setton, O.G.: Micrometeorology. Gidrometeoizdat, Leningrad (1958). (Transl. from Engl.)Google Scholar
  17. 17.
    Zakharov, V.E.: On the domination of nonlinear wave interaction in the energy balance of wind-driven sea. In: Proceedings of 11th Wave Workshop, Halifax, Canada (2009)Google Scholar
  18. 18.
    Komen, G.L., Hasselmann, S., Hasselmann, K.: On the existence of a fully developed wind-sea spectrum. J. Phys. Oceanogr. 8(14), 1271–1285 (1984)ADSCrossRefGoogle Scholar
  19. 19.
    Snyder, R.L., Dobson, F.W., Elliott, J.A., Long, R.B.: Array measurements of atmospheric pressure fluctuations above surface gravity waves. J. Fluid Mech. 102, 1–59 (1981)ADSCrossRefGoogle Scholar
  20. 20.
    Wu, J.: Wind-stress coefficients over sea surface from breeze to hurricane. J. Geophys. Res. 87(C12), 9704–9706 (1982)ADSMathSciNetCrossRefGoogle Scholar
  21. 21.
    Troitskaya, Y.I., Sergeev, D.A., Kandaurov, A.A., et al.: Laboratory and theoretical modeling of air-sea momentum transfer under severe wind conditions. J. Geophys. Res. 117(C11), C00J21 (2012)Google Scholar
  22. 22.
    Donelan, M.A., Drennan, W.M., Magnusson, A.K.: Nonstationary analysis of the directional properties of propagating waves. J. Phys. Oceanogr. 26(9), 1901–1914 (1996)ADSCrossRefGoogle Scholar
  23. 23.
    Brooke, B.T.: Shearing flow over a wavy boundary. J. Fluid Mech. 6, 161–205 (1959)ADSMathSciNetCrossRefGoogle Scholar
  24. 24.
    Belcher, S.E., Hunt, J.C.R.: Turbulent shear flow over slowly moving waves. J. Fluid Mech. 251, 109–148 (1993)ADSMathSciNetCrossRefzbMATHGoogle Scholar
  25. 25.
    Fairall, C.W., Bradley, E.F., Hare, J.E., et al.: Bulk parameterization of air-sea fluxes: updates and verification for the COARE algorithm. J. Clim. 4(16), 571–591 (2003)ADSCrossRefGoogle Scholar
  26. 26.
    Hasselmann, S., Hasselmann, K.: Computations and parameterizations of the nonlinear energy transfer in a gravity-wave spectrum. Part I: a new method for efficient computations of the exact nonlinear transfer integral. J. Phys. Oceanogr. 15, 1369–1377 (1985)ADSCrossRefGoogle Scholar
  27. 27.
    Hasselmann, S., Hasselmann, K., Allender, J.H., Barnett, T.P.: Computations and parameterizations of the nonlinear energy transfer in a gravity-wave spectrum. Part II: parameterizations of nonlinear energy transfer for application in wave models. J. Phys. Oceanogr. 15, 1378–1391 (1985)ADSCrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute of Applied PhysicsRussian Academy of SciencesNizhny NovgorodRussia

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