The change characteristics of the calculated wind wave fields near lateral boundaries with SWAN model

ZHANG Hongsheng; ZHAO Jiachen; LI Penghui; YUE Wenhan; WANG Zhenxiang

doi:10.1007/s13131-016-0800-6

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Article Navigation > Acta Oceanologica Sinica > 2016 > 35(1): 96-105

ZHANG Hongsheng, ZHAO Jiachen, LI Penghui, YUE Wenhan, WANG Zhenxiang. The change characteristics of the calculated wind wave fields near lateral boundaries with SWAN model[J]. Acta Oceanologica Sinica, 2016, 35(1): 96-105. doi: 10.1007/s13131-016-0800-6

Citation:

ZHANG Hongsheng, ZHAO Jiachen, LI Penghui, YUE Wenhan, WANG Zhenxiang. The change characteristics of the calculated wind wave fields near lateral boundaries with SWAN model[J]. Acta Oceanologica Sinica, 2016, 35(1): 96-105. doi: 10.1007/s13131-016-0800-6

Citation:

ZHANG Hongsheng, ZHAO Jiachen, LI Penghui, YUE Wenhan, WANG Zhenxiang. The change characteristics of the calculated wind wave fields near lateral boundaries with SWAN model[J]. Acta Oceanologica Sinica, 2016, 35(1): 96-105. doi: 10.1007/s13131-016-0800-6

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The change characteristics of the calculated wind wave fields near lateral boundaries with SWAN model

doi: 10.1007/s13131-016-0800-6

1.
College of Ocean Science and Engineering, Shanghai Maritime University, Shanghai 201306, China
2.
Yangtze River Estuary Investigation Bureau of Hydrology and Water Resource, Yangtze River Water Resource Commission, Shanghai 200136, China

Received Date: 2015-02-13
Rev Recd Date: 2015-04-15

Abstract

Abstract

Since the wind wave model Simulating Waves Nearshore (SWAN) cannot effectively simulate the wave fields near the lateral boundaries, the change characteristics and the distortion ranges of calculated wave factors including wave heights, periods, directions, and lengths near the lateral boundaries of calculation domain are carefully studied in the case of different water depths and wind speeds respectively. The calculation results show that the effects of the variety of water depth and wind speed on the modeled different wave factors near the lateral boundaries are different. In the case of a certain wind speed, the greater the water depth is, the greater the distortion range is. In the case of a certain water depth, the distortion ranges defined by the relative errors of wave heights, periods, and lengths are different from those defined by the absolute errors of the corresponding wave factors. Moreover, the distortion ranges defined by the relative errors decrease with the increase of wind speed; whereas the distortion ranges defined by the absolute errors change a little with the variety of wind speed. The distortion range of wave direction decreases with the increase of wind speed. The calculated wave factors near the lateral boundaries with the SWAN model in the actual physical areas, such as Lake Taihu and Lake Dianshan considered in this study, are indeed distorted if the calculation domains are not enlarged on the basis of actual physical areas. Therefore, when SWAN is employed to calculate the wind wave fields near the shorelines of sea or inland lakes, the appropriate approaches must be adopted to reduce the calculation errors.
- SWAN model,
- wave factor,
- change characteristic,
- distortion range,
- water depth,
- wind speed,
- lateral boundary

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References

Booij N, Ris R C, Holthuijsen L H. 1999. A third-generation wave model for coastal regions: 1. model description and validation. Journal of Geophysical Research, 104(C4): 7649-7666

Bottema M, van Vledder G P. 2009. A ten-year data set for fetch-and depth-limited wave growth. Coastal Engineering, 56(6): 703-725

Gelci R, Cazalé H, Vassal J. 1956. Utilization des diagrammes de propagation à la prévision énergéltique de la houle. Info Bull (in French), 8(4): 160-179

Gorrell L, Raubenheimer B, Elgar S, et al. 2011. SWAN predictions of waves observed in shallow water onshore of complex bathymetry. Coastal Engineering, 58(6): 510-516 Holthuijsen L H, Herman A, Booij N. 2003. Phase-decoupled refraction- diffraction for spectral wave models. Coastal Engineering, 49(4): 291-305

Hsu T W, Ou S H, Liau J M. 2005. Hindcasting nearshore wind waves using a FEM code for SWAN. Coastal Engineering, 52(2): 177-195

Jia Xiao, Pan Junning, Niclasen B. 2010. Improvement and validation of wind energy input in SWAN model. Journal of Hohai University (Natural Sciences) (in Chinese), 38(5): 585-591

Lin Weiqi, Sanford L P, Suttles S E. 2002. Wave measurement and modeling in Chesapeake Bay. Continental Shelf Research, 22(18-19): 2673-2686

Moeini M H, Etemad-Shahidi A. 2009. Wave parameter hindcasting in a lake using the SWAN model. Scientia Iranica, Transaction A: Civil Engineering, 16(2): 156-164

Ris R C, Holthuijsen L, Booij N. 1999. A third-generation wave model for coastal regions, 2. Verification. Journal of Geophysical Research, 104(C4): 7667-7681

Rogers W E, Kaihatu J M, Hsu L, et al. 2007. Forecasting and hindcasting waves with the SWAN model in the Southern California Bight. Coastal Engineering, 54(1): 1-15

Rusu E, Goncalves M, Soares C G. 2011. Evaluation of the wave transformation in an open bay with two spectral models. Ocean Engineering, 38(16): 1763-1781

Shi J Z, Luther Mark E, Meyers S. 2006. Modelling of wind wave-induced bottom processes during the slack water periods in Tampa Bay, Florida. International Journal for Numerical Methods in Fluids, 52(11): 1277-1292

Signell R P, Carniel S, Cavaleri L, et al. 2005. Assessment of wind quality for oceanographic modelling in semi-enclosed basins. Journal of Marine Systems, 53 (4): 217-233

Smith G A, Babanin A V, Riedel P, et al. 2011. Introduction of a new friction routine into the SWAN model that evaluates roughness due to bedform and sediment size changes. Coastal Engineering, 58(4): 317-326

The SWAMP Group. 1985. Ocean Wave Modeling. New York: Plenum The SWAN Team. 2013. SWAN Technical Documentation. The Netherlands: Delft University of Technology The SWIM Group. 1985. A shallow water intercomparison of three numerical wave prediction models (Swim). Quarterly Journal of the Royal Meteorological Society, 111(470): 1087-1112

The WAMDI Group. 1988. The WAM model-A third generation ocean wave prediction model. Journal of Physical Oceanography, 18: 1775-1810

Tolman H L. 1991. A third-generation model for wind waves on slowly varying, unsteady, and inhomogeneous depths and currents. Journal of Physical Oceanography, 21(6): 782-797

van der Westhuysen A J, Zijlema M, Battjes J A. 2007. Nonlinear saturation- based whitecapping dissipation in SWAN for deep and shallow water. Coastal Engineering, 54(2): 151-170

Xu Fumin, Zhang Changkuan, Mao Lihua, et al. 2000. Application of a numerical model for shallow water waves. Journal of Hydrodynamics (in Chinese), 15(4): 429-434

Zhang Hongsheng, Gu Junbo, Wang Hailong, et al. 2013. Simulating wind wave field near the Pearl River Estuary with SWAN nested in WAVEWATCH. Journal of Tropical Oceanography (in Chinese), 32(1): 8-17

Zhang Hongsheng, Zhou Enxian, Dai Su, et al. 2016. Comparison of the calculated and measured wave heights in Inland Lakes. Journal of Coastal Research, 32(3) (Being Printed) Zijlema M. 2010. Computation of wind-wave spectra in coastal waters with SWAN on unstructured grids. Coastal Engineering, 57(3): 267-277

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