Hydrophysics

Hydrophysics

Improving Wave Simulation in a Semi-Enclosed Bay Using ERA5 Wind Field Correction in the SWAN Model: A Case Study of Botany Bay

Document Type : Original Article

Authors
Hosnieh Ghaemi Bajgan 1
Maryam Rahbani 2
1 Department of Marine and Ocean Science, Faculty of Marine Science and Technology, University of Hormozgan, Bandar Abbas, Iran
2 Faculty of Marine Science and Technology, Hormozgan University, Bandar Abbas, Iran
Abstract
Accurate wave simulation in semi-enclosed, shallow-water environments remains challenging due to hydrodynamic complexity and uncertainties in wind forcing data. This study evaluates the performance of the third-generation SWAN model in simulating the wave field in the semi-enclosed Botany Bay, with a focus on improving ERA5 wind data and calibrating key physical parameters of the model. ERA5 wind data were first validated against observations from a meteorological station and then corrected using several bias adjustment methods, including linear regression, speed–direction correction, quantile mapping, and machine learning algorithms. The corrected wind fields were subsequently used as input to the SWAN model. Model sensitivity was examined with respect to three primary source term packages (KOMEN, WST, and ST6), considering different combinations of wind input, whitecapping parameterization, bottom friction, and depth-induced breaking. Model performance was assessed using standard statistical metrics and diagnostic tools, including Taylor diagrams, probability density distributions, and Q–Q plots, across four coastal stations with varying hydrodynamic conditions. The results show that the WST package performs best at more exposed stations influenced by swell, while at more sheltered and shallow locations, targeted calibration of whitecapping parameters and reduction of swell energy contribution in the KOMEN and ST6 packages significantly improve model performance. Overall, the findings demonstrate that combining ERA5 wind correction—particularly using machine learning approaches—with targeted calibration of SWAN physical parameters substantially enhances wave simulation accuracy in semi-enclosed environments. Moreover, applying a uniform model configuration across the entire bay can lead to systematic errors in wave energy estimation.
Keywords
waves
Semi enclosed bay
SWAN
ERA5 wind
Subjects
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  • Receive Date 03 January 2026
  • Revise Date 05 February 2026
  • Accept Date 01 April 2026