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Influence of bed roughness parameter in storm surge modeling along the east coast of India
Influence of bed roughness parameter in storm surge modeling along the east coast of India
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Influence of bed roughness parameter in storm surge modeling along the east coast of India
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Influence of bed roughness parameter in storm surge modeling along the east coast of India
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Influence of bed roughness parameter in storm surge modeling along the east coast of India
Influence of bed roughness parameter in storm surge modeling along the east coast of India
Journal Article

Influence of bed roughness parameter in storm surge modeling along the east coast of India

2024
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Overview
The east coast of India is highly prone to devastating winds, torrential rainfall, and storm surges caused by tropical cyclones. The storm surge is affected by ocean basin characteristics involving the width and slope of the continental shelf. The bed roughness plays a major role in surge formation. The east coast of India is characterized by a broader shelf in the north and a narrow shelf in the south. This paper uses a hybrid Finite Volume Method–Finite Element Method based Shallow water equation (SWE) solver to predict the storm surges during different cyclone events, and the roughness parameter Manning’s n is used in bed friction calculations. The bottom friction coefficient parameterization involving bed roughness is used to calibrate the resistance to flow in the numerical model. The calibration exercises are carried out with different values of n for each surge simulations for different cyclones to predict the surface elevation. Different statistical parameters against the measured values are used to analyze the impact of varying n values on predicted surge levels, and the most suitable n value is carefully chosen. The relationship between n and the bed slope is established as an expression, to replace the formulations involving Manning’s n , thereby minimizing the usual computational efforts. The performance of the novel bed friction formulation involving the physical parameter in bed slope is demonstrated through statistical evaluations.