Predicting movable bed roughness in coastal waters
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Madsen_Predicting movable.pdf
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Author(s)
Humbyrd, Chelsea Joy
Madsen, Ole S.
Date Issued
2010
Journal
Proceedings of 32nd Conference on Coastal Engineering
Publisher
Coastal Engineering Research Council
Citation
Humbyrd, Chelsea Joy, and Ole S. Madsen. "Predicting Movable Roughness in Coastal Waters." Proceedings of 32nd Conference on Coastal Engineering 32 (2010).
Version
Author's final manuscript
Abstract
Accurately predicting movable bed roughness is essential to the analyses of transport processes, but when the bottom is rippled, as it commonly is in the coastal environment, characterizing the roughness is less straightforward than when the bottom is flat. The common method of predicting roughness, while effective, unnecessarily predicts ripple
geometry and requires a model-dependent factor, which varies widely, relating ripple geometry and bottom roughness. We have therefore developed an alternative, more direct method of predicting bed roughness in the ripple regime: the wave energy dissipation factor is predicted from flow and sediment information and then any desired
theoretical friction factor model is used to back-calculate the roughness. This paper describes the common and proposed methods of predicting roughness and presents results of preliminary testing of the methods with field data. Both methods adequately predict current velocities in wave-current field flows, with the proposed method yielding the
smaller RMS-error of 3.1 cm/s. Remaining questions concerning the appropriate near-bottom orbital velocity required to describe field conditions must be resolved when additional field data becomes available.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Parsons Laboratory for Environmental Science and Engineering (Massachusetts Institute of Technology)
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Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
http://journals.tdl.org/icce/index.php/icce/article/view/1010/pdf_157
