Short communication: Multiscalar roughness length decomposition in fluvial systems using a transform-roughness correlation (TRC) approach

David L. Adams*, Andrea Zampiron

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


In natural open-channel flows over complex surfaces, a wide range of superimposed roughness elements may contribute to flow resistance. Gravel-bed rivers present a particularly interesting example of this kind of multiscalar flow resistance problem, as both individual grains and bedforms may contribute to the roughness length. In this paper, we propose a novel method of estimating the relative contribution of different physical scales of in-channel topography to the total roughness length, using a transform-roughness correlation (TRC) approach. The technique, which uses a longitudinal profile, consists of (1) a wavelet transform which decomposes the surface into roughness elements occurring at different wavelengths and (2) a "roughness correlation" that estimates the roughness length (ks ) associated with each wavelength based on its geometry alone. When applied to original and published laboratory experiments with a range of channel morphologies, the roughness correlation estimates the total ks to approximately a factor of 2 of measured values but may perform poorly in very steep channels with low relative submergence. The TRC approach provides novel and detailed information regarding the interaction between surface topography and fluid dynamics that may contribute to advances in hydraulics, bedload transport, and channel morphodynamics.

Original languageEnglish
Pages (from-to)1039-1051
Number of pages13
JournalEarth Surface Dynamics
Issue number4
Publication statusPublished - 9 Dec 2020

Bibliographical note

Publisher Copyright:
© 2020 Royal Society of Chemistry. All rights reserved.

We would like to thank two anonymous reviewers whose comments greatly improved this paper. We also thank William Booker, Lucy MacKenzie, Brett Eaton, and Ian Rutherfurd for reviewing the original manuscript and Benjamin Hohermuth for providing the laboratory step–pool data. This work was supported by postgraduate scholarships provided to DLA by the Australian and Canadian governments.


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