Abstract. 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 can potentially be important roughness elements. In this paper, we propose a novel method of estimating the relative contribution of different physical scales of river bed topography to the total drag, using a transform-roughness correlation (TRC) approach. The technique, which requires only a single 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 drag associated with each wavelength based on its geometry alone, expressed as ks. We apply the TRC approach to original and published laboratory experiments and show that the multiscalar drag decomposition yields estimates of grain- and form-drag that are consistent with estimates in channels with similar morphologies. Also, we demonstrate that the roughness correlation may be used to estimate total flow resistance via a conventional equation, suggesting that it could replace representative roughness values such as median grain size or the standard deviation of elevations. An improved understanding of how various scales contribute to total flow resistance may lead to advances in hydraulics as well as channel morphodynamics.
Near-bottom flow and flow resistance for currents obliquely incident to two-dimensional roughness elements
