Flow resistance in mountain streams is important for assessing flooding hazard and quantifying sediment transport and bedrock incision in upland landscapes. In such settings, flow resistance is sensitive to grain‐scale roughness, which has traditionally been characterized by particle size distributions derived from laborious point counts of streambed sediment. Developing a general framework for rapid quantification of resistance in mountain streams is still a challenge. Here we present a semi‐automated workflow that combines millimeter‐ to centimeter‐scale structure‐from‐motion (SfM) photogrammetry surveys of bed topography and computational fluid dynamics (CFD) simulations to better evaluate surface roughness and rapidly quantify flow resistance in mountain streams. The workflow was applied to three field sites of gravel, cobble, and boulder‐bedded channels with a wide range of grain size, sorting, and shape. Large‐eddy simulations with body‐fitted meshes generated from SfM photogrammetry‐derived surfaces were performed to quantify flow resistance. The analysis of bed microtopography using a second‐order structure function identified three scaling regimes that corresponded to important roughness length scales and surface complexity contributing to flow resistance. The standard deviation
- Award ID(s):
- 1849109
- Publication Date:
- NSF-PAR ID:
- 10315907
- Journal Name:
- Lab on a Chip
- Volume:
- 22
- Issue:
- 3
- ISSN:
- 1473-0197
- Sponsoring Org:
- National Science Foundation
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