Evaluation of bed load transport equations in gravel bed rivers: A case study of the lower Jinsha River (SW China)
Study region: This research is centered on the Sanduizi Reach of the lower Jinsha River, situated within the upper Yangtze River Basin in southwestern China. This section exemplifies a typical mountainous gravel-bed river, characterized by intricate hydraulic conditions, heterogeneous bed material,...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-08-01
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| Series: | Journal of Hydrology: Regional Studies |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S221458182500391X |
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| Summary: | Study region: This research is centered on the Sanduizi Reach of the lower Jinsha River, situated within the upper Yangtze River Basin in southwestern China. This section exemplifies a typical mountainous gravel-bed river, characterized by intricate hydraulic conditions, heterogeneous bed material, and a well-developed armor layer. Study focus: Existing bed load transport equations, predominantly derived from flume experiments with uniform sediments or data gathered in small to medium-sized rivers, frequently yield unreliable predictions when applied to large gravel-bed systems such as the Jinsha River. Utilizing 738 field measurements, we assessed the performance of six classical equations and identified systematic overestimations and underestimations, primarily attributable to the neglect of armor layer effects and transport phase variability. To address these limitations, we propose a novel dimensionless equation that incorporates critical parameters: d84 (surface material mobility), θ84/θc84 (transport phase classification), (d84/ d50)J (hiding–exposure effect), d84/H (relative roughness), and U (dimensionless velocity). New hydrological insights for the region: This study conducts the first comparative assessment of bed load transport equations in the lower Jinsha River. The newly proposed equation exhibits markedly enhanced predictive accuracy, with 97 % of the calculated values residing within one order of magnitude of the observed data. By necessitating only five variables, it improves field applicability and highlights the critical importance of incorporating armor layer mobility and transport phase dynamics in the modeling of gravel-bed rivers. |
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| ISSN: | 2214-5818 |