Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
Understanding the effects of human disturbance on the bedload transport regime of anthropised rivers is a topic of growing importance, as such information is of interest for adequate river diagnosis, correct implementation of restoration measures and appropriate design of post‐action monitoring programs. However, such assessments are complex, especially in sites where multiple factors simultaneously influence the bedload transport regime, so that it is difficult to establish simple causal relationships between human disturbances and changes in the sediment transport regime, notably on bedload. To overcome this, there is a need for rigorous hypothesis‐driven approaches to assess the isolated effects of each driver. With this in mind, we have characterised the dynamics of bedload transport in the Upper Garonne (Central Pyrenees, Spain‐France), a river impacted by sediment retention, flow diversion and mining that influence its morphological conditions and transport regime. We assessed the effects of (1) surface grain size distribution, (2) river morphology, (3) sediment supply and (4) flow diversion on the bedload transport regime. Four sites with different degrees of river anthropisation were selected. After defining hypotheses on the most likely bedload transport conditions for each site, we proposed a set of discriminating criteria to test these hypotheses, based on temporal within‐site and spatial between‐site comparisons of coarse particle tracking measurements over four years. The results of this research showed that the hydrosedimentary regime of the Garonne is controlled by a complex combination of drivers such as valley physiography, which exerts a first‐order control on differences in reach‐scale bedforms and bedload dynamics; and human disturbances which contribute to a reduction in sediment supply through changes in land cover and hydropower dams, or to changes in hydrology (i.e., flow competence) due to water diversion and abstraction.
Understanding the effects of human disturbance on the bedload transport regime of anthropised rivers is a topic of growing importance, as such information is of interest for adequate river diagnosis, correct implementation of restoration measures and appropriate design of post‐action monitoring programs. However, such assessments are complex, especially in sites where multiple factors simultaneously influence the bedload transport regime, so that it is difficult to establish simple causal relationships between human disturbances and changes in the sediment transport regime, notably on bedload. To overcome this, there is a need for rigorous hypothesis‐driven approaches to assess the isolated effects of each driver. With this in mind, we have characterised the dynamics of bedload transport in the Upper Garonne (Central Pyrenees, Spain‐France), a river impacted by sediment retention, flow diversion and mining that influence its morphological conditions and transport regime. We assessed the effects of (1) surface grain size distribution, (2) river morphology, (3) sediment supply and (4) flow diversion on the bedload transport regime. Four sites with different degrees of river anthropisation were selected. After defining hypotheses on the most likely bedload transport conditions for each site, we proposed a set of discriminating criteria to test these hypotheses, based on temporal within‐site and spatial between‐site comparisons of coarse particle tracking measurements over four years. The results of this research showed that the hydrosedimentary regime of the Garonne is controlled by a complex combination of drivers such as valley physiography, which exerts a first‐order control on differences in reach‐scale bedforms and bedload dynamics; and human disturbances which contribute to a reduction in sediment supply through changes in land cover and hydropower dams, or to changes in hydrology (i.e., flow competence) due to water diversion and abstraction.
Sediment transport remains a significant challenge for researchers due to the intricate nature of the physical processes involved and the diverse characteristics of watercourses worldwide. A type of watercourse that is of particular interest for study is the ephemeral streams, found primarily in semiarid and arid regions. Due to their unique nature, a new measurement algorithm was created and a modified bed load sampler was built. Measurement of the bed load transport rate and calculation of the water discharge were conducted in an ephemeral stream in Northeastern Greece, where the mean calculated streamflow rate ranged from 0.019 to 0.314 m3/s, and the measured sediment load transport rates per unit width varied from 0.00001 to 0.00213 kg/m/s. The sediment concentration was determined through various methods, including nonlinear regression equations and formulas developed by Yang, with the coefficients of these formulas calibrated accordingly. The results demonstrated that the equations derived from Yang’s multiple regression analysis offered a superior fit compared to the original equations. As a result, two modified versions of Yang’s stream sediment transport formulas were developed and are presented to the readership. To assess the accuracy of the modified formulas, a comparison was conducted between the calculated total sediment concentrations and the measured total sediment concentrations based on various statistical criteria. The analysis shows that none of Yang’s original formulas fit the available data well, but after optimization, both modified formulas can be applied to the specific ephemeral stream. The results indicate also that the formulas derived from the nonlinear regression can be successfully used for the determination of the total sediment concentration in the ephemeral stream and have a better fit compared to Yang’s formulas. The correlation from the nonlinear regression equations suggests that total sediment transport is primarily influenced by water discharge and rainfall intensity, with the latter showing a high correlation coefficient of 0.998.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.