sediment transport capacity
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2021 ◽  
Author(s):  
Robert J Hawley ◽  
Kathryn Russell ◽  
Kristine Taniguchi-Quan

Abstract Stream channel erosion, enlargement, and habitat degradation are ubiquitous in urban watersheds with conventional stormwater management. Hydrologic-based restoration aims to discharge a more natural flow regime via stormwater management interventions. Whether such interventions facilitate geomorphic recovery depends, in part, on the degree to which they restrict discharges that would otherwise contribute to channel erosion. Erosion potential (E), the ratio of post-developed to predeveloped sediment transport capacity, provides a simplified, mechanistic framework to quantify the relative influence of stormwater interventions on the geomorphic effectiveness of the flow regime. This paper compiles ca. five years of data following stormwater-based interventions in three distinct settings in the United States and Australia to demonstrate how the E framework can be used to elucidate the role of hydrologic restoration interventions in helping to facilitate trajectories of geomorphic recovery (or lack thereof). In a previously developed watershed with unstable streams, substantial reductions in E coincided with a trajectory of geomorphic recovery, whereas our case study that did not reduce E between the study periods exhibited continued instability. Furthermore, a greenfield study site that used the E framework to optimize their SCMs to match the sediment transport capacity of the predeveloped regime (E = 1) was able to maintain a recovery trajectory in a legacy-impacted setting that is otherwise highly susceptible to hydromodification. Although available space and funding will limit the ability to fully reduce E in previously developed watersheds, these case studies underscore the mechanistic value of using stormwater controls to maximize reductions in E if geomorphic stability is a goal of stormwater interventions. Streambed material size and channel evolution stage also likely affect the level of E reduction necessary to promote geomorphic recovery, with coarser-grained and/or over-widened streams potentially needing less reduction than finer-grained and/or more entrenched channels.


Water ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 3054
Author(s):  
Linh Nguyen Van ◽  
Xuan-Hien Le ◽  
Giang V. Nguyen ◽  
Minho Yeon ◽  
Sungho Jung ◽  
...  

Estimation of sediment transport capacity (STC) plays a crucial role in simulating soil erosion using any physics-based models. In this research, we aim to investigate the pros and cons of six popular STC methods (namely, Shear velocity, Kilinc-Richardson (KR), Effective stream power, Slope and unit discharge, Englund-Hansen (EH), and Unit stream power) for soil erosion/deposition simulation at watershed scales. An in-depth analysis was performed using the selected STC methods integrated into the Grid Surface Subsurface Hydrologic Analysis model for investigating the changes in morphology at spatial-temporal scales at the Cheoncheon watershed, South Korea, over three storm events. Conclusions were drawn as follows. (1) Due to the ability of the KR and EH methods to include an additional parameter (i.e., erodibility coefficient), they outperformed others by producing more accurate simulation results of sediment concentration predictions. The KR method also proved to be superior to the EH method when it showed a more suitable for sediment concentration simulations with a wide range of sediment size and forcing magnitude. (2) We further selected 2 STC methods among the 6 methods to deeply explore the spatial distribution of erosion/deposition. The overall results were more agreeable. For instance, the phenomenon of erosion mainly occurred upstream of watersheds with steep slopes and unbalanced initial sediment concentrations, whereas deposition typically appeared at locations with flat terrain (or along the mainstream). The EH method demonstrated the influence of topography (e.g., gradient slope) on accretionary erosion/deposition results more significantly than the KR method. The obtained results contribute a new understanding of rainfall-sediment-runoff processes and provide fundamental plans for soil conservation in watersheds.


PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0256827
Author(s):  
Kai Zhang ◽  
Wang Xuan ◽  
Bai Yikui ◽  
Xu Xiuquan

Sediment transport capacity (Tc) is an essential parameter in the establishment of the slope soil erosion model. Slope type is an important crucial factor affecting sediment transport capacity of overland flow, and vegetation can effectively inhibit soil loss. Two new formulae of sediment transport capacity (Tc) are proposed of brown soil slope and vegetation slope in this study and evaluate the influence of slope gradient (S) and flow discharge (Q) on sediment transport capacity of different slope types. Laboratory experiments conducted using four flow discharges (0.35, 0.45, 0.55, and 0.65 L s-1), four slope gradients (3, 6, 9, and 12°), and two kinds of underlying surface (Brown soil slope, Vegetation slope). The soil particle size range is 0.05–0.5mm. The vegetation stems were 2mm in diameter and randomly arranged. The results show that the sediment transport capacity was positively correlated with the flow discharge and slope gradient. The vegetation slope’s average sediment transport capacity is 11.80% higher than the brown soil slope that same discharge and slope gradient conditions. The sensitivity of sediment transport capacity to flow discharge on brown soil slope is higher than that of slope gradient. The sensitivity of sediment transport capacity of vegetation slope to slope gradient is more heightened than flow discharge. The sediment transport capacity was well predicted by discharge and slope gradient on brown soil slope (R2 = 0.982) and vegetation slope (R2 = 0.993). This method is helpful to promote the study of the sediment transport process on overland flow.


CATENA ◽  
2021 ◽  
Vol 202 ◽  
pp. 105261
Author(s):  
Yuhan Huang ◽  
Xiaohui Zhuang ◽  
Wei Wang ◽  
Tingwu Lei ◽  
Zhiqiang Liu ◽  
...  

2021 ◽  
pp. 125951
Author(s):  
Jinliang Zhang ◽  
Yizi Shang ◽  
Jinyong Liu ◽  
Jun Lu ◽  
Shitao Wei ◽  
...  

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