Predicting the sediment transport capacity from flow condition and particle size in the presence of vegetation cover

Abstract

The sediment transport capacity plays a pivotal role in erosion research, and is usually predicted using hydraulic variables. The transport capacity and hydraulic variables are affected by vegetation cover. Our understanding of the effect of vegetation cover, including the size, density, and arrangement of vegetation stems, on the relationship between the sediment transport capacity and hydraulic variables were rather limited. The objectives of this study were to investigate the effect vegetation stem cover on the relationship between hydraulic variables and the sediment transport capacity and to derive an equation for predicting the sediment transport capacity in the presence of vegetation cover. Five data sets from 288 flume experiments with a wide range of discharge (0.25–2 × 10−3 m3 s−1), slope (8.8–42.3%), median sediment diameter (0.11–1.16 × 10−3 m), stem cover (0–30%), stem diameter (2–36 mm), and stem arrangement (bead, tessellation, zigzag, random, and banding) were compiled for this study. Extensive regression analysis has shown that the sediment transport capacity could be expressed as a power function of flow velocity, shear stress, stream power, or unit stream power. Predictors of the sediment transport capacity were ranked from the unit stream power as the strongest, followed by the stream power, flow velocity, and the shear stress. Vegetation stem cover had no apparent and direct effect on the relationship between hydraulic variables and the sediment transport capacity so long as the unit stream power or stream power was used as its predictor. Vegetation cover became a significant factor only when the shear stress was used to predict the sediment transport capacity. Finally, a new equation involving the slope gradient, flow velocity, and median sediment diameter in a nondimensional form was shown to be a superior predictor of the sediment transport capacity with the Nash–Sutcliffe coefficient of efficiency of 0.92. The product of slope and flow velocity, that is, the unit stream power, captures the effect of vegetation stem cover and surface roughness and was shown to be an effective predictor of the transport capacity in the presence of vegetation cover.

Exploring the relationship between soil erosion and hydraulic parameters on slopes with clipped herbaceous vegetation through Bayesian network modeling

“…This disturbance results in the loss of a stable surface roughness, leading to the need for a portion of the shear stress to counteract the ensuing instability, as a consequence, the form shear stress acting on the soil may decrease (Ding & Fu, 2022). Additionally, when taking into account the presence of vegetation stem cover, relying solely on the τ value may not accurately predict sediment transport capacity, as emphasized in the study by Mu et al (2020). Similarly, Yang et al (2017) and Shi et al (2019) reported weak linear relationships between the τ value and surface roughness in their experimental investigations.…”

“…The hydraulic parameters on a slope are influenced by various complex factors, including vegetation, rainfall characteristics, terrain slope, and soil type (Pan, Ma, & Wainwright, 2016a; Shen et al, 2016). Vegetation plays a pivotal role in attenuating the kinetic energy of raindrops and overland flow on hillslopes and in changing sediment particle transport patterns (Li et al, 2023; Mekonnen et al, 2016; Mu et al, 2020; Wen et al, 2023). Clipping management, as a primary means of regulating vegetation, has significant value in protecting ecology and improving economic benefits (Shahzad et al, 2012; Wang et al, 2023).…”

Determination of sediment transport capacity by hydrodynamic variables considering subsurface water flow

“…Researchers have studied T c under different experimental conditions, including variations in the vegetation/stem basal cover (Ding et al, 2020; Mu et al, 2019; Snelder & Bryan, 1995), median diameter (Mu et al, 2021), and hydrostatic pressure head (Wang et al, 2020). To further illustrate the influence of these conditions on T c , a new and more accurate equation was established by using these parameters with the traditional hydrodynamic parameters to predict T c .…”

“…Many predicted equations have been established for sheet/overland flow (Guy et al, 2009; Li et al, 2011), rill/concentrated flow (Knapen et al, 2009; Tekwa et al, 2016), and interrill flow (Abrahams et al, 2000; Li & Abrahams, 1999; Zhang et al, 2018). Researchers have determined that hydrodynamic variables, including the flow velocity ( V ), shear stress ( τ ), stream power ( w ), unit stream power ( P ), and unit energy ( E ), considerably influence T c (Ali et al, 2012; Ding et al, 2020; Fu et al, 2020; Knapen et al, 2009; Mu et al, 2021; Nord et al, 2009; Shih & Yang, 2009; Wang et al, 2016; Wu et al, 2018). Previous studies have shown that each parameter may be the optimal predictor for estimating T c under different experimental conditions (Ali et al, 2012; Hessel & Jetten, 2007; Knapen et al, 2009; Zhang et al, 2018).…”

“…Researchers have studied T c under different experimental conditions, including variations in the vegetation/stem basal cover (Ding et al, 2020;Mu et al, 2019;Snelder & Bryan, 1995), median diameter (Mu et al, 2021), and hydrostatic pressure head (Wang et al, 2020).…”