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a State Key Lab. of Earth Surface Processes and, Resource Ecology, Beijing, 100875, China
b School of Geography, Beijing Normal Univ., Beijing, 100875, China
c USDA-ARS, Grazinglands Research Lab., El Reno, OK 73036
* Corresponding author (ghzhang{at}bnu.edu.cn).
Quantifying the effect of sediment load on the detachment rate is crucial to understand soil erosion processes and develop physically based soil erosion models. Many recent studies attempted to quantify the feedback relationship between sediment load and detachment rate. To date, however, the effects of sediment load on detachment rate are still unclear. The objectives of this study were to examine the potential effects of sediment load on detachment rates and to examine the widely assumed linear relationship between sediment load and detachment rate in rills under controlled conditions. Experiments were performed in a hydraulic flume with constant roughness. Slope gradient (S) varied from 8.8 to 46.6% and unit flow rate (q) from 1.25 to 5.00 x 10–3 m2 s–1. Detachment rates were measured under different sediment loads, which were 0 (clear water), 25, 50, 75, and 100% of the sediment transport capacity (Tc) for 20 combinations of q and S. Results showed that detachment rates decreased as sediment load increased. Discrepancies in declining patterns of detachment rates were observed. Regression results indicated that 16 combinations of q and S were best simulated by linear feedback relationships, while four combinations were best fitted to exponential functions. Both predicted detachment capacity (Dc) and Tc by linear relationships agreed well with the corresponding measured values (R2 = 0.99, Nash–Sutcliffe efficiency [NSE] = 0.97 for Dc; R2 = 0.99, NSE = 0.98 for Tc). The predicted detachment rate by a first-order coupling equation agreed with the measured data (R2 = 0.94, NSE
0.92). Overall, the feedback relationship between sediment load and detachment rate in this flume study could be adequately represented by the first-order coupling equation.
Abbreviations: MAE, mean absolute error ME, maximum error NSE, coefficient of Nash–Sutcliffe efficiency WEPP, Water Erosion Prediction Project
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