Discussion of “ Sediment Transport and Unit Stream Power Function ” by Chih Ted Yang and Albert Molinas (June, 1982)

1983 ◽  
Vol 109 (12) ◽  
pp. 1779-1781
Author(s):  
Thomas Maddock
Keyword(s):  
Sediment Transport ◽  
Power Function ◽  
Stream Power

Sediment Transport and Unit Stream Power Function

1982 ◽  
Vol 108 (6) ◽  
pp. 774-793 ◽  
Author(s):  
Chih Ted. Yang ◽  
Albert Molinas
Keyword(s):  
Sediment Transport ◽  
Power Function ◽  
Stream Power

Experimental study on dynamic mechanism of sheet erosion processes on steep grassland in the loess region of China

2021 ◽  
Author(s):  
Qi Guo ◽  
Zhanli Wang
Keyword(s):  
Shear Stress ◽  
Soil Erosion ◽  
Power Function ◽  
Erosion Rate ◽  
Dynamic Mechanism ◽  
Erosion Process ◽  
Stream Power ◽  
Study Results ◽  
Loess Region ◽  
Sheet Erosion

<p>Sheet erosion has been the major erosion process on steep grassland since the Grain-for-Green project was implemented in 1999 in the Loess Plateau with serious soil erosion, in China. Quantifying sheet erosion rate on steep grassland could improve soil erosion estimation on loess hillslopes and provide scientific support for effectively controlling soil erosion and rationally managing grassland. Simulated rainfall experiments were conducted on grassland plot with vegetation coverage of 40% under complete combination of rainfall intensities of 0.7, 1.0, 1.5, 2.0 and 2.5 mm min<sup>-1</sup> and slope gradients of 7°, 10°, 15°, 20° and 25°. Results showed that sheet erosion rate (<em>SE</em>), varying from 0.0048 to 0.0578 kg m<sup>-2</sup> min<sup>-1</sup>, was well described by binary power function equation (<em>SE</em> = 0.0026 <em>I</em><sup>1.306</sup><em>S</em><sup>0.662</sup>) containing rainfall intensity and slope gradient with <em>R<sup>2</sup></em> = 0.940. The logarithmic equation of shear stress (<em>SE</em> = 0.084 + Ln (<em>τ</em>)) and the power function equation of stream power (<em>SE</em> = 1.141 <em>ɷ</em><sup>1.073</sup>) could be used to predict sheet erosion rate. Stream power (<em>R<sup>2</sup></em> = 0.903) was a better predictor of sheet erosion than shear stress (<em>R<sup>2</sup></em> = 0.882). However, predictions based on flow velocity, unit stream power, and unit energy were unsatisfactory. The stream power was an excellent hydrodynamic parameter for predicting sheet erosion rate. The sheet erosion process of grassland slope was also affected by the raindrop impact except the dynamic action of sheet flow. The combination of stream power and rainfall kinetic energy (<em>KE</em>) among different rainfall physical parameters had the most closely relationship with the sheet erosion rates, which is also better than the stream power only, and a binary power function equation (<em>SE</em> = 0.221 <em>ω</em><sup>0.831</sup><em>KE</em><sup>0.416</sup>) could be used to predict sheet erosion rate on grassland slope with <em>R<sup>2</sup></em> = 0.930. The study results revealed the dynamic mechanism of the sheet erosion process on steep grassland in the loess region of China.</p>

scholarly journals A Fuzzy Transformation of the Classic Stream Sediment Transport Formula of Yang

Water ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 257
Author(s):  
Konstantinos Kaffas ◽  
Matthaios Saridakis ◽  
Mike Spiliotis ◽  
Vlassios Hrissanthou ◽  
Maurizio Righetti
Keyword(s):  
Sediment Transport ◽  
Linear Regression ◽  
Regression Model ◽  
Sediment Concentration ◽  
Stream Sediment ◽  
Fuzzy Regression ◽  
Large Set ◽  
Stream Power ◽  
Fuzzy Transformation ◽  
Total Sediment

The objective of this study is to transform the arithmetic coefficients of the total sediment transport rate formula of Yang into fuzzy numbers, and thus create a fuzzy relationship that will provide a fuzzy band of in-stream sediment concentration. A very large set of experimental data, in flumes, was used for the fuzzy regression analysis. In a first stage, the arithmetic coefficients of the original equation were recalculated, by means of multiple regression, in an effort to verify the quality of data, by testing the closeness between the original and the calculated coefficients. Subsequently, the fuzzy relationship was built up, utilizing the fuzzy linear regression model of Tanaka. According to Tanaka’s fuzzy regression model, all the data must be included within the produced fuzzy band and the non-linear regression can be concluded to a linear regression problem when auxiliary variables are used. The results were deemed satisfactory for both the classic and fuzzy regression-derived equations. In addition, the linear dependence between the logarithmized total sediment concentration and the logarithmized subtraction of the critical unit stream power from the exerted unit stream power is presented. Ultimately, a fuzzy counterpart of Yang’s stream sediment transport formula is constructed and made available to the readership.

scholarly journals Effect of hydraulic parameters on sediment transport capacity in overland flow over erodible beds

2012 ◽  
Vol 16 (2) ◽  
pp. 591-601 ◽  
Author(s):  
M. Ali ◽  
G. Sterk ◽  
M. Seeger ◽  
M. Boersema ◽  
P. Peters
Keyword(s):  
Shear Stress ◽  
Sediment Transport ◽  
Hydraulic Parameters ◽  
Transport Capacity ◽  
Slope Gradient ◽  
Mean Flow ◽  
Stream Power ◽  
Unit Discharge ◽  
Sediment Transport Capacity ◽  
Mean Flow Velocity

Abstract. Sediment transport is an important component of the soil erosion process, which depends on several hydraulic parameters like unit discharge, mean flow velocity, and slope gradient. In most of the previous studies, the impact of these hydraulic parameters on transport capacity was studied for non-erodible bed conditions. Hence, this study aimed to examine the influence of unit discharge, mean flow velocity and slope gradient on sediment transport capacity for erodible beds and also to investigate the relationship between transport capacity and composite force predictors, i.e. shear stress, stream power, unit stream power and effective stream power. In order to accomplish the objectives, experiments were carried out in a 3.0 m long and 0.5 m wide flume using four well sorted sands (0.230, 0.536, 0.719, 1.022 mm). Unit discharges ranging from 0.07 to 2.07 × 10−3 m2 s−1 were simulated inside the flume at four slopes (5.2, 8.7, 13.2 and 17.6%) to analyze their impact on sediment transport rate. The sediment transport rate measured at the bottom end of the flume by taking water and sediment samples was considered equal to sediment transport capacity, because the selected flume length of 3.0 m was found sufficient to reach the transport capacity. The experimental result reveals that the slope gradient has a stronger impact on transport capacity than unit discharge and mean flow velocity due to the fact that the tangential component of gravity force increases with slope gradient. Our results show that unit stream power is an optimal composite force predictor for estimating transport capacity. Stream power and effective stream power can also be successfully related to the transport capacity, however the relations are strongly dependent on grain size. Shear stress showed poor performance, because part of shear stress is dissipated by bed irregularities, bed form evolution and sediment detachment. An empirical transport capacity equation was derived, which illustrates that transport capacity can be predicted from median grain size, total discharge and slope gradient.

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