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The Functional Relationship of Sediment Transport under Various Simulated Rainfall Conditions
被引:1
作者:
Henorman, Hanna Mariana
[1
]
Tholibon, Duratul Ain
[2
]
Nujid, Masyitah Md
[3
]
Mokhtar, Hamizah
[2
]
Rahim, Jamilah
[2
]
Saadon, Azlinda
[1
]
机构:
[1] Univ Teknol MARA UiTM, Coll Engn, Sch Civil Engn, Shah Alam 40000, Selangor, Malaysia
[2] Univ Teknol MARA UiTM, Coll Engn, Sch Civil Engn, Jengka Campus, Jengka 26400, Pahang, Malaysia
[3] Univ Teknol MARA UiTM, Coll Engn, Sch Civil Engn, Permatang Pauh Campus, George Town 13500, Malaysia
来源:
关键词:
dimensional analysis;
functional relationship;
sediment transport;
simulated rainfall;
HYDRAULIC PARAMETERS;
OVERLAND-FLOW;
EROSION;
RUNOFF;
CAPACITY;
SOIL;
PATTERNS;
SIZE;
YIELD;
D O I:
10.3390/fluids7030107
中图分类号:
O3 [力学];
学科分类号:
08 ;
0801 ;
摘要:
Sediment removed in the detachment process is transported by overland flow. Previous experimental and field works studied that sediment transport is influenced by hydraulic properties of flow, physical properties of soil, and surface characteristics. Several equations in predicting sediment transport have been developed from previous research. The objective of this paper was to establish the selected parameters that contribute to the sediment transport capacity in overland flow conditions under different rainfall pattern conditions and to evaluate their significance. The establishment of independent variables was performed using the dimensional analysis approach that is Buckingham's pi theorem. The final results obtained are a series of independent parameters; the Reynolds number (Re), dimensionless rainfall parameter (iL/v), hydraulic characteristics (Q/Lv) that related to the dependent parameters; and dimensionless sediment transport (q(s)/rho v). The relationship indicates that 63.6% to 72.44% of the variance in the independent parameters is in relation to the dependent parameter. From the iteration method, the estimation of constant and regression coefficient values is presented in the form of the general formula for linear and nonlinear model equations. The linear and nonlinear model equations have the highest model accuracy of 93.1% and 81.5%, respectively. However, the nonlinear model equation has the higher discrepancy ratio of 54.9%.
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页数:18
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