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Effects of flow hydraulics on total nitrogen loss on steep slopes under simulated rainfall conditions
Author(s) -
Qian Feng,
Jiesheng Huang,
Jingjun Liu,
Honghu Liu
Publication year - 2017
Publication title -
hydrology research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.665
H-Index - 48
eISSN - 1996-9694
pISSN - 0029-1277
DOI - 10.2166/nh.2017.261
Subject(s) - froude number , hydraulics , surface runoff , hydrology (agriculture) , sediment transport , environmental science , sediment , flow (mathematics) , soil water , reynolds number , stream power , flow velocity , water flow , soil science , geology , geotechnical engineering , mathematics , mechanics , turbulence , geomorphology , geometry , ecology , physics , biology , engineering , aerospace engineering
Flow hydraulics play important roles in soil erosion and loss of soil nutrients. A better understanding of the relationship between flow hydraulics and nutrient losses will improve chemical transport modeling. The laboratory experiment was conducted to determine flow hydraulics9 effects on total nitrogen (TN) loss. The impacts of rainfall intensities (0.6, 1.1, 1.61, 2.12, and 2.54 mm·min −1 ) and slope gradients (10°, 15°, and 20°) on TN loss were also studied. Selected soils were derived from purple sandy shales, which are the main parent materials in Wangjiaqiao watershed, southern China. Results show that negative linear relationships ( R 2 = 0.71) were observed between the rate of Manning roughness coefficient to average flow depth and the unit area runoff-associated TN transport rate. There was a good linear relationship between the unit area sediment-associated TN transport rate and Reynolds numbers ( R 2 = 0.90), flow velocity ( R 2 = 0.87), and stream power ( R 2 = 0.73), while Froude numbers, Darcy–Weisbach and Manning friction coefficients were not good hydraulic indicators of the sediment-associated TN loss of purple soil. The equation including stream power and flow velocity may have a better correlation coefficient ( R 2 = 0.94).

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