[1]ZHANG Xin,ZHANG Qingfeng,ZHOU Yangyang,et al.SCS-CN Parameter Determination Using Rainfall-Runoff Data on Microtopographic Surfaces of Different Gradient Loess Slopes[J].Research of Soil and Water Conservation,2019,26(02):74-77.
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Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
26
Number of periods:
2019 02
Page number:
74-77
Column:
Public date:
2019-04-28
- Title:
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SCS-CN Parameter Determination Using Rainfall-Runoff Data on Microtopographic Surfaces of Different Gradient Loess Slopes
- Author(s):
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ZHANG Xin, ZHANG Qingfeng, ZHOU Yangyang, LIU Jinlong
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College of Natural Resources and Environment, Northwest A & F University, Yangling, Shaanxi 712100, China
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- Keywords:
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microtopographic surface on a loess slope; SCS-CN model; λ value; CN value
- CLC:
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P481;TV121+.1
- DOI:
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- Abstract:
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The most popular hydrological models are based on the Soil Conservation Service Curve Number (SCS-CN) model for its simplicity. If using data obtained in natural rainfall events, the effect of slope gradient will be significant as the model is parameterized that way, which may interfere with calculating runoff in the events. This work tries to explore the influence of slope gradients (5°,15° and 25°) on initial abstraction rate λ and curve number (CN) and their evolution in the events on the loess slope surface under microtopographic conditions, which can prepare ground for future SCS-CN parameterization research and for runoff prediction modeling in the related fields. A laboratory rainfall experiment (rainfall intensity at 90 mm/h and slope surfaces tilled by manual hoeing and digging) was carried out to determine appropriate values of λ and CN for a SCS-CN model. The results showed that the model provided the most appropriate values of λ and CN and prediction for runoff volume which fit measured rainfall-runoff data when the model determined that λ=0.2,CN=75.58 at 5°; λ=0.15,CN=77.28 at 15° and λ=0.1,CN=72.91 at 25°. It was also found that the standard parameter λ=0.2 alone could not verify runoff prediction modeling at different slope gradients and a more appropriate value tended to decrease when the slope gradient increased.