A modification to the Soil Conservation Service curve number method for steep slopes in the Loess Plateau of China
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Bibliographic record
Abstract
Abstract The Soil Conservation Service curve number (CN) method is widely used for predicting direct runoff from rainfall. However, despite the extent of cultivation on hillslope areas, very few attempts have been made to incorporate a slope factor into the CN method. The objectives of this study were (1) to evaluate existing approaches integrating slope in the CN method, and (2) to develop an equation incorporating a slope factor into the CN method for application in the steep slope areas of the Loess Plateau of China. The dataset consisted of 11 years of rainfall and runoff measurements from two experimental sites with slopes ranging from 14 to 140%. The results indicated that the standard CN method underestimated large runoff events and overestimated small events. For our experimental conditions, the optimized and non‐optimized forms of the slope‐modified CN method of the Erosion Productivity Impact Calculator model improved runoff prediction for steep slopes, but large runoff events were still underestimated and small ones overpredicted. Based on relationships between slope and the observed and theoretical CN values, an equation was developed that better predicted runoff depths with an R 2 of 0·822 and a linear regression slope of 0·807. This slope‐adjusted CN equation appears to be the most appropriate for runoff prediction in the steep areas of the Loess Plateau of China. Copyright © 2005 John Wiley & Sons, Ltd.
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Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it