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Article

A Calibrated, Watershed-Specific SCS-CN Method: Application to Wangjiaqiao Watershed in the Three Gorges Area, China

1
Universiti Tunku Abdul Rahman, Jalan Sungai Long, Bandar Sungai Long, Kajang 43000, Malaysia
2
Centre for Environmental Sustainability and Water Security, Universiti Teknologi Malaysia, Skudai 81310, Malaysia
3
Institute of Energy Infrastructure, Universiti Tenaga Nasional, Kajang 43000, Malaysia
4
Department of Liberal Arts and Languages, American Degree Programme, Taylor’s University, No. 1, Jalan Taylors, Subang Jaya 47500, Malaysia
*
Author to whom correspondence should be addressed.
Current address: Department of Civil Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kajang 43000, Malaysia.
Water 2020, 12(1), 60; https://doi.org/10.3390/w12010060
Received: 27 September 2019 / Revised: 23 November 2019 / Accepted: 26 November 2019 / Published: 22 December 2019
The Soil Conservation Service curve number ( S C S-C N) method is one of the most popular methods used to compute runoff amount due to its few input parameters. However, recent studies challenged the inconsistent runoff results obtained by the method which set the initial abstraction ratio λ as 0.20. This paper developed a watershed-specific S C S-C N calibration method using non-parametric inferential statistics with rainfall–runoff data pairs. The proposed method first analyzed the data and generated confidence intervals to determine the optimum values for S C S- C N model calibration. Subsequently, the runoff depth and curve number were calculated. The proposed method outperformed the runoff prediction accuracy of the asymptotic curve number fitting method, linear regression model and the conventional S C S-C N model with the highest Nash–Sutcliffe index value of 0.825, the lowest residual sum of squares value of 133.04 and the lowest prediction error. It reduced the residual sum of squares by 66% and the model prediction errors by 96% when compared to the conventional S C S-C N model. The estimated curve number was 72.28, with the confidence interval ranging from 62.06 to 78.00 at a 0.01 confidence interval level for the Wangjiaqiao watershed in China. View Full-Text
Keywords: SCS; initial abstraction ratio; curve number; bootstrap; rainfall–runoff model SCS; initial abstraction ratio; curve number; bootstrap; rainfall–runoff model
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MDPI and ACS Style

Ling, L.; Yusop, Z.; Yap, W.-S.; Tan, W.L.; Chow, M.F.; Ling, J.L. A Calibrated, Watershed-Specific SCS-CN Method: Application to Wangjiaqiao Watershed in the Three Gorges Area, China. Water 2020, 12, 60. https://doi.org/10.3390/w12010060

AMA Style

Ling L, Yusop Z, Yap W-S, Tan WL, Chow MF, Ling JL. A Calibrated, Watershed-Specific SCS-CN Method: Application to Wangjiaqiao Watershed in the Three Gorges Area, China. Water. 2020; 12(1):60. https://doi.org/10.3390/w12010060

Chicago/Turabian Style

Ling, Lloyd, Zulkifli Yusop, Wun-She Yap, Wei L. Tan, Ming F. Chow, and Joan L. Ling 2020. "A Calibrated, Watershed-Specific SCS-CN Method: Application to Wangjiaqiao Watershed in the Three Gorges Area, China" Water 12, no. 1: 60. https://doi.org/10.3390/w12010060

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