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A Modified SCS-CN Method Incorporating Storm Duration and Antecedent Soil Moisture Estimation for Runoff Prediction

Author

Listed:
  • Wenhai Shi

    (Institute of Soil and Water Conservation, CAS&MWR
    University of Chinese Academy of Sciences)

  • Mingbin Huang

    (Institute of Soil and Water Conservation, CAS&MWR
    Northwest A&F University)

  • Kate Gongadze

    (Rothamsted Research)

  • Lianhai Wu

    (Rothamsted Research)

Abstract

In one of the widely used methods to estimate surface runoff - Soil Conservation Service Curve Number (SCS-CN), the antecedent moisture condition (AMC) is categorized into three AMC levels causing irrational abrupt jumps in estimated runoff. A few improved SCS-CN methods have been developed to overcome several in-built inconsistencies in the soil moisture accounting (SMA) procedure that lies behind the SCS-CN method. However, these methods still inherit the structural inconsistency in the SMA procedure. In this study, a modified SCS-CN method was proposed based on the revised SMA procedure incorporating storm duration and a physical formulation for estimating antecedent soil moisture (V 0 ). The proposed formulation for V 0 estimation has shown a high degree of applicability in simulating the temporal pattern of soil moisture in the experimental plot. The modified method was calibrated and validated using a dataset of 189 storm-runoff events from two experimental watersheds in the Chinese Loess Plateau. The results indicated that the proposed method, which boosted the model efficiencies to 88% in both calibration and validation cases, performed better than the original SCS-CN and the Singh et al. (2015) method, a modified SCS-CN method based on SMA. The proposed method was then applied to a third watershed using the tabulated CN value and the parameters of the minimum infiltration rate (f c ) and coefficient (β) derived for the first two watersheds. The root mean square error between the measured and predicted runoff values was improved from 6 mm to 1 mm. Moreover, the parameter sensitivity analysis indicated that the potential maximum retention (S) parameter is the most sensitive, followed by f c . It can be concluded that the modified SCS-CN method, may predict surface runoff more accurately in the Chinese Loess Plateau.

Suggested Citation

  • Wenhai Shi & Mingbin Huang & Kate Gongadze & Lianhai Wu, 2017. "A Modified SCS-CN Method Incorporating Storm Duration and Antecedent Soil Moisture Estimation for Runoff Prediction," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(5), pages 1713-1727, March.
  • Handle: RePEc:spr:waterr:v:31:y:2017:i:5:d:10.1007_s11269-017-1610-0
    DOI: 10.1007/s11269-017-1610-0
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    References listed on IDEAS

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    1. Pingjin Jiao & Di Xu & Shaoli Wang & Yingduo Yu & Songjun Han, 2015. "Improved SCS-CN Method Based on Storage and Depletion of Antecedent Daily Precipitation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(13), pages 4753-4765, October.
    2. S. Mishra & M. Jain & P. Suresh Babu & K. Venugopal & S. Kaliappan, 2008. "Comparison of AMC-dependent CN-conversion Formulae," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(10), pages 1409-1420, October.
    3. S. Mishra & R. Sahu & T. Eldho & M. Jain, 2006. "An Improved I a S Relation Incorporating Antecedent Moisture in SCS-CN Methodology," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(5), pages 643-660, October.
    4. P. Singh & S. Mishra & R. Berndtsson & M. Jain & R. Pandey, 2015. "Development of a Modified SMA Based MSCS-CN Model for Runoff Estimation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(11), pages 4111-4127, September.
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    1. Sushindra Kumar Gupta & Jaivir Tyagi & Gunwant Sharma & A. S. Jethoo & P. K. Singh, 2019. "An Event-Based Sediment Yield and Runoff Modeling Using Soil Moisture Balance/Budgeting (SMB) Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(11), pages 3721-3741, September.

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