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Accounting for Spatiotemporal Variations of Curve Number Using Variable Initial Abstraction and Antecedent Moisture

Author

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  • Vijay P. Santikari

    (Clemson University)

  • Lawrence C. Murdoch

    (Clemson University)

Abstract

The curve number (CN) of a watershed varies spatially due to heterogeneity, and temporally due to changes in soil moisture, land cover, temperature, and other processes. The conventional event-scale lumped-parameter CN method lacks the capability to account for spatiotemporal variations, which diminishes the accuracy of its predictions. Heterogeneity causes several parameters of the CN method, including the initial abstraction (Ia), to vary with event rainfall (P), so one way to account for heterogeneity is to treat Ia as a function of P. This modification to the CN method gives rise to variable Ia models. Including antecedent moisture (M) is a common way to account for the temporal variation of CN. This paper presents an improved method of including M, which when used together with variable Ia can allow for accounting of both spatial and temporal variability. A suite of models that use M and/or variable Ia was evaluated using published event-scale data from several studies along with rainfall-runoff observations from two small watersheds in South Carolina, USA. Including M in the CN models significantly improved the accuracy of the runoff predictions, whereas including variable Ia alone resulted in modest improvements. The best performance, NSE > 0.8, was achieved when both variable Ia and M were included together. These modifications significantly improve runoff predictions while only modestly increasing the complexity of the CN method.

Suggested Citation

  • Vijay P. Santikari & Lawrence C. Murdoch, 2019. "Accounting for Spatiotemporal Variations of Curve Number Using Variable Initial Abstraction and Antecedent Moisture," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(2), pages 641-656, January.
    • Handle: RePEc:spr:waterr:v:33:y:2019:i:2:d:10.1007_s11269-018-2124-0
    DOI: 10.1007/s11269-018-2124-0
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    References listed on IDEAS

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    1. S. K. Mishra & M. K. Jain & V. P. Singh, 2004. "Evaluation of the SCS-CN-Based Model Incorporating Antecedent Moisture," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 18(6), pages 567-589, December.
    2. 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.
    3. Gassman, Philip W. & Reyes, Manuel R. & Green, Colleen H. & Arnold, Jeffrey G., 2007. "The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions," ISU General Staff Papers 200701010800001027, Iowa State University, Department of Economics.
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