Technical Notes
Mar 15, 2016

Alternative CN Averaging Methods for Determining the Representative CN of a Watershed

Publication: Journal of Irrigation and Drainage Engineering
Volume 142, Issue 6

Abstract

A representative curve number (CN) of a catchment is often calculated from the area-weighted average of CN values of unique land use and soil combinations. While convenient for implementation, this method is known to underestimate direct runoff depth. This paper investigates the mathematical mechanism of the expected underestimation and proposes alternative CN averaging methods called the quadratic and exact averaging methods, to handle the underestimation problem. Results suggest that the quadratic method could reduce the level of underestimation in direct runoff depth; further, the exact method could provide the same direct runoff depth as that of the area-weighted direct runoff depth averaging method. A representative CN is found to be a function of rainfall size and catchment landscape, and the underestimation is relatively large for small and mid-sized storm events. The improvement in runoff estimation with the newly proposed averaging methods is particularly beneficial to stormwater management, flood controls, and erosion controls upon small return-period events.

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Go to Journal of Irrigation and Drainage Engineering
Journal of Irrigation and Drainage Engineering
Volume 142Issue 6June 2016

History

Received: Sep 14, 2015
Accepted: Dec 28, 2015
Published online: Mar 15, 2016
Published in print: Jun 1, 2016
Discussion open until: Aug 15, 2016

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Authors

Affiliations

Younggu Her [email protected]
Assistant Research Scientist, Blackland Research and Extension Center, Texas A&M Univ., 720 East Blackland Rd., Temple, TX 76502. E-mail: [email protected]
Chounghyun Seong [email protected]
Postdoctoral Research Fellow, Dept. of Biological Systems Engineering, Virginia Tech, 155 Ag Quad Ln., Blacksburg, VA 24061 (corresponding author). E-mail: [email protected]
Jaehak Jeong [email protected]
Assistant Professor, Blackland Research and Extension Center, Texas A&M Univ., 720 East Blackland Rd., Temple, TX 76502. E-mail: [email protected]

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