Estimating the parameters of the curve number model

David A. Chin

doi:10.1061/(ASCE)HE.1943-5584.0001495

Estimating the parameters of the curve number model

David A. Chin

Civil, Architectural & Environmental Engineering

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

A methodology is presented for combining the conventional Natural Resources Conservation Service (NRCS) 24-h rainfall distributions with Horton and Green-Ampt infiltration processes to estimate the curve number (CN) and initial abstraction (I_a) parameters of the NRCS curve number model. It is shown that the rainfall distribution, rainfall depth, and infiltration characteristics all affect CN and I_a, and the influence of these factors on CN and I_a under selected conditions are quantified. The results presented in this paper are particularly applicable to cases in which the dominant abstraction mechanism is infiltration.

Original language	English (US)
Article number	06017001
Journal	Journal of Hydrologic Engineering
Volume	22
Issue number	6
DOIs	https://doi.org/10.1061/(ASCE)HE.1943-5584.0001495
State	Published - Jun 1 2017

Keywords

Curve number model
Green-Ampt model
Horton model
Rainfall
Runoff

ASJC Scopus subject areas

Environmental Chemistry
Civil and Structural Engineering
Water Science and Technology
Environmental Science(all)

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10.1061/(ASCE)HE.1943-5584.0001495

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abstract = "A methodology is presented for combining the conventional Natural Resources Conservation Service (NRCS) 24-h rainfall distributions with Horton and Green-Ampt infiltration processes to estimate the curve number (CN) and initial abstraction (Ia) parameters of the NRCS curve number model. It is shown that the rainfall distribution, rainfall depth, and infiltration characteristics all affect CN and Ia, and the influence of these factors on CN and Ia under selected conditions are quantified. The results presented in this paper are particularly applicable to cases in which the dominant abstraction mechanism is infiltration.",

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AB - A methodology is presented for combining the conventional Natural Resources Conservation Service (NRCS) 24-h rainfall distributions with Horton and Green-Ampt infiltration processes to estimate the curve number (CN) and initial abstraction (Ia) parameters of the NRCS curve number model. It is shown that the rainfall distribution, rainfall depth, and infiltration characteristics all affect CN and Ia, and the influence of these factors on CN and Ia under selected conditions are quantified. The results presented in this paper are particularly applicable to cases in which the dominant abstraction mechanism is infiltration.

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KW - Runoff

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Estimating the parameters of the curve number model

Abstract

Keywords

ASJC Scopus subject areas

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