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Runoff Estimation Using the NRCS Slope-Adjusted Curve Number in Mountainous Watersheds

Title
Runoff Estimation Using the NRCS Slope-Adjusted Curve Number in Mountainous Watersheds
Author
김태웅
Keywords
Initial abstraction; Natural resources conservation service (NRCS) model; Slope-adjusted curve number(CN); Surface runoff; INCORPORATING ANTECEDENT MOISTURE; INITIAL ABSTRACTION; LOESS PLATEAU; LAND SLOPE; MODEL; INFILTRATION; HILLSLOPE; COVER; CHINA
Issue Date
2016-04
Publisher
ASCE-AMER SOC CIVIL ENGINEERS
Citation
JOURNAL OF IRRIGATION AND DRAINAGE ENGINEERING, v. 142, No. 4, Article no. 04016002
Abstract
In mountainous watersheds, rainfall generates runoff quickly because of the decreased depression storage, high downslope flow velocity, and smaller chance for rainwater infiltration. In order to obtain precise event-based runoff estimations in mountainous watersheds, a slope-adjusted curve number (CNII) with a smaller initial abstraction ratio () is indispensable in the standard natural resources conservation service (NRCS) curve number (CN) model. Using measured rainfall-runoff data from 39 mountainous watersheds in South Korea, this study investigated two existing CNII approaches and suggested a new approach that was accompanied by a lower value. The new CNII equation was calibrated with 1,402 measured rainfall-runoff events from 31 watersheds and validated with 377 rainfall-runoff events from the remaining eight watersheds. Most of the runoff events, used for both calibration and validation, were underestimated using a CN without a slope-adjusting factor. By considering the combined effect of the proposed CNII and setting equal to 0.01, the performance measures based on the root mean squares error (in mm), Nash-Sutcliffe efficiency, and coefficient of determination were significantly improved from averages of 27.10, 0.64, and 0.75 to 18.69, 0.82, and 0.87, respectively, as compared to the standard NRCS model. The proposed modification exhibited superior results compared to the two existing CNII approaches. Findings from this study support the adjustment of both the CN and in the NRCS model to increase its runoff prediction capabilities.
URI
https://ascelibrary.org/doi/abs/10.1061/(ASCE)IR.1943-4774.0000998https://repository.hanyang.ac.kr/handle/20.500.11754/102278
ISSN
0733-9437; 1943-4774
DOI
10.1061/(ASCE)IR.1943-4774.0000998
Appears in Collections:
COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > CIVIL AND ENVIRONMENTAL ENGINEERING(건설환경공학과) > Articles
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