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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/15041
Title: Evaluation of the Soil Conservation Service curve number methodology using data from agricultural plots
Authors: Lal M.
Mishra, Surendra Kumar
Pandey, Ashish
Pandey R.P.
Meena P.K.
Chaudhary A.
Jha R.K.
Shreevastava A.K.
Kumar Y.
Published in: Hydrogeology Journal
Abstract: The Soil Conservation Service curve number (SCS-CN) method, also known as the Natural Resources Conservation Service curve number (NRCS-CN) method, is popular for computing the volume of direct surface runoff for a given rainfall event. The performance of the SCS-CN method, based on large rainfall (P) and runoff (Q) datasets of United States watersheds, is evaluated using a large dataset of natural storm events from 27 agricultural plots in India. On the whole, the CN estimates from the National Engineering Handbook (chapter 4) tables do not match those derived from the observed P and Q datasets. As a result, the runoff prediction using former CNs was poor for the data of 22 (out of 24) plots. However, the match was little better for higher CN values, consistent with the general notion that the existing SCS-CN method performs better for high rainfall–runoff (high CN) events. Infiltration capacity (fc) was the main explanatory variable for runoff (or CN) production in study plots as it exhibited the expected inverse relationship between CN and fc. The plot-data optimization yielded initial abstraction coefficient (λ) values from 0 to 0.659 for the ordered dataset and 0 to 0.208 for the natural dataset (with 0 as the most frequent value). Mean and median λ values were, respectively, 0.030 and 0 for the natural rainfall–runoff dataset and 0.108 and 0 for the ordered rainfall–runoff dataset. Runoff estimation was very sensitive to λ and it improved consistently as λ changed from 0.2 to 0.03. © 2016, Springer-Verlag Berlin Heidelberg.
Citation: Hydrogeology Journal (2017), 25(1): 151-167
URI: https://doi.org/10.1007/s10040-016-1460-5
http://repository.iitr.ac.in/handle/123456789/15041
Issue Date: 2017
Publisher: Springer Verlag
Keywords: Agricultural
Curve number
Infiltration capacity
Initial abstraction coefficient
ISSN: 14312174
Author Scopus IDs: 56203222900
55463271000
55851948174
7401527632
56513694100
56203290400
57190848080
57205122003
55085038300
Author Affiliations: Lal, M., Department of Water Resources Development and Management, Indian Institute of Technology, Roorkee, Uttarakhand 247667, India, Irrigation and Drainage Engineering Department, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, Uttarakhand 263145, India
Mishra, S.K., Department of Water Resources Development and Management, Indian Institute of Technology, Roorkee, Uttarakhand 247667, India
Pandey, A., Department of Water Resources Development and Management, Indian Institute of Technology, Roorkee, Uttarakhand 247667, India
Pandey, R.P., National Institute of Hydrology, Roorkee, Uttarakhand 247667, India
Meena, P.K., Department of Water Resources Development and Management, Indian Institute of Technology, Roorkee, Uttarakhand 247667, India
Chaudhary, A., Ministry of Irrigation, Kathmandu, Nepal
Jha, R.K., Ministry of Irrigation, Kathmandu, Nepal
Shreevastava, A.K., Ministry of Irrigation, Kathmandu, Nepal
Kumar, Y., Irrigation and Drainage Engineering Department, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, Uttarakhand 263145, India
Corresponding Author: Lal, M.; Irrigation and Drainage Engineering Department, Govind Ballabh Pant University of Agriculture and TechnologyIndia; email: mohan841987@gmail.com
Appears in Collections:Journal Publications [WR]

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