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Runoff Curve Numbers at the Agricultural Field‐Scale and Implications for Continuous Simulation Modeling
Author(s) -
McGinley Paul M.,
Freihoefer Adam T.,
Mentz Randy S.
Publication year - 2013
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/jawr.12097
Subject(s) - surface runoff , runoff curve number , storm , environmental science , runoff model , hydrology (agriculture) , precipitation , continuous simulation , meteorology , geology , computer science , geography , simulation , ecology , geotechnical engineering , biology
Abstract This study used monitoring in the waterways of agricultural fields to understand the use of the runoff curve number ( CN ) in continuous simulation models. The CN has a long history as a design tool for estimating runoff volumes for large, single storms on small watersheds, but its use in continuous simulation models to describe runoff from smaller storms and relatively small areas is more recent and controversial. We examined 788 nonwinter rainfall events on four agricultural fields over five years (2004‐2008) during which runoff was generated in 87 events. The largest 20 runoff events on each field generated approximately 90% of the total runoff volume. The runoff event CN s showed an inverse correlation with storm depth that could not consistently be explained by previous precipitation. We review how small areas of higher runoff generation within larger areas will systematically increase the apparent CN of the larger area as the storm size decreases. If this variation is not incorporated into a model explicitly, continuous simulation modelers must understand that when source areas are aggregated or when runoff generation is spatially variable, the overall CN is not unique when smaller storms are included in the calibration set.