Premium
Curve Number Derivation for Watersheds Draining Two Headwater Streams in Lower Coastal Plain South Carolina, USA
Author(s) -
Epps Thomas H.,
Hitchcock Daniel R.,
Jayakaran Anand D.,
Loflin Drake R.,
Williams Thomas M.,
Amatya Devendra M.
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.12084
Subject(s) - antecedent moisture , surface runoff , hydrology (agriculture) , watershed , storm , water table , environmental science , streams , runoff curve number , coastal plain , streamflow , table (database) , precipitation , geology , drainage basin , groundwater , meteorology , ecology , geography , computer network , paleontology , geotechnical engineering , computer science , oceanography , cartography , machine learning , biology , data mining
The objective of this study was to assess curve number ( CN ) values derived for two forested headwater catchments in the Lower Coastal Plain ( LCP ) of South Carolina using a three‐year period of storm event rainfall and runoff data in comparison with results obtained from CN method calculations. Derived CN s from rainfall/runoff pairs ranged from 46 to 90 for the Upper Debidue Creek ( UDC ) watershed and from 42 to 89 for the Watershed 80 (WS80). However, runoff generation from storm events was strongly related to water table elevation, where seasonally variable evapotranspirative wet and dry moisture conditions persist. Seasonal water table fluctuation is independent of, but can be compounded by, wet conditions that occur as a result of prior storm events, further complicating flow prediction. Runoff predictions for LCP first‐order watersheds do not compare closely to measured flow under the average moisture condition normally associated with the CN method. In this study, however, results show improvement in flow predictions using CN s adjusted for antecedent runoff conditions and based on water table position. These results indicate that adaptations of CN model parameters are required for reliable flow predictions for these LCP catchments with shallow water tables. Low gradient topography and shallow water table characteristics of LCP watersheds allow for unique hydrologic conditions that must be assessed and managed differently than higher gradient watersheds.