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Hydrograph Separation by Incorporating Climatological Factors: Application to Small Experimental Watersheds 1
Author(s) -
Nejadhashemi Amir P.,
Sheridan Joseph M.,
Shirmohammadi Adel,
Montas Hubert J.
Publication year - 2007
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/j.1752-1688.2007.00059.x
Subject(s) - hydrograph , streamflow , watershed , base flow , surface runoff , time of concentration , environmental science , hydrology (agriculture) , evapotranspiration , scale (ratio) , runoff model , subsurface flow , drainage basin , geology , computer science , geography , groundwater , biology , ecology , cartography , geotechnical engineering , machine learning
Evaluating the relative amounts of water moving through the different components of the hydrological cycle is required for precise management and planning of water resources. An important aspect of this evaluation is the partitioning of streamflow into surface (quick flow) and base‐flow components. A prior study evaluated 40 different approaches for hydrograph‐partitioning on a field scale watershed in the Coastal Plain of the Southeastern United States and concluded that the Boughton’s method produced the most consistent and accurate results. However, its accuracy depends upon the proper estimation of: (1) the end of surface runoff, and (2) the fraction factor ( α ) that is function of many physical and hydrologic characteristics of a watershed. Proper identification of the end of surface runoff was accomplished by using a second derivative approach. Applying this approach to 12 years of separately measured surface and subsurface flow data from a field scale watershed (study area) proved to be accurate for 87% of the time. Estimation of the α value was accomplished in this study using two steps: (1) alpha was fitted to individual hydrographs: and, (2) a regression equation that determines these alpha values based on climatological factors (e.g., rainfall, evapotranspiration) was developed. Using these strategies improved the streamflow partitioning method’s performance significantly.