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ARS Home » Research » Publications at this Location » Publication #127525


item Van Liew, Michael
item Garbrecht, Jurgen
item Starks, Patrick

Submitted to: American Geophysical Union
Publication Type: Other
Publication Acceptance Date: 1/7/2002
Publication Date: 1/7/2002
Citation: N/A

Interpretive Summary:

Technical Abstract: The integrated effects of climatic, physiographic, and anthropogenic factors govern the hydrologic response of a watershed. In particular seasonal and inter-annual variations in precipitation lead to variations in streamflow that can affect downstream water availability, water quality, flood control, reservoir operation and low-flow management. To address such water resources related issues, the temporal variations of the streamflow must be quantified. This investigation evaluates the temporal variation of annual, monthly, and daily streamflow on four large experimental watersheds managed by the USDA Agricultural Research Service over a period of 26 years from 1972 to 1997. The four experimental watersheds are representative of four different ecosystems and runoff regimes, and include Reynolds Creek, ID, Walnut Gulch, AZ, Little Washita River, OK, and Little River, GA. The mean, standard deviation and coefficient of variation are computed for annual, monthly, and daily streamflow values for the four ARS locations, and resulting variability measures at the three time scales are illustrated in graphical format. Findings show that the annual variation in streamflow is strongly correlated to annual precipitation. Reynolds Creek and Little Washita River exhibit the smallest variation in monthly flows from year to year, while variations in flow are greatest during the fall months for the Little River and greatest during the spring and fall months for Walnut Gulch. Results demonstrate the uniqueness of temporal streamflow variations for each watershed, and uphold the need for a network of experimental watersheds that can be used to assess the hydrologic response of various ecosystems under changing boundary conditions associated with global change issues.