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ARS Home » Midwest Area » Columbus, Ohio » Soil Drainage Research » Research » Publications at this Location » Publication #153088
Title: COMPARISON OF TRUE LOADS TO VARIOUS TIME-BASED SAMPLING

Author
item King, Kevin
item Harmel, Daren
item Zwierschke, Eric

Submitted to: ASAE Annual International Meeting
Publication Type: Proceedings
Publication Acceptance Date: 5/30/2003
Publication Date: 7/27/2003
Citation: KING, K.W., HARMEL, R.D., ZWIERSCHKE, E.L. COMPARISON OF TRUE LOADS TO VARIOUS TIME-BASED SAMPLING. 2003. AMERICAN SOCIETY FOR AGRICULTURAL ENGINEERING. PAPER NO. 03 2178.

Interpretive Summary:

Technical Abstract: Estimates of water quality loadings are often taken without any knowledge of the relation of the estimates to the true loads. A laboratory runoff simulation study was designed and conducted to compare true loads with several time-based sampling schemes. True loads were measured for three constituents (NO3+NO2-N, NH4-N, and PO4-P) on three 2.2m2 plots topped with bermudagrass (Cynodon dactylon L. Pers.) sod and set at a 5% slope. Water samples were manually collected on 1-min intervals for a runoff duration of 2-hr. The true loads were compared to an array of time-discrete and time-composite sampling schemes. The schemes included time-discrete sampling at 1, 2, 3, 4, 5, 10, 15, and 30-min and composite sampling that included 2, 3, 4, and 5 sample composites based on the same time-discrete intervals as well as a single composite sample collected at 1-min intervals. Time-discrete sampling at 1-min intervals was the only discrete sampling scheme that produced load calculations not statistically different ( = 0.05) from the true loads. A single composite sample based on 1-min interval sampling and a 5 sample composite based on 1-min intervals were the only tested composite schemes that produced loads not significantly different from the true loads. To preserve the true load from plot-scale studies, more intensive sampling is required. The results from this study will facilitate the selection of time-based sampling strategies for small plot studies.