Electrical Conductivity as a tool to estimate chemical properties of drainage water quality in the Des Moines Lobe, Iowa

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2012-07-01
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Soupir, Michelle
Helmers, Matthew
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Soupir, Michelle
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Agricultural and Biosystems Engineering
Abstract

Frequent sampling is needed to capture intra-event and seasonal fluctuations of nutrient concentrations for accurate load estimations to surface waters; however, processing water samples for multiple nutrients can be expensive and time consuming. The goal of this study is to investigate electrical conductivity as an inexpensive surrogate for traditional water quality sampling and analysis. This study is being conducted in a heavily tile-drained-agricultural watershed typical of the Des Moines Lobe region of Iowa, Hickory Grove Lake Watershed. This watershed has a unique setup where drained water from a drainage district of 879 ha flows into a single location where both surface runoff and drained water from the drainage district can be monitored separately. Electrical Conductivity (EC) meters, flow meters, and autosamplers (ISCOs) were installed at both surface and subsurface monitoring locations. The samples are being analyzed for nitrate (NO3-N), ammonium (NH4-N), and, total phosphorus (TP). The average EC at the tile drainage outlet and surface water monitoring location was 484 µS/cm and 519 µS/cm, respectively. The average daily nitrate concentrations in 2011 at the watershed outlet and drainage district outlet were 9.06 and 8.28 mg/L, respectively. An inverse relation between EC and flow was observed which is in agreement with findings from previous studies. Significant fluctuations were observed in all the nutrients monitored during runoff events. Better relationships between EC and nutrient concentrations could be used to estimate more accurate TMDLs during runoff events, and thus development of more accurate TMDLs. Rigorous monitoring in similar watersheds can help improve the efficiency of the relationships.

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This is an ASABE Meeting Presentation, Paper No. 121338083.

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Sun Jan 01 00:00:00 UTC 2012