Assessing watershed transport of atrazine and nitrate to evaluate conservation practice effects and advise future monitoring strategies |
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Authors: | O'Donnell T Kevin |
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Affiliation: | (1) Department of Soil, Environmental, and Atmospheric Sciences, University of Missouri, 302 ABNR Building, Columbia, MO 65211, USA;(2) U.S. EPA - Great Lakes National Program Office, 77 West Jackson Blvd. (G-17J), Chicago, IL 60604, USA |
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Abstract: | Continued public support for U.S. taxpayer funded programs aimed at reducing agricultural pollutants depends on clear demonstrations of water quality improvements. The objective of this research was to determine if implementation of agricultural best management practices (BMPs) in the Goodwater Creek Experimental Watershed (GCEW) resulted in changes to atrazine and nitrate (NO3–N) loads during storm events. An additional objective was to estimate future monitoring periods necessary to detect a 5, 10, 20, and 25% reduction in atrazine and NO3–N event load. The GCEW is a 73 km2 watershed located in northcentral Missouri, USA. Linear regressions and Akaike Information Criteria were used to determine if reductions in atrazine and NO3–N event loads occurred as BMPs were implemented. No effects due to any BMP type were indicated for the period of record. Further investigation of event sampling from the long-term GCEW monitoring program indicated errors in atrazine load calculations may be possible due to pre-existing minimum threshold levels used to trigger autosampling and sample compositing. Variation of event loads was better explained by linear regressions for NO3–N than for atrazine. Decommissioning of upstream monitoring stations during the study period represented a missed opportunity to further explain variation of event loads at the watershed outlet. Atrazine requires approximately twice the monitoring period relative to NO3–N to detect future reductions in event load. Appropriate matching of pollutant transport mechanisms with autosampling protocols remains a critical information need when setting up or adapting watershed monitoring networks aimed at detecting watershed-scale BMP effects. |
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