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Tillage Practices Usage in Early Warning Prediction of Atrazine Pollution

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Transactions of the ASABE. 51(4): 1311-1321. (doi: 10.13031/2013.25247) @2008
Authors:   J. E. Quansah, B. A. Engel, I. Chaubey
Keywords:   Atrazine, Early warning prediction, St. Joseph watershed, SWAT, Tillage practices, Water quality.

Tillage and pesticide management are important factors controlling pesticide losses from agricultural watersheds. In this research, tillage activities were mapped from Landsat TM and MODIS data and were used in Soil and Water Assessment Tool (SWAT) model to simulate atrazine concentrations in the St. Joseph River in northeastern Indiana. The calibrated and validated model proved to be crucial in making early warning predictions and decisions on atrazine pollution. Average Nash-Sutcliffe efficiency (NSE) values of 0.56 and 0.70 were obtained for daily and monthly stream flow calibration, respectively, while those for validation were 0.55 and 0.79, respectively. The best NSE values ranged from 0.06 to 0.42 for daily atrazine calibrations at four locations within the watershed and from 0.01 to 0.29 during validation. Daily and monthly R2 values at the St. Joseph watershed outlet during the atrazine validation were 0.35 and 0.63, respectively. Although NSE values for some water quality stations were poor, predicted atrazine concentrations compared reasonably well to measured trends at the watershed outlet. Pollution peaks in simulated atrazine concentrations were also within days of measured atrazine concentrations. The research showed that the temporal and spatial trend of tillage activities, which influences the timing and location of atrazine applications, together with application amounts have significant impact on critical areas and concentration levels of atrazine pollution. Uncertainties in observed data could also affect the model outcome. The results showed the potential application in early warning prediction of atrazine pollution and can be used to make appropriate management decisions to mitigate this problem.

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