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A novel method to reveal the nitrate transport and fate in agricultural fields

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

Citation:  2016 10th International Drainage Symposium Conference, 6-9 September 2016, Minneapolis, Minnesota  .(doi:10.13031/IDS.20162515024)
Authors:   Wenlong Liu, François Birgand, Mohamed Youssef, George Chescheir
Keywords:   Best Management Practices (BMPs), Drainage, Technology, Water Quality.

Abstract. Current knowledge of nitrate movement, fate and load in artificially drained agricultural fields has been built over decades from very incomplete spatio-temporal information on nitrate concentrations. There is evidence that significant uncertainties on nitrate annual loads can result from infrequent samples. Yet, all drainage water management practices and tools developed to reduce nitrogen loads to environmentally sensitive receiving waters and the mechanisms put forth to explain the observed reductions in nitrogen loads, have been derived from this sparse information. Consequently the relative roles of e.g., drainage volume, crop uptake, and denitrification, are still in debate for lack of spatial and temporal data that could help document the transformation and movement of nitrate in field experiments. In this paper, we propose to employ newly available continuous water quality probes to collect high frequency nitrate concentration and flow data at the outlet of agricultural drains, and at multiple locations in the shallow ground water using a multiplexed sampler system we developed coupled with the same probes. Using these two systems, i) we expect to more accurately estimate nitrate loads from several water management practices, ii) we will conduct uncertainty analyses among grab samples, composite samples and high frequency samples in agricultural fields, iii) we expect to provide more definite and quantitative explanation for observed nitrate loads across a variety of drainage management, and iv) we expect to update and enhance current best practice recommendations. The abstract is often the only part of the paper to be read, so include your major findings in a useful and concise manner. Include a problem statement, objectives, brief methods, quantitative results, and the significance of your findings. The abstract should be no more than 250 words long.

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