Articles | Volume 18, issue 11
https://doi.org/10.5194/hess-18-4721-2014
https://doi.org/10.5194/hess-18-4721-2014
Research article
 | 
28 Nov 2014
Research article |  | 28 Nov 2014

Comparison of sampling methodologies for nutrient monitoring in streams: uncertainties, costs and implications for mitigation

J. Audet, L. Martinsen, B. Hasler, H. de Jonge, E. Karydi, N. B. Ovesen, and B. Kronvang

Abstract. Eutrophication of aquatic ecosystems caused by excess concentrations of nitrogen and phosphorus may have harmful consequences for biodiversity and poses a health risk to humans via water supplies. Reduction of nitrogen and phosphorus losses to aquatic ecosystems involves implementation of costly measures, and reliable monitoring methods are therefore essential to select appropriate mitigation strategies and to evaluate their effects. Here, we compare the performances and costs of three methodologies for the monitoring of nutrients in rivers: grab sampling; time-proportional sampling; and passive sampling using flow-proportional samplers. Assuming hourly time-proportional sampling to be the best estimate of the "true" nutrient load, our results showed that the risk of obtaining wrong total nutrient load estimates by passive samplers is high despite similar costs as the time-proportional sampling. Our conclusion is that for passive samplers to provide a reliable monitoring alternative, further development is needed. Grab sampling was the cheapest of the three methods and was more precise and accurate than passive sampling. We conclude that although monitoring employing time-proportional sampling is costly, its reliability precludes unnecessarily high implementation expenses.

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Short summary
The mitigation of excess nitrogen and phosphorus in river waters requires costly measures. Therefore it is essential to use reliable monitoring methods to select adequate mitigation strategies. Here we show that more development is needed before passive samplers can be considered as reliable alternative for sampling nutrients in stream. We also showed that although continuous sampling is expensive, its reliability precludes unnecessarily high implementation costs of mitigation measures.