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Real-time monitoring of nutrients and dissolved organic matter in rivers: Capturing event dynamics, technological opportunities and future directions

Journal

SCIENCE OF THE TOTAL ENVIRONMENT
Volume 569, Issue -, Pages 647-660

Publisher

ELSEVIER
DOI: 10.1016/j.scitotenv.2016.06.116

Keywords

In-situ; High-frequency; Nitrate; Phosphate; DOC

Funding

  1. Natural Environment Research Council [NE/K010689/1, NE/K01093X/1] Funding Source: researchfish
  2. NERC [NE/K01093X/1, NE/L003872/1, NE/K010689/1] Funding Source: UKRI

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Excessive riverine nutrient concentrations threaten aquatic ecosystem structure and functioning and can pose substantial risks to human health. Robust monitoring strategies are therefore required to generate reliable estimates of river nutrient loads and to improve understanding of the catchment processes that drive nutrient fluxes. Furthermore, these data are vital for prediction of future trends under changing environmental conditions and thus the development of appropriate mitigation measures. In recent years, technological developments have led loan increase in the use of in-situ nutrient analysers, which enable measurements at far higher temporal resolutions than can be achieved with discrete sampling and subsequent laboratory analysis. In this paper, we review the principles underlying the key techniques used for in-situ nutrient monitoring and highlight both the advantages, opportunities and challenges associated with high-resolution sampling programs. We then suggest how adaptive monitoring strategies, comprising several different temporal sample frequencies, controlled by one or more 'trigger variables' (e.g. river stage, turbidity, or nutrient concentration), can advance our understanding of catchment nutrient dynamics while simultaneously overcoming many of the practical and economic challenges encountered in typical in-situ river nutrient monitoring applications. We present examples of short-term variability in river nutrient dynamics, driven by complex catchment behaviour, which support our case for the development of monitoring systems that can adapt in real-time to rapid changes in environmental conditions. Finally, we suggest future research directions based on emerging technologies in this field. (C) 2016 Elsevier B.V. All rights reserved.

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