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      New Seasonal Shift in In-Stream Diurnal Nitrate Cycles Identified by Mining High-Frequency Data

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          Abstract

          The recent development of in-situ monitoring devices, such as UV-spectrometers, makes the study of short-term stream chemistry variation relevant, especially the study of diurnal cycles, which are not yet fully understood. Our study is based on high-frequency data from an agricultural catchment (Studienlandschaft Schwingbachtal, Germany). We propose a novel approach, i.e. the combination of cluster analysis and Linear Discriminant Analysis, to mine from these data nitrate behavior patterns. As a result, we observe a seasonality of nitrate diurnal cycles, that differs from the most common cycle seasonality described in the literature, i.e. pre-dawn peaks in spring. Our cycles appear in summer and the maximum and minimum shift to a later time in late summer/autumn. This is observed both for water- and energy-limited years, thus potentially stressing the role of evapotranspiration. This concluding hypothesis on the role of evapotranspiration on nitrate stream concentration, which was obtained through data mining, broadens the perspective on the diurnal cycling of stream nitrate concentrations.

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          High-frequency nutrient monitoring to infer seasonal patterns in catchment source availability, mobilisation and delivery

          To explore the value of high-frequency monitoring to characterise and explain riverine nutrient concentration dynamics, total phosphorus (TP), reactive phosphorus (RP), ammonium (NH4-N) and nitrate (NO3-N) concentrations were measured hourly over a 2-year period in the Duck River, in north-western Tasmania, Australia, draining a 369-km(2) mixed land use catchment area. River discharge was observed at the same location and frequency, spanning a wide range of hydrological conditions. Nutrient concentrations changed rapidly and were higher than previously observed. Maximum nutrient concentrations were 2,577 μg L(-1) TP, 1,572 μg L(-1) RP, 972 μg L(-1) NH₄-N and 1,983 μg L(-1) NO₃-N, respectively. Different nutrient response patterns were evident at seasonal, individual event and diurnal time scales-patterns that had gone largely undetected in previous less frequent water quality sampling. Interpretation of these patterns in terms of nutrient source availability, mobilisation and delivery to the stream allowed the development of a conceptual model of catchment nutrient dynamics. Functional stages of nutrient release were identified for the Duck River catchment and were supported by a cluster analysis which confirmed the similarities and differences in nutrient responses caused by the sequence of hydrologic events: (1) a build-up of nutrients during periods with low hydrologic activity, (2) flushing of readily available nutrient sources at the onset of the high flow period, followed by (3) a switch from transport to supply limitation, (4) the accessibility of new nutrient sources with increasing catchment wetness and hydrologic connectivity and (5) high nutrient spikes occurring when new sources become available that are easily mobilised with quickly re-established hydrologic connectivity. Diurnal variations that could be influenced by riverine processes and/or localised point sources were also identified as part of stage (1) and during late recession of some of the winter high flow events. Illustrated by examples from the Duck River study, we demonstrate that the use of high-frequency monitoring to identify and characterise functional stages of catchment nutrient release is a constructive approach for informing and supporting catchment management and future nutrient monitoring strategies.
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            Nitrogen cycling in natural waters using in situ, reagentless UV spectrophotometry with simultaneous determination of nitrate and nitrite.

            Reliable, high temporal, and spatial resolution data is essential for enhancing our understanding of aquatic nitrogen biogeochemical cycling. This paper describes a novel UV spectrophotometric sensor (ProPS, TriOS GmbH, Oldenburg, Germany) for the real time, in situ, high resolution simultaneous mapping of nitrate/nitrite (linearity 0.01 - 6 mg N L(-1), RSD's NO3-N 4-10%, NO2-N 7-14%) in fresh and estuarine waters. Good agreement (t test at p = 0.05) was found with MOOS-1 certified reference material and with reference segmented flow analysis data. River Taw deployments identified a diurnal cycle for NO3-N (0.22-0.63 mg L(-1), RSD 3.9%) and for NO2-N (0.01-0.28 mg L(-1), RSD 12.4%) with the photo-oxidation of dissolved organic nitrogen a source of diurnal nitrate/nitrite, and a large cyclical amplitude (30-62% of mean nitrate/nitrite). In situ Tamar Estuary nitrate/nitrite concentrations, mapped through the salinity gradient, were strongly correlated with suspended particulate material and inversely correlated with dissolved oxygen and pH, indicating midestuarine, bacterially mediated nitrification/denitrification, with the raised estuarine nitrite also significantly correlated with particulate organic nitrogen. Such previously unquantified inputs have important implications for N loadings calculated from coarse scale sampling and laboratory analysis, pollution assessment, and our understanding of the biological rhythms of aquatic organisms.
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              Fractal Water Quality Fluctuations Spanning the Periodic Table in an Intensively Farmed Watershed

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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                13 April 2016
                2016
                : 11
                : 4
                : e0153138
                Affiliations
                [001]Institute for Landscape Ecology and Resources Management (ILR), Research Centre for BioSystems, Land Use and Nutrition (IFZ), Justus Liebig University Giessen, Heinrich-Buff-Ring 26, Giessen, Germany
                CAS, CHINA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: AHA LB. Performed the experiments: AHA LB. Analyzed the data: AHA LB. Contributed reagents/materials/analysis tools: AHA LB. Wrote the paper: AHA LB.

                [¤]

                Current address: ESS, Eawag, Überlandstrasse 133, Dübendorf, Switzerland

                Article
                PONE-D-15-50835
                10.1371/journal.pone.0153138
                4830558
                27073838
                5885cd0a-1a53-43f4-a564-db8b7d6749c8
                © 2016 Aubert, Breuer

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 21 November 2015
                : 24 March 2016
                Page count
                Figures: 3, Tables: 2, Pages: 12
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Physical Sciences
                Chemistry
                Chemical Compounds
                Nitrates
                Physical Sciences
                Physics
                Electromagnetic Radiation
                Solar Radiation
                Computer and Information Sciences
                Information Technology
                Data Mining
                Earth Sciences
                Atmospheric Science
                Meteorology
                Rain
                Ecology and Environmental Sciences
                Soil Science
                Edaphology
                Earth Sciences
                Geology
                Petrology
                Sediment
                Earth Sciences
                Geology
                Sedimentary Geology
                Sediment
                Earth Sciences
                Hydrology
                Surface Water
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Linear Discriminant Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Linear Discriminant Analysis
                Custom metadata
                Data following the quality check are available at doi: 10.1594/PANGAEA.859204 ( https://doi.pangaea.de/10.1594/PANGAEA.859204).

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                Uncategorized

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