2014
DOI: 10.1039/c4em00100a
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Understanding nutrient biogeochemistry in agricultural catchments: the challenge of appropriate monitoring frequencies

Abstract: We evaluate different frequencies of riverine nutrient concentration measurement to interpret diffuse pollution in agricultural catchments. We focus on three nutrient fractions, nitrate-nitrogen (NO3-N), total reactive phosphorus (TRP) and total phosphorus (TP) observed using conventional remote laboratory-based, low-frequency sampling and automated, in situ high-frequency monitoring. We demonstrate the value of low-frequency routine nutrient monitoring in providing long-term data on changes in surface water a… Show more

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Cited by 47 publications
(61 citation statements)
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References 63 publications
(140 reference statements)
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“…Sampling at low (weekly or longer) frequency fails to capture many of the complex and potentially rapid changes in river nutrient signals linked to hydrological and in-stream biogeochemical drivers (Bowes et al, 2009b;Kirchner et al, 2004), and often results in large errors in load estimations due to missing intermittent high or low nutrient concentrations during storm events (Bowes et al, 2009b;Johnes, 2007;Rozemeijer et al, 2010). Over the last decade, technological advances in auto-analyser and probe design have allowed high-frequency long-term nutrient concentration data to be produced for the first time, giving new insights into riverine P and N dynamics and sources (Bieroza et al, 2014;Bowes et al, 2012b;Gkritzalis-Papadopoulos et al, 2012;Jordan et al, 2007;Palmer-Felgate et al, 2008;Rozemeijer et al, 2010;Wade et al, 2012). This monitoring has revealed the presence of diurnal nutrient cycling, and rapid concentration changes through individual storm events (Bowes et al, 2012b;Jordan et al, 2005;Palmer-Felgate et al, 2008;Wade et al, 2012).…”
Section: Introductionmentioning
confidence: 99%
“…Sampling at low (weekly or longer) frequency fails to capture many of the complex and potentially rapid changes in river nutrient signals linked to hydrological and in-stream biogeochemical drivers (Bowes et al, 2009b;Kirchner et al, 2004), and often results in large errors in load estimations due to missing intermittent high or low nutrient concentrations during storm events (Bowes et al, 2009b;Johnes, 2007;Rozemeijer et al, 2010). Over the last decade, technological advances in auto-analyser and probe design have allowed high-frequency long-term nutrient concentration data to be produced for the first time, giving new insights into riverine P and N dynamics and sources (Bieroza et al, 2014;Bowes et al, 2012b;Gkritzalis-Papadopoulos et al, 2012;Jordan et al, 2007;Palmer-Felgate et al, 2008;Rozemeijer et al, 2010;Wade et al, 2012). This monitoring has revealed the presence of diurnal nutrient cycling, and rapid concentration changes through individual storm events (Bowes et al, 2012b;Jordan et al, 2005;Palmer-Felgate et al, 2008;Wade et al, 2012).…”
Section: Introductionmentioning
confidence: 99%
“…Data collected in monitoring programmes that involve sampling at regular time intervals (e.g. monthly) are often used to calibrate water quality models, but these are unlikely to fully represent the range of hydrologic conditions in a catchment (Bieroza et al, 2014). In particular, water quality data collected during storm flow periods are rarely available for SWAT calibration, thus prohibiting opportunities to investigate how parameter sensitivity varies under conditions which can contribute disproportionately to nutrient or sediment transport, particularly in lower-order catchments (Chiwa et al, 2010;.…”
Section: Introductionmentioning
confidence: 99%
“…While field-based studies [Burns, 1998;Peterson et al, 2001;Duff et al, 2008;Mulholland et al, 2008Mulholland et al, , 2009Tank et al, 2008;Hall et al, 2009;Mulholland and Webster, 2010] and modeling approaches [Jaworski et al, 1992;Boynton et al, 1995;Alexander et al, 2000Alexander et al, , 2009Seitzinger et al, 2002;Boyer et al, 2006;Runkel, 2007;Ator and Denver, 2012] have provided much needed information on reach and watershed-scale nitrate dynamics, the limited spatial extent and/or low temporal resolution of discrete data collection continues to be a challenge for quantifying loads and interpreting drivers of change in watersheds. Recent studies have demonstrated that the collection and interpretation of high-frequency nitrate data collected using water quality sensors can be used to better quantify nitrate loads to sensitive stream and coastal environments [Ferrant et al, 2013;Bieroza et al, 2014;Pellerin et al, 2014], and provide insights into temporal nitrate dynamics that would otherwise be difficult to obtain using traditional field-based mass balance, solute injection, and/or isotopic tracer studies [Pellerin et al, 2009[Pellerin et al, , 2012Heffernan and Cohen, 2010;Sandford et al, 2013;Carey et al, 2014;Hensley et al, 2014Hensley et al, , 2015Outram et al, 2014;Crawford et al, 2015]. Coupling these measurements with techniques for quantifying water sources and/or flow paths [Gilbert et al, 2013;Bowes et al, 2015;Duncan et al, 2015] provides further opportunity for understanding and managing the drivers of coastal eutrophication.…”
Section: Introductionmentioning
confidence: 99%