Continuous measurement of nitrate concentration in a highly event‐responsive agricultural catchment in south‐west of France: is the gain of information useful?

Abstract

International audienceA nitrate sensor has been set up to measure every 10 min the nitrate signal in a stream draining a small agricultural catchment dominated by fertilized crops during a 2-year study period (2006-2008) in the south-west of France. An in situ sampling protocol using automatic sampler to monitor flood events have been used to assume a point-to-point calibration of the sensor values. The nitrate concentration exhibits nonsystematic concentration and dilution effects during flood events. We demonstrate that the calibrated nitrate sensor signal gathered from the outlet is considered to be a continuous signal using the Nyquist-Shannon sampling theorem. The objectives of this study are to quantify the errors generated by a typical infrequent sampling protocol and to design appropriate sampling strategy according to the sampling objectives. Nitrate concentration signal and flow data are numerically sampled to simulate common sampling frequencies. The total fluxes calculated from the simulated samples are compared with the reference value computed on the continuous signal. Uncertainties are increasing as sampling intervals increase; the method that is not using continuous discharge to compute nitrate fluxes bring larger uncertainty. The dispersion and bias computed for each sampling interval are used to evaluate the uncertainty during each hydrological period. High underestimation is made during flood periods when high-concentration period is overlooked. On the contrary, high sampling frequencies (from 3 h to 1 day) lead to a systematic overestimation (bias around 3%): highest concentrations are overweighted by the interpolation of the concentration in such case. The in situ sampling protocol generates less than 1% of load estimation error and sample highest concentration peaks. We consider useful such newly emerging field technologies to assess short-term variations of water quality parameters, to minimize the number of samples to be analysed and to assess the quality state of the stream at any time

Quantifying watershed‐scale groundwater loading and in‐stream fate of nitrate using high‐frequency water quality data

“…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.…”

Upland streamwater nitrate dynamics across decadal to sub-daily timescales: a case study of Plynlimon, Wales

“…These studies have also tended to focus on single-site installations and often measurements have only been made during one hydrological year (e.g. Chapin et al, 2004;Ferrant et al, 2012;Parker et al, 2007). Whilst these studies are pioneering in many ways, their short durations make the evaluation of the observed sub-daily dynamics and their importance to the overall NO 3 cycle difficult to quantify, because it is not possible to place the dynamics within the wider context of NO 3 variability.…”

“…The Hafren catchment has an area of 3.6 km 2 (of which the Upper Hafren is 1.2 km 2 ) with an altitudinal range of 355-670 m (Brandt et al, 2004;Marsh and Hannaford, 2008). The bedrock geology is base-poor and comprises fractured Lower Palaeozoic slate, mudstone, greywacke and sandstone (Foster et al, 2001;Godsey et al, 2010). The landscape has been influenced by Quaternary glaciation, with periglacial activity leaving remnants of locally derived overlying boulder clay and till (Brandt et al, 2004;Neal et al, 2010).…”

Extracting Soil Water Holding Capacity Parameters of a Distributed Agro-Hydrological Model from High Resolution Optical Satellite Observations Series

“…The geological substratum is essentially impermeable, which is highly favorable to surface and subsurface runoff (hereafter called lateral flow). The subsurface flows are responsible for the major geochemical transfer of nitrate [37], metals [38] and pesticides [39] at the watershed scale, especially during storm and flood events. The soil type is predominantly non-permeable clay-limestone.…”

“…Discharge and nitrate concentration were continuously recorded at the outlet of the catchment area using the continuous sampling protocol described in [37]. The crop succession was derived from Registre Parcellaire Graphique (RPG) database and the crop cover supervised classification of F2 and SPOT images.…”