Continuous measurement of nitrate concentration in a highly event‐responsive agricultural catchment in south‐west of France: is the gain of information useful?. Issue 12 (12th May 2012)

• Record Type: Journal Article
• Authors: Ferrant, S.; Laplanche, C.; Durbe, G.; Probst, A.; Dugast, P.; Durand, P.; Sanchez‐Perez, J. M.; Probst, J. L.
• Is Part Of: Hydrological processes. Volume 27:Issue 12(2013:Jun. 15)
• Page Start: 1751
• Page End: 1763
• Publication Date: 2012-05-12
• Subjects: Hydrology -- Periodicals; Hydrology -- Research -- Periodicals; Hydrologic models -- Periodicals; Hydrological forecasting -- Periodicals; 631.432
• DOI: 10.1002/hyp.9324
• Languages: English
• ISSNs: 0885-6087

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>A 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 <italic>in situ</italic> 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 <italic>in situ</italic> 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. Copyright © 2012 John Wiley & Sons, Ltd.</p> </abstract>