Uncertainties in Assessing Annual Nitrate Loads and Concentration Indicators: Part 1. Impact of Sampling Frequency and Load Estimation Algorithms

Abstract

The objectives of this study are to evaluate the uncertainty in annual nitrate loads and concentrations (such as annual average and median concentrations) as induced by infrequent sampling and by the algorithms used to compute fluxes. A total of 50 watershed-years of hourly to daily flow and concentration data gathered from nine watersheds (5 to 252 km 2) in Brittany, France, were analyzed. Original (high frequency) nitrate concentration and flow data were numerically sampled to simulate common sampling frequencies. Annual fluxes and concentration indicators calculated from the simulated samples were compared to the reference values calculated from the high-frequency data. The uncertainties contributed by several algorithms used to calculate annual fluxes were also quantified. In all cases, uncertainty increased as sampling intervals increased. Results showed that all the tested algorithms that do not use continuous flow data to compute nitrate fluxes introduced considerable uncertainty. The flow-weighted average concentration ratio method was found to perform best across the 50 annual datasets. Analysis of the bias values suggests that the 90th and 95th percentiles and the maximum concentration values tend to be systematically underestimated in the long term, but the load estimates (using the chosen algorithm) and the average and median concentrations were relatively unbiased. Great variability in the precision of the load estimation algorithms was observed, both between watersheds of different sizes and between years for a particular watershed. This has prevented definitive uncertainty predictions for nitrate loads and concentrations in this preliminary work, but suggests that hydrologic factors, such as the watershed hydrological reactivity, could be a key factor in predicting uncertainty levels.

Incorporating Rainfall-Runoff Events into Nitrate-Nitrogen and Phosphorus Load Assessments for Small Tile-Drained Catchments

“…For both P forms monitored in drainage waters, no such differences were found. During the REs, a dilution of N-NO 3 in drainage waters usually prevailed, whilst for both P-PO 4 and P tot , the concentrations usually rose with elevated discharge, which is in accordance with many monitoring campaigns in tile-drained catchments [5,12,18,25,31]. The only exceptions were sites PD1 and PD2, with Cfw N-NO 3 higher in ESs than in RSs.…”

“…For nitrate-N load estimation, two methods have been recommended by numerous authors: (1) linear interpolation, a period weighted method, and (2) flow-weighted mean concentration, an averaging method [18,24,25]. Previous research has shown that the uncertainty due to infrequent sampling and nutrient load estimation approaches for drainage systems or small streams is often much greater than the uncertainty brought about by other steps in the sample collection process [25][26][27].…”

“…For nitrate-N load estimation, two methods have been recommended by numerous authors: (1) linear interpolation, a period weighted method, and (2) flow-weighted mean concentration, an averaging method [18,24,25]. Previous research has shown that the uncertainty due to infrequent sampling and nutrient load estimation approaches for drainage systems or small streams is often much greater than the uncertainty brought about by other steps in the sample collection process [25][26][27]. In general, the uncertainties in annual or monthly nutrient load estimates are reported to be influenced both by the sampling interval and the load assessment methods and tend to increase with an increasing sampling interval for the majority of load estimation algorithms [24,25,28].…”

“…Previous research has shown that the uncertainty due to infrequent sampling and nutrient load estimation approaches for drainage systems or small streams is often much greater than the uncertainty brought about by other steps in the sample collection process [25][26][27]. In general, the uncertainties in annual or monthly nutrient load estimates are reported to be influenced both by the sampling interval and the load assessment methods and tend to increase with an increasing sampling interval for the majority of load estimation algorithms [24,25,28]. Ratio methods are often reported as bei ng unsatisfactory compared with the two aforementioned simple methods.…”

“…To our knowledge, only a few studies have been published to compare monitoring approaches and nutrient load assessment methods for tile-drained fields or small catchments [6,25,27,31]. These studies often conclude that the most dominant factors influencing nutrient fluxes are precipitation characteristics and catchment hydrological connectivity.…”