Uncertainties on nitrate water quality indicators associated with infrequent sampling in Brittany, France

Bírgand, François; Faucheux, Claire; Moatar, Florentina; Meybeck, Michel

doi:10.13031/2013.27431

Cited by 3 publications

(2 citation statements)

References 17 publications

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“…Numerous studies have focused on comparing different methods for estimating nutrient loads, particularly nitrate-nitrogen (NO 3 -N), and assessing their uncertainties. High-resolution datasets and Monte Carlo sub-sampling were used to evaluate the performance of various load estimation methods at different sampling frequencies [2,3]. The flow-weighted average concentration ratio method and error correction techniques were found to improve load estimate accuracy.…”

Section: Introductionmentioning

confidence: 99%

“…Despite the numerous studies focused on improving nutrient load estimation techniques and addressing their uncertainties [2][3][4][5][7][8][9][10][11][12], there is still a need for further research on the influence of sampling frequency and estimation methods on the uncertainty of nutrient load estimates under different seasonal and hydrological conditions, especially during high-flow seasons and extreme precipitation events. This study aims to address the knowledge gap by focusing on an agricultural watershed dominated by non-point source pollution in the Yiluo River Basin, China.…”

Section: Introductionmentioning

confidence: 99%

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Optimizing Sampling Strategies for Estimating Riverine Nutrient Loads in the Yiluo River Watershed, China

Zhang,

Xu,

et al. 2024

Water

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Accurately estimating nutrient loads is crucial for effective management and monitoring of aquatic ecosystems. This study evaluated the uncertainty in different sampling frequencies and calculation methods for estimating total nitrogen (TN) and total phosphorus (TP) loads in the Yiluo River watershed, a tributary of the Yellow River in China. Using daily TN and TP concentration data from 2019 to 2020, we conducted a bootstrapping analysis to evaluate the accuracy of nine different load estimation methods at different sampling frequencies. Our results showed that Method 3 (M_3, constant concentration interpolation) and Method 7 (M_7, flow-weighted concentration method), when used with a biweekly sampling frequency, had the lowest Standard Deviation of the Percentage errors (STD) (7.70% and 8.60% for TN, 12.0% and 18.8% for TP, respectively) and Mean Relative Error (MRE) values (0.078% and −1.60% for TN, 0.305% and 2.33% for TP, respectively) on an annual scale. For monthly TN and TP load estimates, M_7 can control the MRE within ±20% at a biweekly sampling frequency. Furthermore, the uncertainty in TN and TP load estimates was generally larger during the summer months (June–September), emphasizing the important role of storm events in nutrient export. Extreme events (<10% of the time) contributed approximately 50% of the annual nutrient loads. The findings of this study provide a scientific basis for optimizing water quality monitoring schemes and management strategies in agricultural watersheds.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimizing Sampling Strategies for Estimating Riverine Nutrient Loads in the Yiluo River Watershed, China

Zhang,

Xu,

et al. 2024

Water

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

Bírgand¹,

Faucheux²,

Gruau³

et al. 2010

Transactions of the ASABE

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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.

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High-Frequency Nitrate Monitoring in Dynamic River Systems

Banerjee¹

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High frequency water quality monitoring presents unique and unlimited opportunities of exploring spatio-temporal variation in water quality. Knowledge gained from analyzing high frequency water quality data can provide more clarity regarding transportation and processing of water constituents over time and space and scale. This study analyzes high frequency discharge, nitrate load and concentration data for three watersheds of different sizes-Cedar River Watershed, North Raccoon and Middle Raccoon. Each of these sites were monitored for 2-3 calendar years. Sudden spikes in discharge, nitrate concentration and load data, also defined as "events" were analyzed in great detail to understand the patterns in event occurrence and event intensity. Smaller watersheds seemed to have sharper and "flashier" events compared to bigger watersheds. Nitrate concentration events were flatter in shape compared to discharge and nitrogen load events. The relationship between nitrogen concentration and discharge was found to be varying over time, unlike the relationship between nitrate load and discharge, which were almost perfectly correlated for most siteyear combinations. Based on more than 40,000 simulations, it was determined that high frequency water quality sampling is not only efficient in capturing minute spatio-temporal variations but can also capture nitrate exceedances to a greater degree. High frequency sampling was also associated with higher yield ratio in nitrate load estimates, not only during high flow periods, but also during the non-high-flow period. vi

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Uncertainties on nitrate water quality indicators associated with infrequent sampling in Brittany, France

Cited by 3 publications

References 17 publications

Optimizing Sampling Strategies for Estimating Riverine Nutrient Loads in the Yiluo River Watershed, China

Optimizing Sampling Strategies for Estimating Riverine Nutrient Loads in the Yiluo River Watershed, China

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

High-Frequency Nitrate Monitoring in Dynamic River Systems

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