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

机译:评估年度硝酸盐负荷和浓度指标的不确定性:第1部分。采样频率和负荷估算算法的影响

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摘要

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 km²) 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
机译:这项研究的目的是评估由不频繁采样和用于计算通量的算法引起的年度硝酸盐负荷和浓度(例如年平均浓度和中位数浓度)的不确定性。从法国布列塔尼的9个流域(5至252km²)收集的每小时到日流量和浓度数据的总共50个分水年进行了分析。对原始(高频)硝酸盐浓度和流量数据进行了数值采样,以模拟常见的采样频率。将模拟样品计算出的年通量和浓度指标与高频数据计算出的参考值进行比较。还量化了几种用于计算年通量的算法带来的不确定性。在所有情况下,不确定性都随着采样间隔的增加而增加。结果表明,所有不使用连续流量数据来计算硝酸盐通量的经过测试的算法都带来了相当大的不确定性。发现流量加权平均浓度比方法在50个年度数据集中表现最佳。对偏差值的分析表明,从长远来看,第90和第95个百分位数以及最大浓度值往往会被系统低估,但负荷估算(使用所选算法)以及平均和中值浓度相对无偏。在大小不同的流域之间以及特定流域的年份之间,都可以观察到负荷估算算法精度的巨大差异。这阻止了在这项初步工作中对硝酸盐含量和浓度进行明确的不确定性预测,但表明水文因素(例如流域水文反应性)可能是预测不确定性水平的关键因素

著录项

  • 来源
    《Transactions of the ASABE》 |2010年第2期|p.437-446|共10页
  • 作者单位

    François Birgand, ASABE Member Engineer, Assistant Professor, Department of Biological and Agricultural Engineering, North Carolina State University, Raleigh, North Carolina;

    C laire Faucheux, Research Consultant, Geovariances, Avon, France;

    Gérard Gruau, Professor, CNRS-CAREN, Rennes, France;

    Bénédicte Augeard, Research Scientist, Cemagref, Antony, France;

    Florentina Moatar, Associate Professor, Laboratoire de Géologie des Environnements Aquatiques Continentaux , Université de Tours, France;

    and Paul Bordenave, Research Scientist, Cemagref, Bordeaux, France. Corresponding author: François Birgand, Department of Biological and Agricultural Engineering, Box 7625, North Carolina State University, Raleigh, NC 27695-7625;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Concentration indicators; Measurement uncertainty; Nitrate; Nutrient fluxes; Sampling strategies; Water quality; Watershed;

    机译:浓度指标;测量不确定度;硝酸盐营养通量;抽样策略;水质;分水岭;

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