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Compared performances of different algorithms for estimating annual nutrient loads discharged by the eutrophic River Loire

机译:估算富营养化卢瓦尔河排放的年度养分的不同算法的比较性能

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Good estimates of pollutant fluxes are required for Earth systems sciences and water quality management. The gradual accumulation of water quality data records over the past few decades has increased the value of these data for examining long-term trends. On many major rivers, however, infrequent sampling of most pollutants makes flux estimates and their analysis difficult. This paper explores the performance of different methods for estimating nutrient fluxes. The objective is to assess the accuracy (bias) and precision (dispersion) of annual nutrient fluxes based on monthly sampling, which is the frequency with which 80% of French water quality surveys have been carried out since 1971. The study is based on a data set of nutrient concentrations surveyed at high frequency during a 5 year pilot study (1981-85) at the Orleans station in the middle reaches of the River Loire, France. The mean specific fluxes were 641 (nitrate-N), 96 (total-P) and 37 kg year~(-1) km~(-2) (orthophosphate-P). For each year, the data set was then 'resampled' by randomly simulating 12 sampling dates. 100 simulated monthly samplings were generated, upon which seven estimation methods were tested. The evaluations indicate that, when concentrations of specific substances in large rivers exhibit seasonal variation, a simple method based on linear interpolation between samples taken at approximately monthly intervals is advocated. With the monthly sampling interval, the precision (confidence level of 95%) of annual nutrient fluxes obtained by the appropriate methods was 13% for nitrates, 20% for total-P, 26% for orthophosphates, and 34% for particulate-P. The frequency of water quality surveys required to obtain an annual nutrient flux with 10% precision was around 15 days for nitrate, 10 days for orthophosphate-P and total-P, and about 5 days in the case of particulate-P.
机译:地球系统科学和水质管理需要对污染物通量进行良好的估算。在过去的几十年中,水质数据记录的逐步积累增加了这些数据在检验长期趋势方面的价值。但是,在许多主要河流上,大多数污染物的采样很少,因此很难进行通量估算及其分析。本文探讨了估算养分通量的不同方法的性能。目的是根据每月抽样评估年度养分通量的准确性(偏差)和精度(分散性),这是自1971年以来法国进行的80%水质调查的频率。在法国卢瓦尔河中游奥尔良站进行的为期5年的试验研究(1981-85年)中,对高频营养物浓度进行的数据收集。平均比通量为641(硝酸盐-N),96(总P)和37 kg年〜(-1)km〜(-2)(正磷酸盐-P)。对于每一年,然后通过随机模拟12个采样日期对数据集进行“重新采样”。生成了100个模拟的每月抽样,并测试了7种估计方法。评价表明,当大河流中特定物质的浓度呈现季节性变化时,提倡一种基于线性插值的简单方法,该方法以大约每月的时间间隔采样。在每月采样间隔内,通过适当方法获得的年度养分通量的精确度(置信度为95%)为硝酸盐为13%,总磷为20%,正磷酸盐为26%,微粒P为34%。获得10%精度的年度养分通量所需的水质调查频率对于硝酸盐大约为15天,对于正磷酸盐P和总P为10天,对于颗粒P为大约5天。

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