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首页> 外文期刊>Journal of the American Water Resources Association >A MULTI-AGENCY NUTRIENT DATASET USED TO ESTIMATE LOADS, IMPROVEMONITORING DESIGN, AND CALIBRATE REGIONAL NUTRIENT SPARROW MODELS
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A MULTI-AGENCY NUTRIENT DATASET USED TO ESTIMATE LOADS, IMPROVEMONITORING DESIGN, AND CALIBRATE REGIONAL NUTRIENT SPARROW MODELS

机译：用于评估负荷，改进监测设计和校准区域养分分布模型的多代理养分数据集

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摘要

Stream-loading information was compiled from federal, state, and local agencies, and selected universities as part of an effort to develop regional SPAtially Referenced Regressions On Watershed attributes (SPARROW) models to help describe the distribution, sources, and transport of nutrients in streams throughout much of the United States. After screening, 2,739 sites, sampled by 73 agencies, were identified as having suitable data for calculating long-term mean annual nutrient loads required for SPARROW model calibration. These sites had a wide range in nutrient concentrations, loads, and yields, and environmental characteristics in their basins. An analysis of the accuracy in load estimates relative to site attributes indicated that accuracy in loads improve with increases in the number of observations, the proportion of uncensored data, and the variability in flow on observation days, whereas accuracy declines with increases in the root mean square error of the water-quality model, the flow-bias ratio, the number of days between samples, the variability in daily streamflow for the prediction period, and if the load estimate has been detrended. Based on compiled data, all areas of the country had recent declines in the number of sites with sufficient water-quality data to compute accurate annual loads and support regional modeling analyses. These declines were caused by decreases in the number of sites being sampled and data not being entered in readily accessible databases.
机译：流负荷信息是从联邦，州和地方机构以及选定的大学中收集的，作为开发区域空间参考流域回归属性（SPARROW）模型的工作的一部分，以帮助描述流中养分的分布，来源和运输在美国大部分地区。筛选后，确定了73个机构采样的2739个站点，这些站点具有用于计算SPARROW模型校准所需的长期平均年营养负荷的合适数据。这些流域的营养元素含量，负荷和产量以及流域的环境特征变化很大。相对于站点属性的负荷估计准确性的分析表明，负荷的准确性随观察次数，未审查数据的比例以及观察日流量变化的增加而提高，而准确性随均方根的增加而下降水质模型的平方误差，流量偏比，样本之间的天数，预测期内每日流量的变化以及是否对负荷估算进行了反趋势化。根据汇编的数据，该国所有地区的站点数量最近都有所下降，其水质数据足以计算准确的年度负荷并支持区域模型分析。这些下降是由于采样的站点数量减少以及没有将数据输入易于访问的数据库而引起的。

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