USING REGRESSION METHODS TO ESTIMATE STREAM PHOSPHORUS LOADS AT THE ILLINOIS RIVER, ARKANSAS
USING REGRESSION METHODS TO ESTIMATE STREAM PHOSPHORUS LOADS AT THE ILLINOIS RIVER, ARKANSAS
复制标题
使用回归方法估算阿肯色州伊利诺伊河的河流磷负荷
DOI：
10.13031/2013.13110
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发表时间：
2003
影响因子：
0.9
通讯作者：
R. Richards
中科院分区：
文献类型：
--
作者：
B. Haggard;T. Soerens;W. Green;R. Richards
总最大日负荷（TMDLs）的发展需要评估流中现有的成分负荷。需要准确估计组分负荷来校准TMDL开发的流域和水库模型。估计组分负荷的最佳方法是高频采样，特别是在风暴事件期间，以及通过流中某一点的组分的质量积分。大多数情况下，资源是有限的，离散的水质样本收集在固定的时间间隔，有时补充直接采样在风暴事件。当资源有限时，质量集成不是确定组成负荷的准确方法，并且使用诸如回归模型的其他负荷估计技术。这项工作的目的是确定一个最低数量的水质样本需要提供足够的成分浓度数据，以估计在一个大的流成分负荷。在不同的固定间隔从阿肯色州西北部伊利诺斯河的数据库中随机选择了20组水质样本（有和没有补充风暴样本）。随机集被用来估计总磷（TP）负荷使用回归模型。回归为基础的年度TP负荷进行了比较的综合年度TP负荷估计使用所有的数据。至少需要每月采样加上补充风暴样本（每年6个样本），以产生小于15%的均方根误差。如果在回归模型中使用季节性时间因素，则在不到两年的研究中，应至少每半个月（每15天）收集一次水质样本。从独立收集的离散水质样本估计的年度TP负荷进一步证明了使用回归模型来估计该流系统中的年度TP负荷的实用性。
The development of total maximum daily loads (TMDLs) requires evaluating existing constituent loads in streams. Accurate estimates of constituent loads are needed to calibrate watershed and reservoir models for TMDL development. The best approach to estimate constituent loads is high frequency sampling, particularly during storm events, and mass integration of constituents passing a point in a stream. Most often, resources are limited and discrete water quality samples are collected on fixed intervals and sometimes supplemented with directed sampling during storm events. When resources are limited, mass integration is not an accurate means to determine constituent loads and other load estimation techniques such as regression models are used. The objective of this work was to determine a minimum number of water-quality samples needed to provide constituent concentration data adequate to estimate constituent loads at a large stream. Twenty sets of water quality samples with and without supplemental storm samples were randomly selected at various fixed intervals from a database at the Illinois River, northwest Arkansas. The random sets were used to estimate total phosphorus (TP) loads using regression models. The regression-based annual TP loads were compared to the integrated annual TP load estimated using all the data. At a minimum, monthly sampling plus supplemental storm samples (six samples per year) was needed to produce a root mean square error of less than 15%. Water quality samples should be collected at least semi-monthly (every 15 days) in studies less than two years if seasonal time factors are to be used in the regression models. Annual TP loads estimated from independently collected discrete water quality samples further demonstrated the utility of using regression models to estimate annual TP loads in this stream system.