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Turning Routine Data into Systems Insight: Multivariate Analysis of Water Quality Dynamics in a Major Drinking Water Reservoir
Environmental Modeling & Assessment ( IF 2.7 ) Pub Date : 2020-02-22 , DOI: 10.1007/s10666-020-09700-2
Azadeh Golshan , Craig Evans , Phillip Geary , Abigail Morrow , Zoe Rogers , Marcel Maeder

Long-term water quality datasets generated by the routine monitoring activities of public water supply utilities are often under-utilized in terms of the information they contain regarding system dynamics. This study demonstrates the insight that may be derived from thorough analysis of such data, in terms of evaluating key factors underlying spatial and temporal patterns in the water quality of major storage reservoirs. Principal component (PCA) and multivariate curve resolution-alternating least squares (MCR-ALS) analyses were applied to three consecutive years of monitoring data, comprising 22 physicochemical parameters, measured at three sampling stations within a major drinking water reservoir. Reservoir nitrogen levels were found to be most strongly influenced by urban run-off from the south-eastern catchment region, while total phosphorus levels were more closely linked to inflows to the northern end of the reservoir from the mainly agricultural neighbouring catchment. Elevations in soluble reactive phosphorus (SRP) were correlated with increases in the vertical temperature gradient of the water column at the relatively shallow northern end, suggesting possible release from sediments as a major source. SRP and thermal gradient, as opposed to absolute water temperature, were found to be the factors most closely aligned with chlorophyll-α levels in the reservoir. The analyses highlighted the catchment origins and in-storage foci of key factors driving algal productivity within the reservoir, suggesting that water quality management strategies may be further informed by investigation of sediment characteristics and interplay between physical, chemical and biological processes at the northern end of the reservoir.



中文翻译:

将常规数据转化为系统洞察力:大型饮用水水库水质动态的多元分析

在公共供水公用事业的常规监测活动中生成的长期水质数据集,由于它们所包含的有关系统动态的信息,常常没有得到充分利用。这项研究表明,通过评估主要存储水库水质时空分布的关键因素,可以对此类数据进行全面分析而得出的见解。将主成分(PCA)和多变量曲线分辨率交替最小二乘(MCR-ALS)分析应用于连续三年的监测数据,该数据包括22个理化参数,这些数据是在主要饮用水水库中的三个采样站测得的。发现水库中的氮水平受东南集水区城市径流的影响最大,而总磷水平则与主要来自农业邻近集水区的水库北端流入量有更紧密的联系。可溶性活性磷(SRP)的升高与相对较浅的北端水柱的垂直温度梯度的升高相关,这表明可能从沉积物中释放出水作为主要来源。与绝对水温相反,SRP和热梯度是与储层中叶绿素-α水平最紧密相关的因素。这些分析突出显示了影响水库内藻类生产力的关键因素的集水区起源和入库重点,这表明通过研究沉积物特征和物理,水体之间的相互作用,可以进一步为水质管理策略提供参考。

更新日期:2020-04-23
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