Sampling frequency for water quality variables in streams: Systems analysis to quantify minimum monitoring rates
Sampling frequency for water quality variables in streams: Systems analysis to quantify minimum monitoring rates
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DOI：
10.1016/j.watres.2017.06.047
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发表时间：
2017-10-15
期刊：
影响因子：
12.8
通讯作者：
Tych, Wlodek
中科院分区：
文献类型：
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作者：
Chappell, Nick A.;Jones, Timothy D.;Tych, Wlodek
在溪流或工程排水系统的水质不充分的时间监测改变了风暴化学图的明显形状，导致转移模型parameterisations和改变的解释溶质来源，产生了不良的水质发作。这种所谓的“混叠”现象在水研究中认识不足。利用现场传感器技术的进步，现在可以足够频繁地进行监测，以避免出现混叠。提出了一种系统建模程序，可以客观地确定避免强烈降雨驱动的化学动力学中的混叠所需的采样率。在这项研究中，风暴化学图形状的混叠量化的时间常数参数（TC）的传递函数的变化。作为原始TC的比例，混叠的开始在流域之间变化，范围从3.9-7.7到54- 79%TC（或110-160到300 - 600分钟）。然而，如果建模结果以新的统计量Delta TC的形式呈现，则可以确定所有数据集的最低监测率。对于八个H+，DOC和NO3-N数据集检查从一系列的流域设置，一个简单的派生阈值为1.3（三角洲TC）可以用来量化采样协议内的最低监测率，以避免在随后的数据分析的文物。(C)2017作者爱思唯尔有限公司出版
Insufficient temporal monitoring of water quality in streams or engineered drains alters the apparent shape of storm chemographs, resulting in shifted model parameterisations and changed interpretations of solute sources that have produced episodes of poor water quality. This so-called 'aliasing' phenomenon is poorly recognised in water research. Using advances in in-situ sensor technology it is now possible to monitor sufficiently frequently to avoid the onset of aliasing. A systems modelling procedure is presented allowing objective identification of sampling rates needed to avoid aliasing within strongly rainfall-driven chemical dynamics. In this study aliasing of storm chemograph shapes was quantified by changes in the time constant parameter (TC) of transfer functions. As a proportion of the original TC, the onset of aliasing varied between watersheds, ranging from 3.9-7.7 to 54-79 %TC (or 110-160 to 300 -600 min). However, a minimum monitoring rate could be identified for all datasets if the modelling results were presented in the form of a new statistic, Delta TC. For the eight H+, DOC and NO3-N datasets examined from a range of watershed settings, an empirically-derived threshold of 1.3(Delta TC) could be used to quantify minimum monitoring rates within sampling protocols to avoid artefacts in subsequent data analysis. (C) 2017 The Authors. Published by Elsevier Ltd.