Using CANARY event detection software for water quality analysis in the Milwaukee River

IF 2.4 3区 环境科学与生态学 Q2 ENGINEERING, CIVIL Journal of Hydro-environment Research Pub Date : 2021-09-01 DOI:10.1016/j.jher.2021.06.003
Nabila Nafsin, Jin Li
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引用次数: 5

Abstract

Urban water sources are susceptible to various contamination events as a result of natural, accidental, and human-induced occurrences. An early warning monitoring system provides timely information on changes in urban water quality. In this study, an analysis was made with CANARY event detection software (EDS) to monitor water quality parameters in river water and to identify the onset of anomalous water quality periods. Water quality signals including pH, conductivity, and turbidity from the Milwaukee River over specified periods during the summer season of 2018–2020 were employed as inputs to event detection algorithms in CANARY. The data analysis results show that CANARY can be useful as an early warning system for monitoring contamination in urban water sources and help to identify abnormal conditions quickly. The sensibility of the model relies on optimizing the configuration parameters, which involves selecting the ideal set of parameters for the event detection algorithm and adjusting the BED parameters to increase or decrease the probability of generating an alarm. The number of events reported between the Linear Prediction Correction Filter (LPCF) and Multivariate Nearest Neighbor (MVNN) algorithms varied as a result of different residual calculation mechanisms. Climate factors that contributed to the abnormal water quality events in the river were examined. The analysis of rainfall on water quality was carried out using a statistical method by determining whether there is a significant difference (p-value) between the seasonal mean water quality data and the mean value of water parameters during the sampling duration. Regression analysis was also performed to estimate the best model that describes the relationship between each of the water quality parameters and temperature.

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使用CANARY事件检测软件对密尔沃基河进行水质分析
城市水源容易受到自然、意外和人为污染事件的影响。预警监测系统提供有关城市水质变化的及时信息。本研究利用CANARY事件检测软件(EDS)对河流水质参数进行监测分析,识别水质异常期的开始。在2018-2020年夏季的特定时期,密尔沃基河的水质信号包括pH值、电导率和浊度,被用作CANARY事件检测算法的输入。数据分析结果表明,CANARY可作为城市水源污染监测的预警系统,有助于快速识别异常状况。模型的敏感性依赖于配置参数的优化,其中包括为事件检测算法选择理想的参数集和调整BED参数以增加或减少产生告警的概率。由于残差计算机制的不同,线性预测校正滤波器(LPCF)和多元最近邻算法(MVNN)所报告的事件数也有所不同。分析了导致该河流水质异常事件的气候因子。采用统计方法分析降雨对水质的影响,确定季节平均水质数据与采样期间水参数平均值之间是否存在显著差异(p值)。并进行回归分析,以估计描述各水质参数与温度之间关系的最佳模型。
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来源期刊
Journal of Hydro-environment Research
Journal of Hydro-environment Research ENGINEERING, CIVIL-ENVIRONMENTAL SCIENCES
CiteScore
5.80
自引率
0.00%
发文量
34
审稿时长
98 days
期刊介绍: The journal aims to provide an international platform for the dissemination of research and engineering applications related to water and hydraulic problems in the Asia-Pacific region. The journal provides a wide distribution at affordable subscription rate, as well as a rapid reviewing and publication time. The journal particularly encourages papers from young researchers. Papers that require extensive language editing, qualify for editorial assistance with American Journal Experts, a Language Editing Company that Elsevier recommends. Authors submitting to this journal are entitled to a 10% discount.
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