Stormwater monitoring using on-line UV-Vis spectroscopy

浊度 雨水 总悬浮物 环境科学 地表径流 硝酸盐 悬浮物 水质 总溶解固体 水文学(农业) 环境工程 污染物 地表水 生态学 化学 废水 化学需氧量 工程类 生物 有机化学 岩土工程
作者
Jianyin Huang,Christopher W.K. Chow,Zhining Shi,Rolando Fabris,Amanda Mussared,Gary Hallas,Paul Monis,Bo Jin,Christopher P. Saint
出处
期刊:Environmental Science and Pollution Research [Springer Science+Business Media]
卷期号:29 (13): 19530-19539 被引量:2
标识
DOI:10.1007/s11356-021-17056-7
摘要

Stormwater runoff contains a myriad of pollutants, including faecal microbes, and can pose a threat to urban water supplies, impacting both economic development and public health. Therefore, it is a necessity to implement a real-time hazard detection system that can collect a substantial amount of data, assisting water authorities to develop preventive strategies to ensure the control of hazards entering drinking water sources. An on-line UV-Vis spectrophotometer was applied in the field to collect real-time continuous data for various water quality parameters (nitrate, DOC, turbidity and total suspended solids) during three storm events in Mannum, Adelaide, Australia. This study demonstrated that the trends for on-line and comparative laboratory-analysed samples were complimentary through the events. Nitrate and DOC showed a negative correlation with water level, while turbidity and total suspended solids indicated a positive correlation with water level during the high rainfall intensity. The correlations among nitrate, DOC, turbidity, total suspended solids and water level are the opposite during low rainfall intensity. Nitrate, one of the main pollutants in stormwater, was investigated and used as a surrogate parameter for microbial detection. However, the microbiological data (Escherichia coli) from captured storm events showed poor correlations to nitrate and other typical on-line parameters in this study. This is possibly explained by the nature of the stormwater catchment outside of rain events, where the sources of bacteria and nutrients may be physically separated until mixed during surface runoff as a result of rainfall. In addition, the poor correlations among the microbiological data and on-line parameters could be due to the different sources of bacteria and nutrients that were transported to the stormwater drain where sampling and measurement were conducted.
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