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A novel early warning system (EWS) for water quality, integrating a high-frequency monitoring database with efficient data quality control technology at a large and deep lake (Lake Qiandao), China

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Abstract

To assess water quality (WQ) online for assuring the safety of drinking water, a novel early warning system integrating a high-frequency monitoring system (HFMS) and data quality
control (QC) was developed at Lake Qiandao. The HFMS was designed for monitoring water quality, nutrient inputs by main tributaries, water currents and meteorology at different sites at Lake Qiandao. The EWS focused on data availability, a QC method, a statistical analysis method
and data applications instead of technological aspects for sondes, wireless data transfer and interface software development. QC was implemented before use to delete the abnormal values of outliers, to detect change points, to analyse the change trend, to interpolate discrete missing
measurements, and find continuous missing or wrong observations caused by technical problems with the sonde. For demonstrating advantages and data availability, surface and profiling measurements at two sites were plotted. The plots show obvious seasonal and diel variations,
demonstrating the success of integration of the system with advanced automated technology and good QC. This successfully developed system is now not only giving early warning signals, but also providing critical WQ information for the security of drinking water diverted to Hangzhou city
through a tunnel of 110 km length. The automatic monitoring data with QC is also being used to produce initial conditions for WQ prediction based on a three dimensional hydrodynamicecosystem model.

Item Type: Journal article
Uncontrolled Keywords: early warning system, high-frequency monitoring, data quality control, water quality, Lake Qiandao
Subjects: T Technology > T Technology (General)
Divisions: Schools > Centre for Engineering and Industrial Design
Depositing User: Hong Zhou
Date Deposited: 20 Feb 2022 20:49
Last Modified: 21 Jul 2023 09:29
URI: http://researcharchive.wintec.ac.nz/id/eprint/7918

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