Author:
Coraggio Elisa,Han Dawei,Gronow Claire,Tryfonas Theo
Abstract
Water quality monitoring is essential to understanding the complex dynamics of water ecosystems, the impact of human infrastructure on them and to ensure the safe use of water resources for drinking, recreation and transport. High frequency in-situ monitoring systems are being increasingly employed in water quality monitoring schemes due to their much finer temporal measurement scales possible and reduced cost associated with manual sampling, manpower and time needed to process results compared to traditional grab-sampling. Modelling water quality data at higher frequency reduces uncertainty and allows for the capture of transient events, although due to potential constraints of data storage, inducement of noise, and power conservation it is worthwhile not using an excessively high sampling frequency. In this study, high frequency data recorded in Bristol's Floating Harbour as part of the local UKRIC Urban Observatory activities is presented to analyse events not captured by the current manual sampling and laboratory analysis scheme. The frequency components of the time-series are analysed to work towards understanding the necessary sampling frequency of temperature, dissolved oxygen (DO), fluorescent dissolved organic matter (fDOM), turbidity and conductivity as indicators of water quality. This study is the first of its kind to explore a statistical approach for determining the optimum sampling frequency for different water quality parameters using a high frequency dataset. Furthermore, it provides practical tools to understand how different sampling frequencies are representative of the water quality changes.
Funder
Engineering and Physical Sciences Research Council
Cited by
8 articles.
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