Article ID Journal Published Year Pages File Type
4374880 Ecological Informatics 2014 8 Pages PDF
Abstract

•We developed a real-time system for observing and forecasting algal blooms.•The real-time forecasting of algal blooms is based on in situ sondes' data.•HEAs achieved good accuracies in 1–4 days ahead forecasting of algal blooms.

Phytoplankton bloom is one of the most serious threats to water resource, and remains a global challenge in environmental management. Real-time monitoring and forecasting the dynamics of phytoplankton and early warning the risks are critical steps in an effective environmental management. Automated online sondes have been widely used for in situ real-time monitoring of water quality due to their high reliability and low cost. However, the knowledge of using real-time data from those sondes to forecast phytoplankton blooms has been seldom addressed. Here we present an integrated system for real-time observation, early warning and forecasting of phytoplankton blooms by integrating automated online sondes and the ecological model. Specifically, based on the high-frequency data from automated online sondes in Xiangxi Bay of Three Gorges Reservoir, we successfully developed 1–4 days ahead forecasting models for chlorophyll a (chl a) concentration with hybrid evolutionary algorithms (HEAs). With the predicted concentration of chl a, we achieved a high precision in 1–7 days ahead early warning of good (chl a < 25 μg/L) and eutrophic (chl a 8–25 μg/L) conditions; however only achieved an acceptable precision in 1–2 days ahead early warning of hypertrophic condition (chl a ≥ 25 μg/L). Our study shows that the optimized HEAs achieved an acceptable performance in real-time short-term forecasting and early warning of phytoplankton blooms with the data from the automated in situ sondes. This system provides an efficient way in real-time monitoring and early warning of phytoplankton blooms, and may have a wide application in eutrophication monitoring and management.

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Life Sciences Agricultural and Biological Sciences Ecology, Evolution, Behavior and Systematics
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