Factors affecting cyanobacterial blooms and their prediction in a tropical water supply reservoir
by Aline Almeida De Jesus Magalhães; Lafayette Dantas Da Luz; Terencio Rebello De Aguiar Junior
International Journal of Global Environmental Issues (IJGENVI), Vol. 18, No. 4, 2019

Abstract: In this study, our objectives were to determine the factors affecting cyanobacterial bloom and predict the abundance and probability of bloom occurrence in the tropical reservoir using generalised linear models (GLMs) with negative and positive binomial distributions. The water quality, weather, and water level data in the reservoir during 2006-2015 were used to develop the models. The results pointed out that: 1) predictive modelling using binomial distribution was the strongest and most parsimonious GLM; 2) total P and electric conductivity were positive factors, whereas 30-d mean water level and dissolved Al were negative factors; 3) water level had a strong significant effect on the probability of bloom events, while total phosphorus was not statistically significant and thus was not the major factor. The set of GLMs was not only an effective tool for identifying key contributing factors affecting cyanobacterial blooms, but also to improve the management of eutrophic tropical reservoirs.

Online publication date: Mon, 19-Oct-2020

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