九州大学大学院生物資源環境科学府生産環境科学専攻地域環境科学講座水環境学研究室
Laboratory of Drainage and Water Environment, Division of Regional Environment Science, Department of Bioproduction Environmnetal Sciences, Graguate School of Bioresource and Bioenvironmental Sciences, Kyushu University
九州大学大学院農学研究院生産環境科学部門地域環境科学講座水環境学研究室
Laboratory of Drainage and Water Environment, Division of Regional Environment Science, Department of Bioproduction Environmnetal Sciences, Faculty of Agriculture, Kyushu University
九州大学大学院農学研究院生産環境科学部門地域環境科学講座水環境学研究室
Laboratory of Drainage and Water Environment, Division of Regional Environment Science, Department of Bioproduction Environmnetal Sciences, Faculty of Agriculture, Kyushu University
Because of eutrophication, a bloom of phytoplankton called 'aoko' is causing serious problems in Okubo Pond in the Obaru River basin of the Itoshima area of Fukuoka Prefecture. Therefore, a water quality prediction model was built to understand the features of phytoplankton. This model was based on a completely mixed system, and in the model, phytoplankton was separated into four groups: green algae, blue green algae, diatom/dinoflagenates, and cryptophyte algae. Results calculated with the model agreed with observational results. Also, the model parameters connected to phytoplankton corresponded approximately to anamnestic cases. Next, with the model, we considered the characteristics involved in the growth of phytoplankton. The result indicated that features of phytoplankton related to temperature and nutrients varied with species. Also was found that the seasonal prevalence of phytoplankton was multiply influenced by temperature and nutrients.
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