九州大学大学院環境農学専攻生産環境科学教育コース水環境学研究分野 | 九州大学大学院農学研究院環境農学部門生産環境科学講座水環境学研究
Laboratory of Water Environment Engineering, Course of Bioproduction Environmental Sciences, Department of Agro-environmental Sciences, Graduate School of Bioresource and Bioenvironmental Sciences, Kyushu University | Laboratory of Water Environment Engineering, Division of Bioproduction Environmental Sciences, Department of Agro-environmental Sciences, Faculty of Agriculture, Kyushu University | Laboratory of Water Environment Engineering, Division of Bioproduction Environmental Sciences, Department of Agro-environmental Sciences, Faculty of Agriculture, Kyushu University
九州大学大学院農学研究院環境農学部門生産環境科学講座水環境学研究
Laboratory of Water Environment Engineering, Division of Bioproduction Environmental Sciences, Department of Agro-environmental Sciences, Faculty of Agriculture, Kyushu University
九州大学大学院農学研究院環境農学部門生産環境科学講座水環境学研究
Laboratory of Water Environment Engineering, Division of Bioproduction Environmental Sciences, Department of Agro-environmental Sciences, Faculty of Agriculture, Kyushu University
九州大学新キャンパス計画推進室 | 九州大学大学院農学研究院環境農学部門生産環境科学講座水環境学研究
New Campus Planning Office, Kyushu University | Laboratory of Water Environment Engineering, Division of Bioproduction Environmental Sciences, Department of Agro-environmental Sciences, Faculty of Agriculture, Kyushu University | Laboratory of Water Environment Engineering, Division of Bioproduction Environmental Sciences, Department of Agro-environmental Sciences, Faculty of Agriculture, Kyushu University
The water quality of the no. 5 regulation pond at the Ito campus of Kyushu University has deteriorated because of the overloading of organic matter including a large amount of humic substance derived from the deforested wood chip. The reservoir has water quality problems, such as generation of anoxic water mass, decrease in transparency, and deposition of colloidal sediment. Therefore, analysis of the dynamic changes in water quality is important for the maintenance and improvement of the no. 5 regulation pond. In this study, the characteristics of the water area were quantitatively estimated on the basis of the 3 research subjects as the first step for analyzing the dynamic changes in water environment by using the water quality prediction model. These subjects included modeling the vertical turbulent diffusion coefficient, estimation of inflow loading of organic matter, and the evaluation of the effects of the bottom sediment on water quality. First, the temporal and vertical profiles of water temperature were measured in summer, and then, the vertical turbulent diffusion coefficients of the stratified water body were calculated by using a vertical one-dimensional diffusion equation based on the observation data. The model equation for the coefficient could be represented by the stratification function using the local Richardson number, and its validity was assessed on the basis of the relations between the calculated results and observed values. Second, inflow loading for 3 water quality parameters?dissolved organic carbon, total nitrogen, and total phosphorus?was measured at 2 box culverts through which water containing a large amount of organic matter, including humus, from the drainage basin mainly flowed into the no. 5 regulation pond. These measurements were used to derive the accurate L-Q equations for each water quality parameter in both types of drainage. Further, the characteristics of inflow loading were found to differ according to the water quality parameters and the location of the box culverts. Finally, the measurements for the physico-chemical characteristics of the bottom sediment showed that the concentration of total phosphorus was relatively high and that concentrations of total nitrogen and hydrosulphide were low. In addition, the oxygen transfer coefficient was calculated by using the Hosoi’s model based on the physical properties of the sediment, such as specific gravity, representational grain size, water content ratio and ignition loss, and the representative value s of oxygen consumption could be estimated for summer and autumn.