![]() ![]() However, the key hydrodynamic principle for performing reservoir operation strategies is still unknown, posing an obstacle to practical applications. ![]() Reservoir operation strategies with low cost and high efficiency have been proposed to control algal blooms. Although this problem could be overcome by assigning different maximum growth rates for different regions, it may be necessary to improve EFDC so that it can include more phytoplankton groups. This result indicates that more than three algal groups need to be included to improve Chl-a calibration accuracy for the study area, yet the current EFDC model can consider only up to three phytoplankton groups. It was found necessary to apply different maximum growth rates for algal groups for the upstream and downstream regions of the study area to appropriately reflect field observations. The optimum growth temperature ranges were selected based on field data for the study area. To improve the prediction accuracy of Chl-a, three dominant groups of algae were considered: diatoms, green algae, and cyanobacteria. Calibration accuracy was verified not only for physical variables, including the mean water level and temperature, but also for other water quality variables in various locations of the study area. Calibration and verification of EFDC were performed by comparing the model results to three years of field data collected from 2013 to 2015. Chlorophyll-a (Chl-a) was chosen as the primary indicator for the likelihood of algal blooms. This grid system was determined adequate, as the maximum values of the Courant-Friedrichs-Lewy condition and orthogonality deviation were 0.5 and 20.1, respectively. km long river section, 1175 horizontal 2-D grid elements were developed. Modeling of algal bloom occurrence patterns in the lower part of this river was performed using the Environmental Fluid Dynamics Code (EFDC) to understand algal dynamics and thus better develop management alternatives. The lower part of the Han River, which flows through Seoul, Korea, experienced excessive toxic cyanobacterial growth in 2015. In general, through this study, it is seen that the integrated modelling deserves more research inputs because: (1) the hydrodynamic processes and nutrients concentrations can be simulated in details by numerical method (2) the irregular and sparse water quality and biological data, and the empirical knowledge from experts can be explored by the fuzzy logic technique (3) the spatial heterogeneity, local interactions and the emerge of patchiness could be well captured through the cellular automata paradigm. The simulated results of year 1995 were compared with that from BLOOM II model, and the advantages, disadvantages as well as future improvement were presented. The numerical module used Delft3D-WAQ to compute the abiotic conditions, and fuzzy cellular automata approach was applied to predict the algal biomass that was indicated by chlorophyll a concentration. In this paper, an integrated numerical and fuzzy cellular automata model was developed to predict possible algal blooms in Dutch coastal waters basing on the irradiance, nutrients and neighbourhood conditions.
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