Mathematical Modelling of Green Microalgae Invasion and Rehabilitation of the Taganrog Bay: Ecological-Hygienic and Medical Consequences

Introduction. The Taganrog Bay of the Azov Sea is one of the most eutrophic and ecologically vulnerable water areas in Russia, where massive blooms of toxic cyanobacteria (Microcystis, Aphanizomenon, Anabaena, Nodularia) regularly occur during summer. Their proliferation is accompanied by the accumulation of cyanotoxins (microcystin, anatoxin, cylindrospermopsin, saxitoxin), posing a serious threat to public health. This paper considers an approach to the biological rehabilitation of the bay based on the controlled introduction of the freshwater green microalgae Chlorella vulgaris, which competes with cyanobacteria for nutrients. The aim of the study is to develop and apply a comprehensive mathematical model describing phytoplankton kinetics and substance transport processes under conditions of increasing bay salinity, as well as to assess the ecological-hygienic and medical consequences of the proposed method. Materials and Methods. The research object is the Taganrog Bay of the Azov Sea. The modelling is based on the threedimensional hydrodynamic model “Azov3D”, previously used to calculate currents and vertical mixing under conditions of changing salinity. Water environment parameters (salinity, temperature, current velocities) were used as input data for solving the linearized hydrobiological problem. The source of bathymetric data was digitized nautical charts processed using automated depth recognition algorithms. The model grid was generated considering the actual coastline configuration and bottom topography. Calculations were performed on the computing cluster of the Southern Federal University. The numerical method is based on finite-difference schemes previously applied for hydrobiological calculations in the Azov Sea. Results. It is shown that a 30% increase in salinity leads to a shift in the cyanobacteria habitat from the Azov Sea water area to the eastern part of the Taganrog Bay, which is consistent with hydrological observations. Model calculations demonstrate an increase in the proportion of green algae with the controlled introduction of Chlorella vulgaris cultures, reflecting the potential for biomelioration. The forecast of the spatial distribution of populations shows stable dominance of green and blue-green algae, constituting 60−70% of the bay’s phytoplankton biomass, under various impact scenarios. Discussion. The results indicate that mathematical modelling is an effective tool for predicting the dynamics of phytoplankton populations under changing hydrological conditions. The model allows for assessing the influence of biological regulation and salinization scenarios, providing a basis for management decisions in the field of ecological rehabilitation of water bodies. Conclusion. The application of Chlorella vulgaris may be a promising biomelioration method but requires further verification based on field observations and controlled field experiments. The modelling results indicate the possibility of adaptive ecological management of the Taganrog Bay and minimizing the risk of toxic blooms.