MATHEMATICAL MODELING AND ECOLOGICAL DESIGN OF THE MARINE SYSTEMS TAKING INTO ACCOUNT MULTI-SCALE TURBULENCE USING REMOTE SENSING DATA

The paper considers a mathematical model of biological kinetics and geochemical cycles based on a system of convection-diffusion equations with nonlinear coefficients, supplemented by a spatially inhomogeneous three-dimensional mathematical model of wave hydrodynamics of a shallow reservoir, with a refined coefficient of turbulent vertical exchange. The task of monitoring the water surface in order to detect phytoplankton spots involves the creation and verification of effective methods for clustering these objects on the surface of reservoirs, in particular, restoring their boundaries based on remote sensing data. The article uses multispectral satellite images as sounding data. Based on the obtained images of plankton populations, the initial conditions for mathematical models of biogeochemical cycles can be determined, on the basis of which prognostic calculations are performed.

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2. Protsenko S., Sukhinova T. Mathematical modeling of wave processes and transport of bottom materials in coastal water areas taking into account coastal structures // MATEC Web of Conferences, 132, 2017, 04002.

3. Sukhinov A. I., Panasenko N. D. Comparative investigation of neural and locally binary algorithms for image identification of plankton populations // Computational Mathematics and Information Technologies, 2022, 1(2), pp. 70-80.

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5. Sukhinov AI, Chistyakov AE, Protsenko EA, Sidoryakina VV, Protsenko SV 2019 Accounting method of filling cells for the hydrodynamics problems solution with complex geometry of the computational domain (Matem. Mod., 31(8)) pp 79–100. DOI: https://doi.org/10.1134/S0234087919080057.

6. Sukhinov AI, Chistyakov AE, Protsenko EA, Sidoryakina VV, Protsenko SV 2020 Set of coupled suspended matter transport models including three-dimensional hydrodynamic processes in the coastal zone (Matem. Mod., 32(2)) pp 3–23. DOI: https://doi.org/10.20948/mm-2020-02-01.

7. Sukhinov AI, Chistyakov AE, Protsenko EA, Sidoryakina VV, Protsenko SV 2020 Parallel algorithms for solving the problem of coastal bottom relief dynamics (Num. Meth. Prog., 21(3)) p 196–206. DOI: https://doi.org/10.26089/NumMet.v21r318.

8. Sukhinov AI, Chistyakov AYe, Fomenko NA 2013 Metodika postroyeniia raznostnykh skhem dlia resheniia zadach diffuzii-konvektsii- reaktsii, uchityvaiushchikh stepen zapolnennosti kontrolnykh yacheek (Izvestiia YUFU. Tekhnicheskie nauki, 4(141)) p 87-98.

9. Sukhinov A.I., Sukhinov A.A. 2005 3D Model of Diffusion-Advection-Aggregation Suspensions in Water Basins and Its Parallel Realization (Parallel Computational Fluid Dynamics, Multidisciplinary Applications, Proceedings of Parallel CFD 2004 Conference, Las Palmas de Gran Canaria, Spain, ELSEVIER, Amsterdam-Berlin-London-New York-Tokyo) pp 223-230.

10. Sukhinov AI, Chistyakov AE 2012 Adaptive Modified Alternating Triangular Iterative Method for Solving Grid Equations with a Non-Self-Adjoint Operator (Mathematical Models and Computer Simulations, 4(4)) p 398-409.