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Zhurnal Vychislitel'noi Matematiki i Matematicheskoi Fiziki, 2022, Volume 62, Number 2, Pages 270–288
DOI: https://doi.org/10.31857/S0044466921120048
(Mi zvmmf11360)
 

This article is cited in 4 scientific papers (total in 6 papers)

Mathematical physics

Mathematical modeling of hazardous natural phenomena in a shallow basin

A. M. Atayanab, A. V. Nikitinaabcd, A. I. Sukhinova, A. E. Chistyakovab

a Don State Technical University, 344000, Rostov-on-Don, Russia
b Research and Technology University Sirius, 347900, Sochi, Russia
c Southern Federal University, 344006, Rostov-on-Don, Russia
d Research Supercomputer and Neurocomputer Center, 347900, Taganrog, Russia
Citations (6)
Abstract: This paper is devoted to the construction and analysis of coupled mathematical models of hydrophysics and biological kinetics used for predicting hazardous natural phenomena occurring in shallow basins. The propagation and transformation of aquatic organisms is affected by such physical factors as three-dimensional spatial motion of water taking into account the advective transfer and microturbulent diffusion, spatially inhomogeneous distribution of temperature, salinity, and oxygen. Biogenic pollutants cause algae growth, including toxic and harmful ones; this growth can cause hazardous phenomena in the basin, including eutrophication and suffocation phenomena. A three-dimensional mathematical model of hydrodynamics is constructed and used for calculating the water flow velocity field. To investigate hazardous phenomena in a shallow basin related to suffocation phenomena in it, a three-dimensional spatially inhomogeneous ichthyological model of commercial fish dynamics is developed. Models of observations parameterized on the basis of stoichiometric relations, Monod, Michaelis–Menten, and Mitscherlich–Baule laws that describe the consumption and accumulation of nutrients by phytoplankton and commercial detritophagous fish and the growth of aquatic organisms depending on the spatial distribution of salinity, temperature, and oxygen regimen are considered. To calibrate and verify the models, constantly updated ecological databases obtained, in particular, in field research of the Sea of Azov and Taganrog Bay are used. To improve the accuracy of predictive simulation, the field data is filtered using the Kalman algorithm. As a result of processing the hydrological data, salinity and temperature isolines in the surface layer are obtained; for this purpose, a recognition algorithm is used. Using interpolation and superposition of domain boundaries, more detailed depth, salinity, and temperature maps for the Sea of Azov are obtained. Numerical methods for solving the formulated problems that are based on finite difference schemes taking into account the degree of filling of the computation domain control cells are developed. These methods are implemented on high-performance computers, and they decrease the numerical solution error and reduce the computation time by several fold. Based on the numerical implementation of the developed models, hazardous natural phenomena in shallow basins (related to the propagation of harmful pollutants), eutrophication, and algae bloom, which causes suffocation phenomena, are reconstructed.
Key words: mathematical model, hydrodynamics, biological kinetics, phytoplankton, commercial fish, software, high-performance computer, hazardous phenomena, shallow basin.
Funding agency Grant number
Russian Foundation for Basic Research 19-31-51017
This work was supported by the Russian Foundation for Basic Research, project no. 19-31-51017.
Received: 15.02.2021
Revised: 17.07.2021
Accepted: 04.08.2021
English version:
Computational Mathematics and Mathematical Physics, 2022, Volume 61, Issue 2, Pages 269–286
DOI: https://doi.org/10.1134/S0965542521120034
Bibliographic databases:
Document Type: Article
UDC: 519.34
Language: Russian
Citation: A. M. Atayan, A. V. Nikitina, A. I. Sukhinov, A. E. Chistyakov, “Mathematical modeling of hazardous natural phenomena in a shallow basin”, Zh. Vychisl. Mat. Mat. Fiz., 62:2 (2022), 270–288; Comput. Math. Math. Phys., 61:2 (2022), 269–286
Citation in format AMSBIB
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  • https://www.mathnet.ru/eng/zvmmf/v62/i2/p270
  • This publication is cited in the following 6 articles:
    1. A. I. Sukhinov, O. V. Kolgunova, M. Z. Ghirmay, O. S. Nahom, “Two Dimensional Hydrodynamics Model with Evaporation for Coastal Systems”, CMIT, 7:4 (2024), 9  crossref
    2. A. V. Khoperskov, S. S. Khrapov, A. Yu. Klikunova, I. E. Popov, “Efficiency of Using GPUs for Reconstructing the Hydraulic Resistance in River Systems Based on Combination of High Performance Hydrodynamic Simulation and Machine Learning”, Lobachevskii J Math, 45:7 (2024), 3085  crossref
    3. Alexander Sukhinov, Yulia Belova, Asya Atayan, N. Yakovenko, M. Gutalj, S. Ignateva, “Modeling of biogeochemical processes in the Azov Sea based on the Azov3D software package”, BIO Web Conf., 145 (2024), 02018  crossref
    4. “Abstracts of talks given at the 7th International Conference on Stochastic Methods, II”, Theory Probab. Appl., 68:1 (2023), 150–169  mathnet  crossref  crossref
    5. Oksana Yu. Vatyukova, Anna Yu. Klikunova, Anna A. Vasilchenko, Alexander A. Voronin, Alexander V. Khoperskov, Mikhail A. Kharitonov, “The Problem of Effective Evacuation of the Population from Floodplains under Threat of Flooding: Algorithmic and Software Support with Shortage of Resources”, Computation, 11:8 (2023), 150  crossref
    6. “Abstracts of talks given at the 7th International Conference on Stochastic Methods, I”, Theory Probab. Appl., 67:4 (2022), 652–652  mathnet  crossref  crossref
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