Using multichannel satellite images for predictive modelling the «bloom» phytoplankton processes in shallow waters on supercomputer
https://doi.org/10.23947/2587-8999-2017-2-128-140
Abstract
The paper covers the development and research of mathematical models of «bloom» phytoplankton processes, that cause hypoxic phenomena in shallow waters, on the basis of modern information technologies and computational methods. Expedition data and multichannel satellite images of remote sensing obtained by the SRC «Planet» are used for calibration and verification of the developed model. The methods of domain decomposition was used in a parallel implementation for computationally labours problems, taking into account the architecture and parameters of multiprocessor computer system.
Keywords
mathematical model,
the «bloom» of phytoplankton,
hypoxic phenomena,
multichannel satellite images,
supercomputer,
parallel algorithms
Supporting agencies: The research is done with the financial support from RSF, Project No. 17-11-01286.
About the Authors
Alexander Ivanovich Sukhinov
Don State Technical University
(1st Gagarin Square, Rostov-on-Don, Russian Federation)
Russian Federation
Russian Federation
Sukhinov Alexander Ivanovich, Vice Rector for Research and Innovative Activity, Don State Technical University (1st Gagarin Square, Rostov-on-Don, Russian Federation), Doctor of Science in Physics and Maths, Professor
Alla Valerievna Nikitina
Scientific Research Institute of Multiprocessor Computer Systems named after Academician Kalyaev Southern Federal University
(2d Chekhov St., Taganrog, Russian Federation)
Russian Federation
Russian Federation
Nikitina Alla Valerievna, Scientific Research Institute of Multiprocessor Computer Systems named after Academician Kalyaev Southern Federal University (2d Chekhov St., Taganrog, Russian Federation), Doctor of Technical Sciences, Associate professor
Alexander Evgenievich Chistyakov
Don State Technical University
(1st Gagarin Square, Rostov-on-Don, Russian Federation)
Russian Federation
Russian Federation
Chistyakov Alexander Evgenievich, Don State Technical University (1st Gagarin Square, Rostov-on-Don, Russian Federation), Doctor of Science in Physics and Maths, Professor
References
1. Sukhinov A.I., Chistyakov A.E., Semenyakina A.A., Nikitina A.V. Numerical modeling of the ecological condition of the Sea of Azov with the application of the schemes of the growing accuracy of the order on the multiprocessor computing system // Computer researches and modeling. 2016. T. 8, No. 1. pp. 151 - 168.
2. Sukhinov A.I., Chistyakov A.E., Nikitina A.V., Semenyakina A.A., Korovin I.; Schaefer G. Publications. Modeling of oil spill spread 2016 5th International Conference on Informatics, Electronics and Vision (ICIEV). 2016. pp: 1134 - 1139.
3. State Research Center «Planeta», http://planet.iitp.ru/english/index_eng.htm
4. Sukhinov A.I., Nikitina A.V., Chistyakov A.E., Semenov I.S., Semenyakina A.A., Khachunts D.S. Mathematical modeling of eutrophication processes in shallow waters on the multiprocessor computer system / CEUR Workshop Proceedings. Vol. 1576. 2016. PP. 320-333,10th Annual International Scientific Conference on Parallel Computing Technologies, PCT 2016; Arkhangelsk; Russian Federation; 29 March 2016 through 31 March 2016; Code 121197.
5. Nikitina A. V., Sukhinov A.I., Ugolnitsky G.A., Usov A.B., Chistyakov A.E., Puchkin M.V., Semenov I.S. Optimal control of sustainable development in the biological recovery of the Azov Sea // Mathematical Models and Computer Simulations. 2017. 9 (1), pp. 101-107.
6. Nikitina A.V., Tretyakova M.V. Modeling the process of algolization of a shallow water body by introducing into it a strain of green alga Chlorella vulgaris bin // Izvestiya SFU. Technical science. 2012. No. 1. pp. 128-133.
7. Sukhinov A.I., Nikitina A.V., Chistyakov A.E., Semenov I.S. Mathematical modeling of conditions of formation of freezes in shallow water reservoirs on a multiprocessor computer system // Computational methods and programming: new computing technologies. 2013. Vol.14. №1. pp. 103-112.
8. Sukhinov A.I., Chistyakov A.E., Protsenko E.A. Two-dimensional hydrodynamic model, taking into account the dynamic reconstruction of the bottom of a shallow water body // Izvestiya SFU. Technical science. 2011. № 8 (121). pp. 159-167.
9. Sukhinov A.I., Chistyakov A.E., Protsenko E.A. Construction of a discrete two-dimensional mathematical model of sediment transport // Izvestiya SFU. Technical science. 2011. № 8 (121). pp. 32-44.
10. Sukhinov A.I., Chistyakov A.E., Protsenko E.A. Mathematical modeling of sediment transport in the coastal zone of shallow reservoirs. Mathematical models and computer simulations. 2014. Vol. 6. No. 4. pp. 351-363.
11. Samarsky A.A. The theory of difference schemes. Moscow: Nauka, 1989. 616 p.
12. Nikitina AV, Semenyakina AA, Chistyakov AE Parallel realization of the diffusion-convection problem on the basis of high accuracy schemes // Journal of Computer and Information Technologies. 2016, No. 7 (146). pp. 3-7.
13. Semenyakina A.A., Nikitina A.V., Chistyakov A.E., Sukhinov A.I. A complex of models, explicit regularized schemes of increased accuracy order and programs for predictive modeling of consequences of oil spills accident // Proceedings of the Conference «Parallel Computing Technologies: PСT-2016» / 2016 pp. 308-317.
14. Sukhinov A.I., Chistyakov A.E., Semenyakina A.A., Nikitina A.V. Parallel implementation of the tasks of transport of substances and restoration of the bottom surface on the basis of schemes of increased accuracy order // Computational methods and programming: new computing technologies. 2015. Vol.16. pp. 256 - 267.
15. Konovalov A.N. To the theory of alternating-triangular iteration method // Siberian Mathematical Journal. 2002. 43: 3. pp. 552-572.
16. Belotserkovsky O.M. Turbulence: New Approaches. Moscow: Nauka, 2003. 286 c.
17. Sukhinov A.I., Chistyakov A.E. Adaptive modified alternating-triangular iterative method for solving grid equations with a nonselfadjoint operator. // Mathematical Modeling. 2012. Vol. 24, №1. pp. 3-20.
18. Nikitina A.V., Sukhinov A.I., Ugolnitsky G.A., Usov A.B., Chistyakov A.E., Puchkin M.V., Semenov I.S. Optimal management of sustainable development in the biological rehabilitation of the Azov Sea // Mathematical modeling. 2016. Vol. 28, №7. pp. 96 - 106.
19. Nikitina A.V., Puchkin M.V., Semenov I.S., Sukhinov A.I., Ugolnitsky G.A., Usov A.B., Chistyakov A.E. Differential-game model of prevention of freezing in shallow water bodies // Management of large systems. 2015. Issue 55. pp. 343 - 361.
20. Trân J.K. A predator-prey functional response incorporating an indirect interference and depletion // Verh. Internat. Verein. Limnol. 2008. Vol. 30, pp. 302 - 305.
21. Tyutyunov Yu., Senina I., Arditi R. Clustering due to acceleration in the response to the population gradient: a simple self-organization model // The American Naturalist. 2004, pp. 722-735.
22. Volterra V. Variations and fluctuations of the number of individuals in an animal species living together // Rapp. P. - V. Reun. Cons. Int. Explor. Mer. 1928. 3, pp. 3-51.
23. Yakushev E.V., Mikhailovsky G.E. Mathematical modeling of the influence of marine biota on the carbon dioxide ocean-atmosphere exchange in high latitudes // Air-Water Gas Transfer, Sel. Papers, Third Int. Symp., Heidelberg University, ed. by B. Jaehne and E.C. Monahan, AEON Verlag & Studio, Hanau. 1995, pp. 37-48.
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For citations:
Sukhinov A.I., Nikitina A.V., Chistyakov A.E. Using multichannel satellite images for predictive modelling the «bloom» phytoplankton processes in shallow waters on supercomputer. Computational Mathematics and Information Technologies. 2017;1(2). https://doi.org/10.23947/2587-8999-2017-2-128-140
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