Репозиторий Евразийского национального университета имени Л.Н. Гумилева
Репозиторий Евразийского национального университета имени Л.Н. Гумилева
Репозиторий Евразийского национального университета имени Л.Н. Гумилева
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DEVELOPMENT OF AN INTEGRATED APPROACH TO THE ANALYSIS AND FORECAST OF HYDROGRAPHIC AND BATHYMETRIC DATA OF WATER BODIES AND TAILINGS PONDS

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Автор
Zhartybayeva, M.
Serik, N.
Nurzhanova, A.
Rakhimov, R.
Tulegenova, S.
Дата
2024
Редактор
Eastern-European Journal of Enterprise Technologies
ISSN
1729-3774
xmlui.dri2xhtml.METS-1.0.item-identifier-citation
Zhartybayeva, M., Serik, N., Nurzhanova, A., Rakhimov, R., Tulegenova, S. (2024). Development of an integrated approach to the analysis and forecast of hydrographic and bathymetric data of water bodies and tailings ponds. Eastern-European Journal of Enterprise Technologies, 1 (10 (127)), 36–46. doi: https://doi.org/10.15587/1729-4061.2024.299130
Аннотации
There is a need for an effective monitoring solution for water quality control in tailings dumps and adjacent water bodies in order to prevent environmental pollution. This article highlights the importance of water quality monitoring and surveillance to prevent pollution. It is proposed to develop a mobile robotic complex equipped with sensors for monitoring water bodies and tailings, which is also capable of measuring underwater topographic data. The objects of study were a tailings pond and water bodies. The authors analyzed existing technical monitoring solutions, designed and developed a robotic complex, echolocation device, tested them on specific sites (the tailings dump of the Zhayrem Mining and Processing Plant and the Ishim River), conducted laboratory analysis of water samples, classified the results. Additionally, they obtained 2D and 3D maps of the bottom, and entered all collected data into a developed database and software. The developed complex demonstrated high accuracy of movement (an error of about 0.2 m on the x axis and 0.1 m on the y axis) and the ability to register environmental parameters such as temperature, humidity, PH. Data analysis for 2021–2023 showed a significant excess of recycled water discharged into the evaporator pond, which emphasizes the importance of monitoring and management of water resources. The research applies ARIMA models, neural networks to predict water body parameters. The results obtained indicate the high efficiency of the developed robotic complex and methods for analyzing data on water resources. These methods can be used in industry, scientific research and environmental projects to regularly monitor water quality and take measures to protect it
URI
http://repository.enu.kz/handle/enu/30679
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