Data Processing Technology for the Forecasting of the Water Inflow into a Reservoir with the Use of Earth Remote Sensing and the Network of Meteorological and Hydrological Posts
Management of the hydropower plants requires the economically efficient use of water re-sources based on the forecasts and simulation models of the hydropower plant and the reservoir. There are various data sources for the water inflow forecasting: meteorological and hydrological posts, Earth remote...
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| Format: | Article |
| Language: | English |
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Academy of Sciences of Moldova
2022-11-01
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| Series: | Problems of the Regional Energetics |
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| Online Access: | https://journal.ie.asm.md/assets/files/09_04_56_2022.pdf |
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| author | Eroshenko S.A. Matrenin P.V. Khalyasmaa A.I. Klimenko D.E. Sidorova A.V. |
| author_facet | Eroshenko S.A. Matrenin P.V. Khalyasmaa A.I. Klimenko D.E. Sidorova A.V. |
| author_sort | Eroshenko S.A. |
| collection | DOAJ |
| description | Management of the hydropower plants requires the economically efficient use of water re-sources based on the forecasts and simulation models of the hydropower plant and the reservoir. There are various data sources for the water inflow forecasting: meteorological and hydrological posts, Earth remote sensing. However, the problem arises of combining the specified heteroge-neous data for aggregated processing with the use of machine learning methods. The research goal is to design an architecture of a system for collecting and processing the data from various sources to operational forecast of the water inflow and the reservoir water-level. It was achieved by analyzing and selecting the sources and methods for the use of Earth remote sensing data; observing the main principles of hydrological modeling; assessing the availability of the differ-ent data; analyzing the ways of increasing the observability of the hydrological objects by in-stalling additional meteorological and hydrological posts; and designing a technology for the au-tomatic data collection and processing. The most significant results are developed architecture of the data collection and processing system and the technology for aggregating heterogeneous data with the use of machine learning methods. It is aimed to reduce the error of short-term forecast-ing of the water inflow to the reservoir. The significance of the results lies in the fact that the proposed technology was offered and justified for a real hydropower plant; and it can improve the water resources management efficiency: increase the energy generation, minimize the sterile spills, increase the flood forecasting horizon and reduce the risk of flooding during the spring high water. |
| format | Article |
| id | doaj-art-532ea3ee6cf44f3787a01ced918624c7 |
| institution | Kabale University |
| issn | 1857-0070 |
| language | English |
| publishDate | 2022-11-01 |
| publisher | Academy of Sciences of Moldova |
| record_format | Article |
| series | Problems of the Regional Energetics |
| spelling | doaj-art-532ea3ee6cf44f3787a01ced918624c72025-08-20T03:56:19ZengAcademy of Sciences of MoldovaProblems of the Regional Energetics1857-00702022-11-0156410010910.52254/1857-0070.2022.4-56.09Data Processing Technology for the Forecasting of the Water Inflow into a Reservoir with the Use of Earth Remote Sensing and the Network of Meteorological and Hydrological PostsEroshenko S.A.0Matrenin P.V.1Khalyasmaa A.I.2Klimenko D.E.3Sidorova A.V.4Ural Federal University, Yekaterinburg, Russian FederationUral Federal University, Yekaterinburg, Russian FederationUral Federal University, Yekaterinburg, Russian FederationUral Federal University, Yekaterinburg, Russian FederationNovosibirsk State Technical UniversityManagement of the hydropower plants requires the economically efficient use of water re-sources based on the forecasts and simulation models of the hydropower plant and the reservoir. There are various data sources for the water inflow forecasting: meteorological and hydrological posts, Earth remote sensing. However, the problem arises of combining the specified heteroge-neous data for aggregated processing with the use of machine learning methods. The research goal is to design an architecture of a system for collecting and processing the data from various sources to operational forecast of the water inflow and the reservoir water-level. It was achieved by analyzing and selecting the sources and methods for the use of Earth remote sensing data; observing the main principles of hydrological modeling; assessing the availability of the differ-ent data; analyzing the ways of increasing the observability of the hydrological objects by in-stalling additional meteorological and hydrological posts; and designing a technology for the au-tomatic data collection and processing. The most significant results are developed architecture of the data collection and processing system and the technology for aggregating heterogeneous data with the use of machine learning methods. It is aimed to reduce the error of short-term forecast-ing of the water inflow to the reservoir. The significance of the results lies in the fact that the proposed technology was offered and justified for a real hydropower plant; and it can improve the water resources management efficiency: increase the energy generation, minimize the sterile spills, increase the flood forecasting horizon and reduce the risk of flooding during the spring high water.https://journal.ie.asm.md/assets/files/09_04_56_2022.pdfarchitecture of the information systemdata collection and processingearth remote sensinghydrological postsmeteorological postshydropower plantinflow forecastingreservoir. |
| spellingShingle | Eroshenko S.A. Matrenin P.V. Khalyasmaa A.I. Klimenko D.E. Sidorova A.V. Data Processing Technology for the Forecasting of the Water Inflow into a Reservoir with the Use of Earth Remote Sensing and the Network of Meteorological and Hydrological Posts Problems of the Regional Energetics architecture of the information system data collection and processing earth remote sensing hydrological posts meteorological posts hydropower plant inflow forecasting reservoir. |
| title | Data Processing Technology for the Forecasting of the Water Inflow into a Reservoir with the Use of Earth Remote Sensing and the Network of Meteorological and Hydrological Posts |
| title_full | Data Processing Technology for the Forecasting of the Water Inflow into a Reservoir with the Use of Earth Remote Sensing and the Network of Meteorological and Hydrological Posts |
| title_fullStr | Data Processing Technology for the Forecasting of the Water Inflow into a Reservoir with the Use of Earth Remote Sensing and the Network of Meteorological and Hydrological Posts |
| title_full_unstemmed | Data Processing Technology for the Forecasting of the Water Inflow into a Reservoir with the Use of Earth Remote Sensing and the Network of Meteorological and Hydrological Posts |
| title_short | Data Processing Technology for the Forecasting of the Water Inflow into a Reservoir with the Use of Earth Remote Sensing and the Network of Meteorological and Hydrological Posts |
| title_sort | data processing technology for the forecasting of the water inflow into a reservoir with the use of earth remote sensing and the network of meteorological and hydrological posts |
| topic | architecture of the information system data collection and processing earth remote sensing hydrological posts meteorological posts hydropower plant inflow forecasting reservoir. |
| url | https://journal.ie.asm.md/assets/files/09_04_56_2022.pdf |
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