The simple network-based measuring system for improving the evaporation estimation
This paper presents a novel method for measuring the data for evaporation estimation as the key ingredient for the final decision of the reclamation form in the area of the Most Basin. The area has been intensively mined for many decades, resulting in significant landscape devastation, loss of natur...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2023-09-01
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| Series: | Production Engineering Archives |
| Subjects: | |
| Online Access: | https://doi.org/10.30657/pea.2023.29.38 |
| _version_ | 1827825302761373696 |
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| author | Dlouhá Dagmar Pospíšil Lukáš Dubovský Viktor |
| author_facet | Dlouhá Dagmar Pospíšil Lukáš Dubovský Viktor |
| author_sort | Dlouhá Dagmar |
| collection | DOAJ |
| description | This paper presents a novel method for measuring the data for evaporation estimation as the key ingredient for the final decision of the reclamation form in the area of the Most Basin. The area has been intensively mined for many decades, resulting in significant landscape devastation, loss of natural habitats, and negative environmental impact. Currently, it is assumed that by 2050, three large-scale reclamation projects will be implemented in the area and it is necessary to decide which form of reclamation to choose. Whether to build lakes according to the currently valid rehabilitation and reclamation plan or to leave the area of the quarries in succession with the support of spontaneous inflow of water up to a naturally sustainable water level. Whether the first or second option is approved, or a combination of both, the prediction of evaporation from the free water surface will always be of great importance. To deal with this goal, the available meteorological data must be combined with a suitable calculation method. In our work, we suggest utilizing a measuring network of meteorological devices that describe the character of the weather in a given area of interest in a long-term time series. Together with the state-of-the-art calibration of models for calculating evaporation, the measurement network helps to provide more accurate evaporation data for a given area. Based on the analysis of research results, it will be possible to choose a specific right decision and thus contribute to the long-term sustainability of these reclamations. |
| first_indexed | 2024-03-12T02:40:12Z |
| format | Article |
| id | doaj.art-600556a9c993495eb5b48f358d6dd1b2 |
| institution | Directory Open Access Journal |
| issn | 2353-7779 |
| language | English |
| last_indexed | 2024-03-12T02:40:12Z |
| publishDate | 2023-09-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Production Engineering Archives |
| spelling | doaj.art-600556a9c993495eb5b48f358d6dd1b22023-09-04T07:12:05ZengSciendoProduction Engineering Archives2353-77792023-09-0129331932710.30657/pea.2023.29.38The simple network-based measuring system for improving the evaporation estimationDlouhá Dagmar0Pospíšil Lukáš1Dubovský Viktor2VSB – Technical University Ostrava, Faculty of Civil Engineering, Department of Mathematics, Ludvíka Podéště 1875/17, 708 00 Ostrava-Poruba, Czech RepublicVSB – Technical University Ostrava, Faculty of Civil Engineering, Department of Mathematics, Ludvíka Podéště 1875/17, 708 00 Ostrava-Poruba, Czech RepublicVSB – Technical University Ostrava, Faculty of Civil Engineering, Department of Mathematics, Ludvíka Podéště 1875/17, 708 00 Ostrava-Poruba, Czech RepublicThis paper presents a novel method for measuring the data for evaporation estimation as the key ingredient for the final decision of the reclamation form in the area of the Most Basin. The area has been intensively mined for many decades, resulting in significant landscape devastation, loss of natural habitats, and negative environmental impact. Currently, it is assumed that by 2050, three large-scale reclamation projects will be implemented in the area and it is necessary to decide which form of reclamation to choose. Whether to build lakes according to the currently valid rehabilitation and reclamation plan or to leave the area of the quarries in succession with the support of spontaneous inflow of water up to a naturally sustainable water level. Whether the first or second option is approved, or a combination of both, the prediction of evaporation from the free water surface will always be of great importance. To deal with this goal, the available meteorological data must be combined with a suitable calculation method. In our work, we suggest utilizing a measuring network of meteorological devices that describe the character of the weather in a given area of interest in a long-term time series. Together with the state-of-the-art calibration of models for calculating evaporation, the measurement network helps to provide more accurate evaporation data for a given area. Based on the analysis of research results, it will be possible to choose a specific right decision and thus contribute to the long-term sustainability of these reclamations.https://doi.org/10.30657/pea.2023.29.38evaporationhydric recultivationcalibrationmeasuring networkregression |
| spellingShingle | Dlouhá Dagmar Pospíšil Lukáš Dubovský Viktor The simple network-based measuring system for improving the evaporation estimation Production Engineering Archives evaporation hydric recultivation calibration measuring network regression |
| title | The simple network-based measuring system for improving the evaporation estimation |
| title_full | The simple network-based measuring system for improving the evaporation estimation |
| title_fullStr | The simple network-based measuring system for improving the evaporation estimation |
| title_full_unstemmed | The simple network-based measuring system for improving the evaporation estimation |
| title_short | The simple network-based measuring system for improving the evaporation estimation |
| title_sort | simple network based measuring system for improving the evaporation estimation |
| topic | evaporation hydric recultivation calibration measuring network regression |
| url | https://doi.org/10.30657/pea.2023.29.38 |
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