Real-time optimization of a large-scale reservoir operation in Thailand using adaptive inflow prediction with medium-range ensemble precipitation forecasts
Study region: The Sirikit Dam in the Nan River Basin is located on a main tributary of the Chao Phraya River in Thailand. Study focus: This study investigates forecasting river flows and real-time optimization of dam release using a distributed hydrological model with ensemble weather forecasting fo...
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| Format: | Article |
| Language: | English |
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Elsevier
2021-12-01
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| Series: | Journal of Hydrology: Regional Studies |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214581821001683 |
| _version_ | 1818461806927020032 |
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| author | Thatkiat Meema Yasuto Tachikawa Yutaka Ichikawa Kazuaki Yorozu |
| author_facet | Thatkiat Meema Yasuto Tachikawa Yutaka Ichikawa Kazuaki Yorozu |
| author_sort | Thatkiat Meema |
| collection | DOAJ |
| description | Study region: The Sirikit Dam in the Nan River Basin is located on a main tributary of the Chao Phraya River in Thailand. Study focus: This study investigates forecasting river flows and real-time optimization of dam release using a distributed hydrological model with ensemble weather forecasting for reservoir operations which provide hydropower and irrigation facilities in Thailand during a case study of the 2019 drought event. Medium-range ensemble precipitation forecasts were employed using a hydrological model to predict the real-time reservoir inflow. Real-time optimization of the water release strategy determined a week in advance with an effective initial condition for hydropower generation and irrigation was conducted with different scenarios using dynamic programming considering inflow predictions. New hydrological insights for the region: The medium-range ensemble precipitation forecast conducted by the European Centre for Medium Range Weather Forecasts was used to quantify precipitation for the study basin. The ensemble precipitation forecast with the hydrological model was employed for inflow prediction of the study basin which was located in a tropical climate with a distinct wet and dry season. The initial conditions of the hydrological model largely influenced the real-time inflow forecast. To determine the initial conditions of the model, the empirical data assimilation considering a drainage area factor was utilized and observed precipitation data were used for model input forcing data during the initial analysis period. This method improved the reservoir inflow prediction and real-time reservoir optimization using dynamic programming with considering ensemble forecasts provided more efficient operating decisions than employing historical data. The resulting information will be useful for water resource management, which may be adapted to other basins in the study region. |
| first_indexed | 2024-12-14T23:52:00Z |
| format | Article |
| id | doaj.art-d5852aaf49474934b3f73a754b030b2f |
| institution | Directory Open Access Journal |
| issn | 2214-5818 |
| language | English |
| last_indexed | 2024-12-14T23:52:00Z |
| publishDate | 2021-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Hydrology: Regional Studies |
| spelling | doaj.art-d5852aaf49474934b3f73a754b030b2f2022-12-21T22:43:14ZengElsevierJournal of Hydrology: Regional Studies2214-58182021-12-0138100939Real-time optimization of a large-scale reservoir operation in Thailand using adaptive inflow prediction with medium-range ensemble precipitation forecastsThatkiat Meema0Yasuto Tachikawa1Yutaka Ichikawa2Kazuaki Yorozu3Correspondence to: Department of Civil and Earth Resources Engineering, Kyoto University, C1, Nishikyo-ku, Kyoto 615-8540, Japan.; Department of Civil and Earth Resources Engineering, Kyoto University, Kyoto, JapanDepartment of Civil and Earth Resources Engineering, Kyoto University, Kyoto, JapanDepartment of Civil and Earth Resources Engineering, Kyoto University, Kyoto, JapanDepartment of Civil and Earth Resources Engineering, Kyoto University, Kyoto, JapanStudy region: The Sirikit Dam in the Nan River Basin is located on a main tributary of the Chao Phraya River in Thailand. Study focus: This study investigates forecasting river flows and real-time optimization of dam release using a distributed hydrological model with ensemble weather forecasting for reservoir operations which provide hydropower and irrigation facilities in Thailand during a case study of the 2019 drought event. Medium-range ensemble precipitation forecasts were employed using a hydrological model to predict the real-time reservoir inflow. Real-time optimization of the water release strategy determined a week in advance with an effective initial condition for hydropower generation and irrigation was conducted with different scenarios using dynamic programming considering inflow predictions. New hydrological insights for the region: The medium-range ensemble precipitation forecast conducted by the European Centre for Medium Range Weather Forecasts was used to quantify precipitation for the study basin. The ensemble precipitation forecast with the hydrological model was employed for inflow prediction of the study basin which was located in a tropical climate with a distinct wet and dry season. The initial conditions of the hydrological model largely influenced the real-time inflow forecast. To determine the initial conditions of the model, the empirical data assimilation considering a drainage area factor was utilized and observed precipitation data were used for model input forcing data during the initial analysis period. This method improved the reservoir inflow prediction and real-time reservoir optimization using dynamic programming with considering ensemble forecasts provided more efficient operating decisions than employing historical data. The resulting information will be useful for water resource management, which may be adapted to other basins in the study region.http://www.sciencedirect.com/science/article/pii/S2214581821001683Ensemble inflow forecastingData assimilationDistributed hydrologic modelReservoir optimizationDynamic programingThailand |
| spellingShingle | Thatkiat Meema Yasuto Tachikawa Yutaka Ichikawa Kazuaki Yorozu Real-time optimization of a large-scale reservoir operation in Thailand using adaptive inflow prediction with medium-range ensemble precipitation forecasts Journal of Hydrology: Regional Studies Ensemble inflow forecasting Data assimilation Distributed hydrologic model Reservoir optimization Dynamic programing Thailand |
| title | Real-time optimization of a large-scale reservoir operation in Thailand using adaptive inflow prediction with medium-range ensemble precipitation forecasts |
| title_full | Real-time optimization of a large-scale reservoir operation in Thailand using adaptive inflow prediction with medium-range ensemble precipitation forecasts |
| title_fullStr | Real-time optimization of a large-scale reservoir operation in Thailand using adaptive inflow prediction with medium-range ensemble precipitation forecasts |
| title_full_unstemmed | Real-time optimization of a large-scale reservoir operation in Thailand using adaptive inflow prediction with medium-range ensemble precipitation forecasts |
| title_short | Real-time optimization of a large-scale reservoir operation in Thailand using adaptive inflow prediction with medium-range ensemble precipitation forecasts |
| title_sort | real time optimization of a large scale reservoir operation in thailand using adaptive inflow prediction with medium range ensemble precipitation forecasts |
| topic | Ensemble inflow forecasting Data assimilation Distributed hydrologic model Reservoir optimization Dynamic programing Thailand |
| url | http://www.sciencedirect.com/science/article/pii/S2214581821001683 |
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