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タイトル: Real-time optimization of a large-scale reservoir operation in Thailand using adaptive inflow prediction with medium-range ensemble precipitation forecasts
著者: Meema, Thatkiat
Tachikawa, Yasuto  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0002-1647-8899 (unconfirmed)
Ichikawa, Yutaka  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0003-1269-2975 (unconfirmed)
Yorozu, Kazuaki  kyouindb  KAKEN_id
著者名の別形: 立川, 康人
市川, 温
萬, 和明
キーワード: Ensemble inflow forecasting
Data assimilation
Distributed hydrologic model
Reservoir optimization
Dynamic programing
Thailand
発行日: Dec-2021
出版者: Elsevier BV
誌名: Journal of Hydrology: Regional Studies
巻: 38
論文番号: 100939
抄録: 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.
著作権等: © 2021 The Authors. Published by Elsevier B.V.
This is an open access article under the CC BY-NC-ND license
URI: http://hdl.handle.net/2433/279268
DOI(出版社版): 10.1016/j.ejrh.2021.100939
出現コレクション:学術雑誌掲載論文等

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