Adaptation of Cascade Hydropower Station Scheduling on A Headwater Stream of the Yangtze River under Changing Climate Conditions Journal Articles uri icon

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abstract

  • Cascade hydropower stations are effective in water resource utilization, regional water allocation, and flood risk management. Under changing climate conditions, water resources would experience complex temporal and spatial changes, which may lead to various issues relating to flood control and water resource management, and challenge the existing optimal scheduling of cascade hydropower stations. It is thus important to conduct a study on cascade hydropower station scheduling under changing climate conditions. In this study, the Jinsha River rainfall–discharge statistical model is developed based on the statistical relationship between meteorological and runoff indicators. Validation results indicate that the developed model is capable of generating satisfactory simulation results and thus can be used for future Jinsha River runoff projection under climate change. Meanwhile, the Providing Regional Climates for Impacts Studies (PRECIS) is run to project future rainfall in the Jinsha River basin under two General Circulation Models (ECHAM5 and HadAM3P), two scenarios (A1B and B2), and four periods (1961–1990, 1991–2020, 2021–2050, and 2051–2099). The regional climate modeling data are analyzed and then fed into the Jinsha hydrological model to analyze the trends of future discharge at Xiangjiaba Hydro Station. Adaptive scheduling strategies for cascade hydropower stations are discussed based on the future inflow trend analysis and current flood scheduling mode. It is suggested that cascade hydropower stations could be operated at flood limited water level (FLWL) during 2021–2099. In addition, the impoundment of cascade hydropower stations should be properly delayed during the post-flood season in response to the possible occurrence of increased and extended inflow in wet seasons.

authors

  • Zhai, Ming
  • Lin, Qian
  • Huang, Gordon
  • Zhu, Le
  • An, Kai
  • Li, Gong
  • Huang, Yue

publication date

  • April 22, 2017