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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/hess-2020-304
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2020-304
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  27 Jul 2020

27 Jul 2020

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This preprint is currently under review for the journal HESS.

Real-time reservoir flood control operation enhanced by data assimilation

Jingwen Zhang1,2, Ximing Cai2, Xiaohui Lei3, Pan Liu1, and Hao Wang3 Jingwen Zhang et al.
  • 1State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
  • 2Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
  • 3China Institute of Water Resources and Hydropower Research, Beijing 100038, China

Abstract. Real world reservoir operations are usually not fully automatic based on computer models; instead, reservoir operators conduct the operations based on their experiences, professional justification, as well as modeling support for some cases due to unavoidable gap between computer modeling and real world reservoir operation conditions. In this paper, we propose a human-machine interactive method, namely Real-time Optimization Model Enhanced by Data Assimilation (ROMEDA) for reservoirs which have complex storage and stage relations (e.g. long and narrow reservoirs). The system is composed of 1) an optimization model to search for optimal releases, 2) reservoir operators’ choices based on their experiences, knowledge, and behaviors, and 3) a reservoir storage-stage simulation and data assimilation schedule to update the storage based on real-time reservoir stage observations. For every time period and based on the updated storage, ROMEDA provides optimal releases as recommendations, actual releases made by operators, as well as a warning of flood risk when the storage exceeds a threshold level. ROMEDA does not assume that operators strictly accept the recommendations, and storage will be updated based on actual release at each time period. Via a case study on-channel reservoir, it is found that for both small and large flood events, ROMEDA, which integrates the advantages of both machine and human, shows better performance on flood risk mitigation and water use (hydropower) benefit than the case with historical operation records (HOR) or optimization with single/multi-objective. ROMEDA is one of the first attempts of a human-machine interactive method for online use of an optimization model for real-time reservoir operation based on integrated modeling, observation, and operators’ choice.

Jingwen Zhang et al.

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Short summary
Real-time reservoir flood control operation is controlled manually by reservoir operators based on their experiences and justifications, rather than by computer automatically. We use a human-machine interactive modeling method to combine computer optimization model, human’s consideration, and reservoir stage observations for actual decisions on release for real-time reservoir flood control operation. The proposed method can reduce the flood risk and improve water use benefit simultaneously.
Real-time reservoir flood control operation is controlled manually by reservoir operators based...
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