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Research of reservoir watershed fine zoning and flood forecasting method

Author

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  • Jiazheng Lu

    (State Key Laboratory of Disaster Prevention and Reduction for Power Grid Transmission and Distribution Equipment
    State Grid Hunan Electric Company Disaster Prevention and Reduction Center)

  • Jun Guo

    (State Key Laboratory of Disaster Prevention and Reduction for Power Grid Transmission and Distribution Equipment
    State Grid Hunan Electric Company Disaster Prevention and Reduction Center)

  • Li Yang

    (State Key Laboratory of Disaster Prevention and Reduction for Power Grid Transmission and Distribution Equipment
    State Grid Hunan Electric Company Disaster Prevention and Reduction Center)

  • Xunjian Xu

    (State Key Laboratory of Disaster Prevention and Reduction for Power Grid Transmission and Distribution Equipment
    State Grid Hunan Electric Company Disaster Prevention and Reduction Center)

Abstract

Flood disaster is an important threat to the safe operation of reservoirs. Accurate flood forecasting can provide important information for optimal reservoir operation. Generally, the characteristic of precipitation spatial distribution is analyzed based on observation of several discreet preset stations. This cannot catch the rainstorm center all the time and will lead to deviation in the characteristic of precipitation spatial distribution. Therefore, it can hardly arrive at optimal sub-watershed delineation and flood modeling. Therefore, a novel method is proposed for analysis of characteristic of precipitation spatial distribution in consideration of rainfall distribution and the delay of rainfall–runoff concentration. Based on the analysis results of precipitation spatial distribution, several key sub-basins which have significant impact on the flood process can be recognized. And then the elaborate sub-watershed delineation and flood modeling approach is put forward consequently on these key sub-basins. The efficacy of the proposed method is estimated on the flood forecasting of Zhexi reservoir watershed. The results verify that the proposed method can significantly improve the flood forecasting precision, which can provide important decision-making basis for reservoir operation.

Suggested Citation

  • Jiazheng Lu & Jun Guo & Li Yang & Xunjian Xu, 2017. "Research of reservoir watershed fine zoning and flood forecasting method," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 89(3), pages 1291-1306, December.
    • Handle: RePEc:spr:nathaz:v:89:y:2017:i:3:d:10.1007_s11069-017-3017-x
    DOI: 10.1007/s11069-017-3017-x
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    References listed on IDEAS

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    1. Junhong Zhang & Lu Chen & Vijay Singh & Hongwen Cao & Dangwei Wang, 2015. "Determination of the distribution of flood forecasting error," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(2), pages 1389-1402, January.
    2. Qingqing Li & Shuo Ouyang, 2015. "Research on multi-objective joint optimal flood control model for cascade reservoirs in river basin system," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(3), pages 2097-2115, July.
    3. Zhangjun Liu & Shenglian Guo & Honggang Zhang & Dedi Liu & Guang Yang, 2016. "Comparative Study of Three Updating Procedures for Real-Time Flood Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(7), pages 2111-2126, May.
    4. Yong Peng & Xinguo Sun & Xiaoli Zhang & Huicheng Zhou & Zixin Zhang, 2017. "A Flood Forecasting Model that Considers the Impact of Hydraulic Projects by the Simulations of the Aggregate reservoir’s Retaining and Discharging," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(3), pages 1031-1045, February.
    5. Richard Arsenault & Marco Latraverse & Thierry Duchesne, 2016. "An Efficient Method to Correct Under-Dispersion in Ensemble Streamflow Prediction of Inflow Volumes for Reservoir Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4363-4380, September.
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    Cited by:

    1. Xinyu Wan & Qingyan Yang & Peng Jiang & Ping’an Zhong, 2019. "A Hybrid Model for Real-Time Probabilistic Flood Forecasting Using Elman Neural Network with Heterogeneity of Error Distributions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(11), pages 4027-4050, September.
    2. Zhaokai Yin & Weihong Liao & Xiaohui Lei & Hao Wang & Ruojia Wang, 2018. "Comparing the Hydrological Responses of Conceptual and Process-Based Models with Varying Rain Gauge Density and Distribution," Sustainability, MDPI, vol. 10(9), pages 1-22, September.

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