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Considering different streamflow forecast horizons in the quantitative flood risk analysis for a multi-reservoir system

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  • Gong, Yu
  • Liu, Pan
  • Zhang, Jun
  • Liu, Dedi
  • Zhang, Xiaoqi
  • Zhang, Xiaojing

Abstract

The flood risk analysis of a multi-reservoir system is based on the forecasted streamflow, whose time length is the forecast horizon (FH). FHs are generally different for each reservoir while the operation horizon (OH) is the same in a multi-reservoir system. To bridge the gap between the FHs and the OH of the multi-reservoir system, this study aims to develop a two-stage flood risk analysis method, specifically considering different FHs of each reservoir. In the first stage (the time period within the FHs), multinormal distribution of multi-reservoir storage was deduced by using the multivariate autoregressive model. In the second stage (the time period between the FHs and the OH), flood risk was calculated by using the reservoir routing for design flood hydrographs. The total flood risk within the OH incorporated the risks in the first and second stages. Finally, the joint effective FHs corresponding to the minimum total flood risk could be identified by numerical experiments. The results for the case study indicate that: (1) the proposed two-stage flood risk analysis utilizes different FHs in the multi-reservoir system and bridge the gap between the FHs and the OH; (2) the joint effective FHs are not constants and change with inflow conditions.

Suggested Citation

  • Gong, Yu & Liu, Pan & Zhang, Jun & Liu, Dedi & Zhang, Xiaoqi & Zhang, Xiaojing, 2020. "Considering different streamflow forecast horizons in the quantitative flood risk analysis for a multi-reservoir system," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    • Handle: RePEc:eee:reensy:v:204:y:2020:i:c:s0951832020306293
    DOI: 10.1016/j.ress.2020.107128
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    2. Gong, Yu & Liu, Pan & Ming, Bo & Feng, Maoyuan & Huang, Kangdi & Wang, Yibo, 2022. "Identifying the functional form of operating rules for hydro–photovoltaic hybrid power systems," Energy, Elsevier, vol. 243(C).
    3. Rajabzadeh, Vida & Hekmatzadeh, Ali Akbar & Tabatabaie Shourijeh, Piltan & Torabi Haghighi, Ali, 2023. "Introducing a probabilistic framework to measure dam overtopping risk for dams benefiting from dual spillways," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    4. Farahmand, Hamed & Liu, Xueming & Dong, Shangjia & Mostafavi, Ali & Gao, Jianxi, 2022. "A Network Observability Framework for Sensor Placement in Flood Control Networks to Improve Flood Situational Awareness and Risk Management," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    5. Zhu, Tiantian & Haugen, Stein & Liu, Yiliu & Yang, Xue, 2023. "A value of prediction model to estimate optimal response time to threats for accident prevention," Reliability Engineering and System Safety, Elsevier, vol. 232(C).

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