Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2019WR025226 |
Determining Inflow Forecast Horizon for Reservoir Operation | |
Zhao, Qiankun1; Cai, Ximing1; Li, Yu2 | |
2019-05-01 | |
发表期刊 | WATER RESOURCES RESEARCH |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2019 |
卷号 | 55期号:5页码:4066-4081 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; Peoples R China |
英文摘要 | A critical study issue to incorporate imperfect forecast in real-time reservoir operation is determining the forecast horizon. In this study, properties for the longest forecast horizon (LFH) and the effective forecast horizon (EFH) are derived from a multistage, deterministic optimization model for the operation of a single water supply reservoir with a concave benefit function. The LFH addresses the question of how long a forecast is sufficient to make an optimal reservoir release decision for the current stage if the effect of forecast uncertainty is not considered. The EFH represents a forecast horizon with the information for decision making as much as allowed by uncertainty effect control, which is set as prescribed decision reliability quantified by the error bound (i.e., the largest difference between the optimal release decisions made under any two inflow scenarios). The properties of LFH and EFH are used to specify the criteria and design the procedures for determining EFH and LFH. A hypothetical but typical case study is used to demonstrate the criteria and procedures. Both theoretical analysis and the case study results show that LFH and EFH are affected by multiple factors such as the reservoir capacity, inflow variability, forecast uncertainty, maximum allowable error bound, and ending storage estimate accuracy. LFH is longer with a larger capacity, smaller inflow variability, and smaller forecast uncertainty, and EFH is longer with smaller forecast uncertainty, larger error bound, and more accurate ending storage estimates. |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000474848500025 |
WOS关键词 | UNCERTAINTY ; PREDICTABILITY ; MODEL |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/183133 |
专题 | 资源环境科学 |
作者单位 | 1.Univ Illinois, Dept Civil & Environm Engn, Champaign, IL 61820 USA; 2.Dalian Univ Technol, Sch Hydraul Engn, Dalian, Peoples R China |
推荐引用方式 GB/T 7714 | Zhao, Qiankun,Cai, Ximing,Li, Yu. Determining Inflow Forecast Horizon for Reservoir Operation[J]. WATER RESOURCES RESEARCH,2019,55(5):4066-4081. |
APA | Zhao, Qiankun,Cai, Ximing,&Li, Yu.(2019).Determining Inflow Forecast Horizon for Reservoir Operation.WATER RESOURCES RESEARCH,55(5),4066-4081. |
MLA | Zhao, Qiankun,et al."Determining Inflow Forecast Horizon for Reservoir Operation".WATER RESOURCES RESEARCH 55.5(2019):4066-4081. |
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