4.7 Article

GRAPS: Generalized Multi-Reservoir Analyses using probabilistic streamflow forecasts

期刊

ENVIRONMENTAL MODELLING & SOFTWARE
卷 133, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2020.104802

关键词

Reservoir modeling; Software development; Simulation; Optimization; Water resources management

资金

  1. National Science Foundation [1442909, 1805293]
  2. Directorate For Engineering
  3. Div Of Chem, Bioeng, Env, & Transp Sys [1805293] Funding Source: National Science Foundation
  4. Division of Computing and Communication Foundations
  5. Direct For Computer & Info Scie & Enginr [1442909] Funding Source: National Science Foundation

向作者/读者索取更多资源

A multi-reservoir simulation-optimization model GRAPS, Generalized Multi-Reservoir Analyses using Probabilistic Streamflow Forecasts, is developed in which reservoirs and users across the basin are represented using a node-link representation. Unlike existing reservoir modeling software, GRAPS can handle probabilistic streamflow forecasts represented as ensembles for performing multi-reservoir prognostic water allocation and evaluate the reliability of forecast-based allocation with observed streamflow. GRAPS is applied to four linked reservoirs in the Jaguaribe Metropolitan Hydro-System (JMH) in Ceara, North East Brazil. Results from the historical simulation and the zero-inflow policy over the JMH system demonstrate the model's capability to support monthly water allocation and reproduce the observed monthly releases and storages. Additional analyses using streamflow forecast ensembles illustrate GRAP's abilities in developing storage-reliability curves under inflow-forecast uncertainty. Our analyses show that GRAPS is versatile and can be applied for 1) short-term operating policy studies, 2) long-term basin-wide planning evaluations, and 3) climate-information based application studies.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据