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 Ceará, 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.

建立了多储层模拟优化模型GRAPS，即使用概率流量预测的广义多储层分析，其中使用节点链接表示法来表示整个盆地的储层和用户。与现有的储层建模软件不同，GRAPS可以处理以集合体形式表示的概率水流预测，以执行多储层预后水分配，并利用观测到的水流评估基于预测的分配的可靠性。GRAPS应用于巴西东北部塞阿拉州Jaguaribe都市水力系统（JMH）的四个相连水库。历史模拟和JMH系统的零流量政策的结果表明，该模型具有支持每月水量分配和重现观察到的每月排放量和储存量的能力。使用流量预测集成进行的其他分析说明了GRAP在流量预测不确定性下开发存储可靠性曲线的能力。我们的分析表明，GRAPS具有多种用途，可用于1）短期运营政策研究，2）长期流域范围内的规划评估以及3）基于气候信息的应用研究。