2020 journal article
GRAPS: Generalized Multi-Reservoir Analyses using probabilistic streamflow forecasts
ENVIRONMENTAL MODELLING & SOFTWARE, 133.
author keywords: Reservoir modeling; Software development; Simulation; Optimization; Water resources management
TL;DR:
Analysis of the model's abilities in developing storage-reliability curves under inflow-forecast uncertainty 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.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
6. Clean Water and Sanitation
(Web of Science)
11. Sustainable Cities and Communities
(Web of Science)
13. Climate Action
(Web of Science; OpenAlex)
Source: Web Of Science
Added: November 9, 2020
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.