Use of Ensemble-Based Forecasting Methods in Reservoir Operation: Issues and Implementation Challenges
Reservoir operations, water resources, and flood control management rely on accurate and reliable forecasting of stream flows. Ensemble streamflow forecasting (ESF) approaches in reservoir operations for flood control, hydropower, and water supply applications are increasingly used to improve real-time operations. Despite their advantages over standard operating procedure-based operations, limited applications of these in practice are noted. The present study discusses the global challenges in reservoir operations. It highlights that reservoir management issues are not effectively addressed by relying solely on optimization techniques based on ESFs. Instead, the key to effective management is transforming ESF results into reliable metrics that management can use directly for making multiobjective, multisite decisions across various time horizons. This paper provides a state-of-the-art review of ESF approaches and their applications, discusses advantages and limitations, and critically assesses implementation issues. Based on lessons from multiple pilot studies, recommendations are provided for implementing these approaches for various reservoir operations.
Authors
- Anant Patel (ORCID: https://orcid.org/0000-0001-6822-7883)
- Ramesh S. V. Teegavarapu (ORCID: https://orcid.org/0000-0002-8194-6038)
- Ayushi Panchal (ORCID: https://orcid.org/0000-0003-3847-2735)
- S. M. Yadav (ORCID: https://orcid.org/0000-0001-8480-2227)
- David C. Curtis
- Chandra S. Pathak
Institutions
- Nirma University (IN)
- Atlantic University (US)
- Sardar Vallabhbhai National Institute of Technology Surat (IN)
- State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering (CN)
- Florida Atlantic University (US)
Publication Details
- Journal
- Journal of Hydrologic Engineering
- Published
- 2025-05-19
- DOI
- https://doi.org/10.1061/jhyeff.heeng-6467
- Citations
- 3
- Primary Topic
- Water resources management and optimization
- Type
- article
- Field-Weighted Citation Impact
- 3.44