41 citations as recorded by crossref.

1. A post-processing machine learning framework for bias-correcting National Water Model outputs by accounting for dominant streamflow drivers S. Naser Neisary et al. https://doi.org/10.1016/j.envsoft.2025.106459
2. Flexible forecast value metric suitable for a wide range of decisions: application using probabilistic subseasonal streamflow forecasts R. Laugesen et al. https://doi.org/10.5194/hess-27-873-2023
3. Quantifying streamflow predictive uncertainty for the optimization of short-term cascade hydropower stations operations Y. Liu et al. https://doi.org/10.1016/j.jhydrol.2021.127376
4. airGRteaching: an open-source tool for teaching hydrological modeling with R O. Delaigue et al. https://doi.org/10.5194/hess-27-3293-2023
5. Research on Reservoir Optimal Operation Based on Long-Term and Mid-Long-Term Nested Models C. Mo et al. https://doi.org/10.3390/w14040608
6. Short-term hydropower optimization driven by innovative time-adapting econometric model D. Avesani et al. https://doi.org/10.1016/j.apenergy.2021.118510
7. XGBoost (Aşırı Gradyan Artırımlı Karar Ağaçları) ile Hidroelektrik Enerji Tahmini B. Atalay & K. Zor https://doi.org/10.21605/cukurovaumfd.1666062
8. Multi-objective operation of cascade reservoirs based on short-term ensemble streamflow prediction S. He et al. https://doi.org/10.1016/j.jhydrol.2022.127936
9. A framework to evaluate and compare synthetic streamflow scenario generation models F. Treistman et al. https://doi.org/10.1590/2318-0331.282320230115
10. Synthetic Forecast Ensembles for Evaluating Forecast Informed Reservoir Operations Z. Brodeur et al. https://doi.org/10.1029/2023WR034898
11. Simulation of hydropower at subcontinental to global scales: a state-of-the-art review S. Turner & N. Voisin https://doi.org/10.1088/1748-9326/ac4e38
12. Day-ahead energy production in small hydropower plants: uncertainty-aware forecasts through effective coupling of knowledge and data K. Drakaki et al. https://doi.org/10.5194/adgeo-56-155-2022
13. Comparing a long short-term memory (LSTM) neural network with a physically-based hydrological model for streamflow forecasting over a Canadian catchment B. Sabzipour et al. https://doi.org/10.1016/j.jhydrol.2023.130380
14. Digitalization, Industry 4.0, Data, KPIs, Modelization and Forecast for Energy Production in Hydroelectric Power Plants: A Review C. Pepe & S. Zanoli https://doi.org/10.3390/en17040941
15. Value of various elements of the hydrological forecasting chain: Is there a successful pathway for improving the overall performance? J. Davidson-Chaput et al. https://doi.org/10.1016/j.jhydrol.2025.133186
16. Forecast Families: A New Method to Systematically Evaluate the Benefits of Improving the Skill of an Existing Forecast C. Rougé et al. https://doi.org/10.1061/JWRMD5.WRENG-5934
17. Streamflow prediction across Canada’s southern provinces using gradient boosting M. Alipour https://doi.org/10.1080/23249676.2025.2606416
18. Choosing between post-processing precipitation forecasts or chaining several uncertainty quantification tools in hydrological forecasting systems E. Valdez et al. https://doi.org/10.5194/hess-26-197-2022
19. Application of Swarm Intelligence and Evolutionary Computation Algorithms for Optimal Reservoir Operation A. Yaghoubzadeh-Bavandpour et al. https://doi.org/10.1007/s11269-022-03141-0
20. Reservoir Reliability as Affected by Climate Change and Strategies for Adaptation H. Chaves et al. https://doi.org/10.3390/w15132323
21. An Operational Streamflow Forecasting System for a Data-Scarce Catchment in Tanzania P. Ndomba & Å. Killingtveit https://doi.org/10.3390/w18020285
22. Using spatial water balance to regionalize long-term mean streamflow in a data-scarce Brazilian semi-arid basin A. Kolling Neto et al. https://doi.org/10.1016/j.jaridenv.2025.105528
23. Algorithmic-specific parameter-less techniques for optimal water supply in the downstream of the reservoir K. Baladaniya et al. https://doi.org/10.1080/09715010.2025.2612597
24. Long-, Medium-, and Short-Term Nested Optimized-Scheduling Model for Cascade Hydropower Plants: Development and Practical Application L. Shang et al. https://doi.org/10.3390/w14101586
25. The relative influences of hydrologic information and dams’ hydropower scheduling decisions on electricity price forecasts H. Ssembatya et al. https://doi.org/10.1016/j.egyr.2026.109203
26. Water resources management: a bibliometric analysis and future research directions M. Favereau et al. https://doi.org/10.1007/s10479-024-06339-0
27. Software library to quantify the value of forecasts for decision-making: Case study on sensitivity to damages R. Laugesen et al. https://doi.org/10.1016/j.envsoft.2025.106697
28. Source identification methods in riverine systems: a combined analysis of transient storage and fractional dispersion J. Chabokpour https://doi.org/10.2166/wqrj.2025.063
29. Connecting hydrological modelling and forecasting from global to local scales: Perspectives from an international joint virtual workshop A. Dasgupta et al. https://doi.org/10.1111/jfr3.12880
30. A mixed-integer linear programming model for hydro unit commitment considering operation constraint priorities X. Wu et al. https://doi.org/10.1016/j.renene.2023.01.006
31. Metaheuristic evolutionary deep learning model based on temporal convolutional network, improved aquila optimizer and random forest for rainfall-runoff simulation and multi-step runoff prediction X. Qiao et al. https://doi.org/10.1016/j.eswa.2023.120616
32. Evaluation of Ensemble Inflow Forecasts for Reservoir Management in Flood Situations J. Mendes & R. Maia https://doi.org/10.3390/hydrology10020028
33. Effect of the quality of streamflow forecasts on the operation of cascade hydropower stations using stochastic optimization models Y. Liu et al. https://doi.org/10.1016/j.energy.2023.127298
34. The Economic Value of Hydrometeorological Information in the Planning of Large-Scale Hydropower System Operations A. Dalcin et al. https://doi.org/10.1061/JWRMD5.WRENG-6591
35. Assessing the National Water Model’s Streamflow Estimates Using a Multi-Decade Retrospective Dataset across the Contiguous United States M. Abdelkader et al. https://doi.org/10.3390/w15132319
36. Advancing Medium-Range Streamflow Forecasting for Large Hydropower Reservoirs in Brazil by Means of Continental-Scale Hydrological Modeling A. Kolling Neto et al. https://doi.org/10.3390/w15091693
37. Improving multi-model ensemble streamflow forecasts by combining lumped, distributed and deep learning hydrological models W. Armstrong et al. https://doi.org/10.1080/02626667.2025.2471430
38. Mitigating systemic risk in cascade hydropower generation: A high-dimensional vine copula framework for correlated inflow uncertainties J. Li et al. https://doi.org/10.1016/j.energy.2026.141185
39. Optimizing the Management of Multireservoir Systems Under Shifting Flow Regimes V. Espanmanesh & A. Tilmant https://doi.org/10.1029/2021WR030582
40. Hydropower System Operation and the Quality of Short-Term Hydrologic Ensemble Forecasts M. Osina Torres et al. https://doi.org/10.1061/JWRMD5.WRENG-5608
41. Optimising ensemble streamflow predictions with bias correction and data assimilation techniques M. Tanguy et al. https://doi.org/10.5194/hess-29-1587-2025