44 citations as recorded by crossref.

1. Extreme seasonal droughts and floods in Amazonia: causes, trends and impacts J. Marengo & J. Espinoza https://doi.org/10.1002/joc.4420
2. A New Approach to Use Load Duration Curves to Evaluate Water Quality: A Study in the Doce River Basin, Brazil L. Serrano et al. https://doi.org/10.3390/w12030811
3. Predictability of daily streamflow for the great rivers of South America based on a simple metric I. Petry et al. https://doi.org/10.1080/02626667.2022.2139620
4. Impact of Geology on Seasonal Hydrological Predictability in Alpine Regions by a Sensitivity Analysis Framework M. Stergiadi et al. https://doi.org/10.3390/w12082255
5. Potential skill of continental-scale, medium-range ensemble streamflow forecasts for flood prediction in South America V. Siqueira et al. https://doi.org/10.1016/j.jhydrol.2020.125430
6. A Decomposition-based Multi-model and Multi-parameter ensemble forecast framework for monthly streamflow forecasting J. Wang et al. https://doi.org/10.1016/j.jhydrol.2023.129083
7. Assessing the performance of global hydrological models for capturing peak river flows in the Amazon basin J. Towner et al. https://doi.org/10.5194/hess-23-3057-2019
8. Community responses to flood early warning system: Case study in Kaijuri Union, Bangladesh S. Fakhruddin et al. https://doi.org/10.1016/j.ijdrr.2015.08.004
9. On the Dominant Factor Controlling Seasonal Hydrological Forecast Skill in China X. Zhang et al. https://doi.org/10.3390/w9110902
10. 100 Years of Progress in Hydrology C. Peters-Lidard et al. https://doi.org/10.1175/AMSMONOGRAPHS-D-18-0019.1
11. Forecasting annual maximum water level for the Negro River at Manaus using dynamical seasonal predictions A. Chevuturi et al. https://doi.org/10.1016/j.cliser.2023.100342
12. Consistent initial conditions for the Saint-Venant equations in river network modeling C. Yu et al. https://doi.org/10.5194/hess-21-4959-2017
13. Daily water level forecasting with limited data using cluster- and season-based transfer learning Z. Huang et al. https://doi.org/10.1016/j.scitotenv.2026.181923
14. Automated Detection of Instability-Inducing Channel Geometry Transitions in Saint-Venant Simulation of Large-Scale River Networks C. Yu et al. https://doi.org/10.3390/w13162236
15. Near-real-time adjusted reanalysis forcing data for hydrology P. Berg et al. https://doi.org/10.5194/hess-22-989-2018
16. Sub seasonal streamflow forecast assessment at large-scale basins E. Schmitt Quedi & F. Mainardi Fan https://doi.org/10.1016/j.jhydrol.2020.124635
17. Uncertainty in the extreme flood magnitude estimates of large-scale flood hazard models L. Devitt et al. https://doi.org/10.1088/1748-9326/abfac4
18. The role of floodplain width and alluvial bar growth as a precursor for the formation of anabranching rivers S. Morón et al. https://doi.org/10.1016/j.geomorph.2016.10.026
19. Attribution of Amazon floods to modes of climate variability: A review J. Towner et al. https://doi.org/10.1002/met.1949
20. Generating Ensemble Streamflow Forecasts: A Review of Methods and Approaches Over the Past 40 Years M. Troin et al. https://doi.org/10.1029/2020WR028392
21. Improving river routing algorithms to efficiently implement canal water diversion schemes in global hydrological models N. Yoden et al. https://doi.org/10.3178/hrl.18.7
22. Testing conceptual and physically based soil hydrology schemes against observations for the Amazon Basin M. Guimberteau et al. https://doi.org/10.5194/gmd-7-1115-2014
23. Conditioning ensemble streamflow prediction with the North Atlantic Oscillation improves skill at longer lead times S. Donegan et al. https://doi.org/10.5194/hess-25-4159-2021
24. An overview of approaches for reducing uncertainties in hydrological forecasting: Progress and challenges A. Panchanathan et al. https://doi.org/10.1016/j.earscirev.2024.104956
25. Verification of inflow into hydropower reservoirs using ensemble forecasts of the TIGGE database for large scale basins in Brazil F. Fan et al. https://doi.org/10.1016/j.ejrh.2015.05.012
26. Future changes in precipitation and impacts on extreme streamflow over Amazonian sub-basins M. Guimberteau et al. https://doi.org/10.1088/1748-9326/8/1/014035
27. Seasonal streamflow forecasts in the Ahlergaarde catchment, Denmark: the effect of preprocessing and post-processing on skill and statistical consistency D. Lucatero et al. https://doi.org/10.5194/hess-22-3601-2018
28. An experimental seasonal hydrological forecasting system over the Yellow River basin – Part 1: Understanding the role of initial hydrological conditions X. Yuan et al. https://doi.org/10.5194/hess-20-2437-2016
29. Skill of a global forecasting system in seasonal ensemble streamflow prediction N. Candogan Yossef et al. https://doi.org/10.5194/hess-21-4103-2017
30. Recurrent neural networks for rainfall-runoff modeling of small Amazon catchments L. de Mendonça et al. https://doi.org/10.1007/s40808-022-01626-w
31. GloFAS – global ensemble streamflow forecasting and flood early warning L. Alfieri et al. https://doi.org/10.5194/hess-17-1161-2013
32. A first integrated modelling of a river-lagoon large-scale hydrological system for forecasting purposes V. Lopes et al. https://doi.org/10.1016/j.jhydrol.2018.08.011
33. On the sources of global land surface hydrologic predictability S. Shukla et al. https://doi.org/10.5194/hess-17-2781-2013
34. Seasonal streamflow forecasting in South America’s largest rivers I. Petry et al. https://doi.org/10.1016/j.ejrh.2023.101487
35. A review on climate‐model‐based seasonal hydrologic forecasting: physical understanding and system development X. Yuan et al. https://doi.org/10.1002/wat2.1088
36. Postprocessing continental-scale, medium-range ensemble streamflow forecasts in South America using Ensemble Model Output Statistics and Ensemble Copula Coupling V. Siqueira et al. https://doi.org/10.1016/j.jhydrol.2021.126520
37. Analyzing the sensitivity of drought recovery forecasts to land surface initial conditions C. DeChant & H. Moradkhani https://doi.org/10.1016/j.jhydrol.2014.10.021
38. Multi-model Hydroclimate Projections for the Alabama-Coosa-Tallapoosa River Basin in the Southeastern United States S. Gangrade et al. https://doi.org/10.1038/s41598-020-59806-6
39. Quantifying Streamflow Forecast Skill Elasticity to Initial Condition and Climate Prediction Skill A. Wood et al. https://doi.org/10.1175/JHM-D-14-0213.1
40. An index of Brazil’s vulnerability to expected increases in natural flash flooding and landslide disasters in the context of climate change N. Debortoli et al. https://doi.org/10.1007/s11069-016-2705-2
41. Assimilating in situ and radar altimetry data into a large-scale hydrologic-hydrodynamic model for streamflow forecast in the Amazon R. Paiva et al. https://doi.org/10.5194/hess-17-2929-2013
42. Benchmarking seasonal forecasting skill using river flow persistence in Irish catchments D. Foran Quinn et al. https://doi.org/10.1080/02626667.2021.1874612
43. An Efficient Approach for Estimating Streamflow Forecast Skill Elasticity L. Arnal et al. https://doi.org/10.1175/JHM-D-16-0259.1
44. Spatio‐Temporal Model Variance‐Covariance Approach to Assimilating Streamflow Observations Into a Distributed Landscape Water Balance Model S. Tian et al. https://doi.org/10.1029/2021WR031649