35 citations as recorded by crossref.

1. Probabilistic Forecast of Ecological Drought in Rivers Based on Numerical Weather Forecast from S2S Dataset C. Cai et al.
2. A Model for Assessing the Importance of Runoff Forecasts in Periodic Climate on Hydropower Production S. Hao et al.
3. Advancing Sub-Seasonal to Seasonal Streamflow Forecasting in Canada: A Review of Conventional and Emerging Approaches for Operational Applications D. Nguyen et al.
4. A review of machine learning concepts and methods for addressing challenges in probabilistic hydrological post-processing and forecasting G. Papacharalampous & H. Tyralis
5. A data-assimilated SEAS5 forecasting framework for seasonal hydropower inflows in a snow-dominated basin G. Uysal et al.
6. Drought hazard assessment across Sweden's diverse hydro-climatic regimes C. Canedo Rosso et al.
7. Customizing large-scale hydrological models: Harnessing the open data realm for impactful local applications I. Pechlivanidis & J. Musuuza
8. Rational gaze: Presenting the open-source HYPEtools R package for analysis, visualization, and interpretation of hydrological models and datasets C. Brendel et al.
9. Catchment memory explains hydrological drought forecast performance S. Sutanto & H. Van Lanen
10. Conditioning ensemble streamflow prediction with the North Atlantic Oscillation improves skill at longer lead times S. Donegan et al.
11. Advancing traditional strategies for testing hydrological model fitness in a changing climate A. Todorović et al.
12. A framework of integrating heterogeneous data sources for monthly streamflow prediction using a state-of-the-art deep learning model W. Xu et al.
13. Leveraging GCM-based forecasts for enhanced seasonal streamflow prediction in diverse hydrological regimes M. Girons Lopez et al.
14. Daily ensemble river discharge reforecasts and real-time forecasts from the operational Global Flood Awareness System S. Harrigan et al.
15. Connecting hydrological modelling and forecasting from global to local scales: Perspectives from an international joint virtual workshop A. Dasgupta et al.
16. Skill-informed seamless communication of European S2S hydrological forecasts I. Pechlivanidis & L. Crochemore
17. Evaluation of Earth Observations and In Situ Data Assimilation for Seasonal Hydrological Forecasting J. Musuuza et al.
18. Construction of a daily streamflow dataset for Peru using a similarity-based regionalization approach and a hybrid hydrological modeling framework H. Llauca et al.
19. Towards robust seasonal streamflow forecasts in mountainous catchments: impact of calibration metric selection in hydrological modeling D. Araya et al.
20. A co-generation success story: Improving drinking water management through hydro-climate services C. Cantone et al.
21. Spatiotemporal deep learning rainfall-runoff forecasting combined with remote sensing precipitation products in large scale basins S. Zhu et al.
22. Predictability of daily streamflow for the great rivers of South America based on a simple metric I. Petry et al.
23. A post-processing machine learning framework for bias-correcting National Water Model outputs by accounting for dominant streamflow drivers S. Naser Neisary et al.
24. Leveraging ensemble meteorological forcing data to improve parameter estimation of hydrologic models H. Liu et al.
25. Hydrological drought forecasts using precipitation data depend on catchment properties and human activities S. Sutanto et al.
26. Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale G. Papacharalampous et al.
27. Characterization of Bias during Meteorological Drought Calculation in Time Series Out-of-Sample Validation K. Mammas & D. Lekkas
28. Hybrid approaches enhance hydrological model usability for local streamflow prediction Y. Du & I. Pechlivanidis
29. Development of an under-ice river discharge forecasting system in Delft-Flood Early Warning System (Delft-FEWS) for the Chaudière River based on a coupled hydrological-hydrodynamic modelling approach K. Usman et al.
30. Stochastic optimization of a mixed moving average process for controlling non-Markovian streamflow environments H. Yoshioka et al.
31. The suitability of a seasonal ensemble hybrid framework including data-driven approaches for hydrological forecasting S. Hauswirth et al.
32. Robustness of hydrometeorological extremes in surrogated seasonal forecasts K. Klehmet et al.
33. Quantifying multi-year hydrological memory with Catchment Forgetting Curves A. de Lavenne et al.
34. Hydrological regimes explain the seasonal predictability of streamflow extremes Y. Du et al.
35. A hybrid deep learning approach for streamflow prediction utilizing watershed memory and process-based modeling B. Yifru et al.