50 citations as recorded by crossref.

1. The Implementation of Multimodal Large Language Models for Hydrological Applications: A Comparative Study of GPT-4 Vision, Gemini, LLaVa, and Multimodal-GPT L. Kadiyala et al. 10.3390/hydrology11090148
2. Superior performance of hybrid model in ungauged basins for real-time hourly water level forecasting – A case study on the Lancang-Mekong mainstream Z. Dong et al. 10.1016/j.jhydrol.2024.130941
3. Global hydrological reanalyses: The value of river discharge information for world‐wide downstream applications – The example of the Global Flood Awareness System GloFAS C. Prudhomme et al. 10.1002/met.2192
4. Water Resources’ AI–ML Data Uncertainty Risk and Mitigation Using Data Assimilation N. Martin & J. White 10.3390/w16192758
5. Research on machine learning hybrid framework by coupling grid-based runoff generation model and runoff process vectorization for flood forecasting C. Liu et al. 10.1016/j.jenvman.2024.121466
6. Artificial intelligence for climate prediction of extremes: State of the art, challenges, and future perspectives S. Materia et al. 10.1002/wcc.914
7. Enhancing Deep Learning Soil Moisture Forecasting Models by Integrating Physics-based Models L. Li et al. 10.1007/s00376-023-3181-8
8. Control of climate and physiography on runoff response behavior through use of catchment classification and machine learning S. Du et al. 10.1016/j.scitotenv.2023.166422
9. In-depth simulation of rainfall–runoff relationships using machine learning methods M. Fuladipanah et al. 10.2166/wpt.2024.147
10. Hydrological model parameter regionalization: Runoff estimation using machine learning techniques in the Tha Chin River Basin, Thailand P. Hlaing et al. 10.1016/j.mex.2024.102792
11. FROSTBYTE: a reproducible data-driven workflow for probabilistic seasonal streamflow forecasting in snow-fed river basins across North America L. Arnal et al. 10.5194/hess-28-4127-2024
12. Enhancing the capabilities of the Chao Phraya forecasting system through the integration of pre-processed numerical weather forecasts T. Charoensuk et al. 10.1016/j.ejrh.2024.101737
13. Investigating Intelligent Forecasting and Optimization in Electrical Power Systems: A Comprehensive Review of Techniques and Applications S. Sharifhosseini et al. 10.3390/en17215385
14. Combining Synthetic and Observed Data to Enhance Machine Learning Model Performance for Streamflow Prediction S. López-Chacón et al. 10.3390/w15112020
15. Optimal Postprocessing Strategies With LSTM for Global Streamflow Prediction in Ungauged Basins S. Tang et al. 10.1029/2022WR034352
16. Analyzing the Relationship between Agricultural AI Adoption and Government-Subsidized Insurance C. Osorio et al. 10.3390/agriculture14101804
17. A national-scale hybrid model for enhanced streamflow estimation – consolidating a physically based hydrological model with long short-term memory (LSTM) networks J. Liu et al. 10.5194/hess-28-2871-2024
18. Coupling SWAT and LSTM for Improving Daily Streamflow Simulation in a Humid and Semi-humid River Basin Z. Mei et al. 10.1007/s11269-024-03975-w
19. A review of hybrid deep learning applications for streamflow forecasting K. Ng et al. 10.1016/j.jhydrol.2023.130141
20. Forecasting bathing water quality in the UK: A critical review K. Krupska et al. 10.1002/wat2.1718
21. Consecutive one-week model predictions of land surface temperature stay on track for a decade with chaotic behavior tracking J. Ren et al. 10.1038/s43247-024-01801-0
22. Soil Dynamics and Crop Yield Modeling Using the MONICA Crop Simulation Model and Time Series Forecasting Methods I. Mirpulatov et al. 10.3390/agronomy13082185
23. A statistical–dynamical approach for probabilistic prediction of sub-seasonal precipitation anomalies over 17 hydroclimatic regions in China Y. Li et al. 10.5194/hess-27-4187-2023
24. Enhanced rainfall nowcasting of tropical cyclone by an interpretable deep learning model and its application in real-time flood forecasting L. Liu et al. 10.1016/j.jhydrol.2024.131993
25. Towards robust seasonal streamflow forecasts in mountainous catchments: impact of calibration metric selection in hydrological modeling D. Araya et al. 10.5194/hess-27-4385-2023
26. A causal physics-informed deep learning formulation for groundwater flow modeling and climate change effect analysis A. Adombi et al. 10.1016/j.jhydrol.2024.131370
27. Advancing Hydrology through Machine Learning: Insights, Challenges, and Future Directions Using the CAMELS, Caravan, GRDC, CHIRPS, PERSIANN, NLDAS, GLDAS, and GRACE Datasets F. Hasan et al. 10.3390/w16131904
28. A Statistical Forecasting Model for Extremes of the Fire Behaviour Index in Australia R. Taylor et al. 10.3390/atmos15040470
29. A Novel mRMR-RFE-RF Method for Enhancing Medium- and Long-Term Hydrological Forecasting: A Case Study of the Danjiangkou Basin T. Tang et al. 10.1109/JSTARS.2024.3449441
30. Review article: Towards improved drought prediction in the Mediterranean region – modeling approaches and future directions B. Zellou et al. 10.5194/nhess-23-3543-2023
31. Synthetic Forecast Ensembles for Evaluating Forecast Informed Reservoir Operations Z. Brodeur et al. 10.1029/2023WR034898
32. Forecasting of wind farm power output based on dynamic loading of power transformer at the substation M. Hartmann et al. 10.1016/j.epsr.2024.110527
33. Editorial: Data-driven machine learning for advancing hydrological and hydraulic predictability D. Lu et al. 10.3389/frwa.2023.1215966
34. Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research directions H. Tao et al. 10.1016/j.engappai.2023.107559
35. Identification of influential weather parameters and seasonal drought prediction in Bangladesh using machine learning algorithm M. Al Mamun et al. 10.1038/s41598-023-51111-2
36. Enhancing long short-term memory (LSTM)-based streamflow prediction with a spatially distributed approach Q. Yu et al. 10.5194/hess-28-2107-2024
37. Internal structure modification of a simple monthly water balance model via incorporation of a machine learning-based nonlinear routing U. Okkan et al. 10.2166/hydro.2024.010
38. Evaluation of machine learning-dynamical hybrid method incorporating remote sensing data for in-season maize yield prediction under drought Y. Luo et al. 10.1007/s11119-024-10149-6
39. Investigating permafrost carbon dynamics in Alaska with artificial intelligence B. Gay et al. 10.1088/1748-9326/ad0607
40. Impacts of hot-dry conditions on hydropower production in Switzerland N. Otero et al. 10.1088/1748-9326/acd8d7
41. A comparison of seasonal rainfall forecasts over Central America using dynamic and hybrid approaches from Copernicus Climate Change Service seasonal forecasting system and the North American Multimodel Ensemble K. Kowal et al. 10.1002/joc.7969
42. Hybrid Deep Learning and S2S Model for Improved Sub-Seasonal Surface and Root-Zone Soil Moisture Forecasting L. Xu et al. 10.3390/rs15133410
43. Connecting hydrological modelling and forecasting from global to local scales: Perspectives from an international joint virtual workshop A. Dasgupta et al. 10.1111/jfr3.12880
44. Monthly Ocean Primary Productivity Forecasting by Joint Use of Seasonal Climate Prediction and Temporal Memory L. Xu et al. 10.3390/rs15051417
45. Soil Dynamics and Crop Yield Modeling Using the MONICA Crop Simulation Model and Time Series Forecasting Methods I. Mirpulatov et al. 10.3390/agronomy13082185
46. Skillful Decadal Flood Prediction S. Moulds et al. 10.1029/2022GL100650
47. Elevation-dependent warming of streams in mountainous regions: implications for temperature modeling and headwater climate refugia D. Isaak & C. Luce 10.1080/07011784.2023.2176788
48. A Statistical Forecasting Model for Extremes of the Fire Behaviour Index in Australia R. Taylor et al. 10.3390/atmos15040470
49. Energy Forecasting Model for Ground Movement Operation in Green Airport A. Ajayi et al. 10.3390/en16135008
50. Resilience of UK crop yields to compound climate change L. Slater et al. 10.5194/esd-13-1377-2022