104 citations as recorded by crossref.

1. Water Resources’ AI–ML Data Uncertainty Risk and Mitigation Using Data Assimilation N. Martin & J. White 10.3390/w16192758
2. Forecasting monthly rainfall and temperature patterns in Van Province, Türkiye, using ARIMA and SARIMA models: a long-term climate analysis V. Yavuz 10.2166/wcc.2025.798
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4. In-depth simulation of rainfall–runoff relationships using machine learning methods M. Fuladipanah et al. 10.2166/wpt.2024.147
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8. 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
9. Leveraging hybrid deep learning architectures for predicting monthly precipitation in Victoria, Australia E. Abdi et al. 10.1007/s40808-025-02514-9
10. A review of hybrid deep learning applications for streamflow forecasting K. Ng et al. 10.1016/j.jhydrol.2023.130141
11. Forecasting bathing water quality in the UK: A critical review K. Krupska et al. 10.1002/wat2.1718
12. 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
13. Ensemble Streamflow Simulations in a Qinghai–Tibet Plateau Basin Using a Deep Learning Method with Remote Sensing Precipitation Data as Input J. Wang et al. 10.3390/rs17060967
14. Advancing Subseasonal Extreme Rainfall Forecasting in Vietnam Using Machine Learning T. Cong et al. 10.2151/sola.2025-034
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16. Synthetic Forecast Ensembles for Evaluating Forecast Informed Reservoir Operations Z. Brodeur et al. 10.1029/2023WR034898
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18. 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
19. Hourly streamflow forecasting across diverse climate zones on Oʻahu Island, Hawaiʻi P. Parisouj et al. 10.1016/j.jhydrol.2025.134225
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24. Hybrid random forest– artificial neural network model based forecasting of anthracnose in bottle gourd across different transplanting windows A. Chittaragi et al. 10.1016/j.atech.2025.101477
25. 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
26. 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
27. 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
28. Seasonal forecasts have sufficient skill to inform some agricultural decisions A. Kondal et al. 10.1088/1748-9326/ad8bde
29. Optimal Postprocessing Strategies With LSTM for Global Streamflow Prediction in Ungauged Basins S. Tang et al. 10.1029/2022WR034352
30. A hybrid deep learning framework for improving short-term precipitation forecasts S. Salehi & S. Akbar Salehi Neyshabouri 10.1016/j.envsoft.2025.106635
31. Tropical Cyclones Across Global Basins: Dynamics, Tracking Algorithms, Forecasting, and Emerging Scientometric Research Trends V. Singh et al. 10.1002/met.70067
32. An extension of WeatherBench 2 to binary hydroclimatic forecasts T. Zhao et al. 10.5194/gmd-18-5781-2025
33. Climate-induced changes in streamflow and nitrogen loading to Long Island Sound M. Duvall & J. Hagy 10.1016/j.scitotenv.2025.179957
34. 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
35. A Hybrid Approach to Physical and Deep Learning Models for Radar-Based Precipitation Nowcasting H. Kim et al. 10.1109/TGRS.2025.3560454
36. A Mamba-Based Hierarchical Partitioning Framework for Upper-Level Wind Field Reconstruction W. Chen et al. 10.3390/aerospace12090842
37. 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
38. Holistic uncertainty quantification and attribution for real-time seasonal streamflow predictions: Insights from input, parameter and initial condition L. Liu et al. 10.1016/j.ejrh.2025.102427
39. How suitable are copula models for post-processing global precipitation forecasts? Z. Huang & T. Zhao 10.1016/j.jhydrol.2025.133005
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41. Predicting precipitation using dynamic distributed lag models in arid and sub-humid regions of South Africa L. Chaka et al. 10.1016/j.sciaf.2025.e02924
42. 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
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44. Runoff simulation based on granular computing by introducing terrain factors to construct climate characteristic index Y. Zhao et al. 10.1016/j.jhydrol.2025.133614
45. 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
46. Prognosticators for precipitation variability adopting principal component regression analysis E. Aamir & A. Ghumman 10.1007/s12517-024-12111-2
47. Advances in land surface forecasting: a comparison of LSTM, gradient boosting, and feed-forward neural networks as prognostic state emulators in a case study with ecLand M. Wesselkamp et al. 10.5194/gmd-18-921-2025
48. Enhancing seasonal fire predictions with hybrid dynamical and random forest models M. Torres-Vázquez et al. 10.1038/s44304-025-00069-4
49. Artificial Intelligence in Hydrology: Advancements in Soil, Water Resource Management, and Sustainable Development S. Biazar et al. 10.3390/su17052250
50. Comparison between Two-Level Machine Learning and Deep Learning for Groundwater Potential Mapping in the Rmel Aquifer (Northwestern Morocco) M. Chahid et al. 10.1007/s41748-025-00857-y
51. 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
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53. 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
54. Artificial intelligence for climate prediction of extremes: State of the art, challenges, and future perspectives S. Materia et al. 10.1002/wcc.914
55. A hybrid statistical-dynamical forecast of seasonal streamflow for a catchment in the Upper Columbia River basin in Canada T. Swift-LaPointe et al. 10.3389/frwa.2025.1595898
56. Enhancing Deep Learning Soil Moisture Forecasting Models by Integrating Physics-based Models L. Li et al. 10.1007/s00376-023-3181-8
57. Artificial intelligence in environmental remote sensing: Progress, way forward and key considerations C. Maniyar et al. 10.1177/27539687251357020
58. Hybrid modeling of first-principles and machine learning: A step-by-step tutorial review for practical implementation P. Shah et al. 10.1016/j.compchemeng.2024.108926
59. Investigating Intelligent Forecasting and Optimization in Electrical Power Systems: A Comprehensive Review of Techniques and Applications S. Sharifhosseini et al. 10.3390/en17215385
60. Analyzing the Relationship between Agricultural AI Adoption and Government-Subsidized Insurance C. Osorio et al. 10.3390/agriculture14101804
61. Fusion of data-driven models with a knowledge-guided loss function for flood forecasting H. Malik et al. 10.1016/j.asoc.2025.113742
62. 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
63. Skill-informed seamless communication of European S2S hydrological forecasts I. Pechlivanidis & L. Crochemore 10.1088/1748-9326/ade0d7
64. Physics-aware machine learning revolutionizes scientific paradigm for process-based modeling in hydrology Q. Xu et al. 10.1016/j.earscirev.2025.105276
65. Skilful probabilistic predictions of UK flood risk months ahead using a large-sample machine learning model trained on multimodel ensemble climate forecasts S. Moulds et al. 10.5194/hess-29-2393-2025
66. 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
67. 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
68. Thermal Load Predictions in Low-Energy Buildings: A Hybrid AI-Based Approach Integrating Integral Feature Selection and Machine Learning Models Y. El Mghouchi & M. Udristioiu 10.3390/app15116348
69. Challenges and opportunities of ML and explainable AI in large-sample hydrology L. Slater et al. 10.1098/rsta.2024.0287
70. Integrating AI in plant science: A review of applications and future prospects I. Khan & B. Khare 10.1016/j.plgene.2025.100542
71. 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
72. Future climate prediction and projection: A systematic review of classical and advanced methodologies R. Sepaspour et al. 10.1007/s00704-025-05795-3
73. 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
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75. Protocols for Water and Environmental Modeling Using Machine Learning in California M. He et al. 10.3390/hydrology12030059
76. Rainy season precipitation trends over motloutse watershed in semi-arid eastern Botswana (1989–2019): implications on groundwater resources and sustainability G. Lentswe & L. Molwalefhe 10.1080/10106049.2025.2545911
77. Прогнозне моделювання процесів формування паводкових стоків з використанням геоінформаційних технологій О. Кравець 10.36930/40350313
78. A Weighted Likelihood Ensemble Approach for Failure Prediction of Water Pipes R. Beig Zali et al. 10.1061/JWRMD5.WRENG-6655
79. Analyzing the generalization capabilities of a hybrid hydrological model for extrapolation to extreme events E. Acuña Espinoza et al. 10.5194/hess-29-1277-2025
80. 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
81. Soil Dynamics and Crop Yield Modeling Using the MONICA Crop Simulation Model and Time Series Forecasting Methods I. Mirpulatov et al. 10.3390/agronomy13082185
82. A pioneering approach to deterministic rainfall forecasting for wet period in the Northern Territory of Australia using machine learning R. Farooq et al. 10.1007/s12145-025-01724-0
83. Hybrid approaches enhance hydrological model usability for local streamflow prediction Y. Du & I. Pechlivanidis 10.1038/s43247-025-02324-y
84. Analysis of time series characteristics using machine learning model and correlation matrix in the tasks of forecasting the state of forest ecosystems P. Gusev et al. 10.1051/bioconf/202414504019
85. A Statistical Forecasting Model for Extremes of the Fire Behaviour Index in Australia R. Taylor et al. 10.3390/atmos15040470
86. 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
87. Soft computing paradigm for climate change adaptation and mitigation in Iran, Pakistan, and Turkey: A systematic review M. Talha et al. 10.1016/j.heliyon.2025.e41974
88. CrackNet: A transformer-based approach for detecting microcrack in photovoltaic panels based on electroluminescence images H. Gao et al. 10.1016/j.renene.2025.124549
89. Temperature-based solar energy forecasting: a big data analysis for sustainable energy planning in Ishwardi and Rajshahi region of Bangladesh H. Alif 10.1007/s00704-025-05746-y
90. Enhancing long short-term memory (LSTM)-based streamflow prediction with a spatially distributed approach Q. Yu et al. 10.5194/hess-28-2107-2024
91. Investigating permafrost carbon dynamics in Alaska with artificial intelligence B. Gay et al. 10.1088/1748-9326/ad0607
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93. 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
94. Hybrid Deep Learning and S2S Model for Improved Sub-Seasonal Surface and Root-Zone Soil Moisture Forecasting L. Xu et al. 10.3390/rs15133410
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98. Soil Dynamics and Crop Yield Modeling Using the MONICA Crop Simulation Model and Time Series Forecasting Methods I. Mirpulatov et al. 10.3390/agronomy13082185
99. Skillful Decadal Flood Prediction S. Moulds et al. 10.1029/2022GL100650
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104. Resilience of UK crop yields to compound climate change L. Slater et al. 10.5194/esd-13-1377-2022