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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Hybrid forecasting: blending climate predictions with AI models
Louise Slater, Louise Arnal, Marie‐Amélie Boucher, et al.
Hydrology and earth system sciences (2023) Vol. 27, Iss. 9, pp. 1865-1889
Open Access | Times Cited: 84

Showing 1-25 of 84 citing articles:

A review of hybrid deep learning applications for streamflow forecasting
Kin‐Wang Ng, Yuk Feng Huang, Chai Hoon Koo, et al.
Journal of Hydrology (2023) Vol. 625, pp. 130141-130141
Closed Access | Times Cited: 72
Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research directions
Tao Hai, Sani I. Abba, Ahmed M. Al‐Areeq, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 129, pp. 107559-107559
Closed Access | Times Cited: 56
Identification of influential weather parameters and seasonal drought prediction in Bangladesh using machine learning algorithm
Md. Abdullah Al Mamun, Mou Rani Sarker, Md. Abdur Rouf Sarkar, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 16
Optimal Postprocessing Strategies With LSTM for Global Streamflow Prediction in Ungauged Basins
Senlin Tang, Fubao Sun, Wenbin Liu, et al.
Water Resources Research (2023) Vol. 59, Iss. 7
Closed Access | Times Cited: 32
Artificial intelligence for climate prediction of extremes: State of the art, challenges, and future perspectives
Stefano Materia, Lluís Palma García, Chiem van Straaten, et al.
Wiley Interdisciplinary Reviews Climate Change (2024)
Open Access | Times Cited: 12
In-depth simulation of rainfall–runoff relationships using machine learning methods
Mehdi Fuladipanah, Alireza Shahhosseini, Namal Rathnayake, et al.
Water Practice & Technology (2024) Vol. 19, Iss. 6, pp. 2442-2459
Open Access | Times Cited: 10
Global hydrological reanalyses: The value of river discharge information for world‐wide downstream applications – The example of the Global Flood Awareness System GloFAS
Christel Prudhomme, Ervin Zsótér, Gwyneth Matthews, et al.
Meteorological Applications (2024) Vol. 31, Iss. 2
Open Access | Times Cited: 7
Advancing Hydrology through Machine Learning: Insights, Challenges, and Future Directions Using the CAMELS, Caravan, GRDC, CHIRPS, PERSIANN, NLDAS, GLDAS, and GRACE Datasets
F. M. Hasan, Paul Medley, Jason Drake, et al.
Water (2024) Vol. 16, Iss. 13, pp. 1904-1904
Open Access | Times Cited: 7
Combining Synthetic and Observed Data to Enhance Machine Learning Model Performance for Streamflow Prediction
Sergio Ricardo López-Chacón, Fernando Salazar, Ernest Bladé
Water (2023) Vol. 15, Iss. 11, pp. 2020-2020
Open Access | Times Cited: 18
Enhancing Deep Learning Soil Moisture Forecasting Models by Integrating Physics-based Models
Lu Li, Yongjiu Dai, Zhongwang Wei, et al.
Advances in Atmospheric Sciences (2024) Vol. 41, Iss. 7, pp. 1326-1341
Closed Access | Times Cited: 6
Superior performance of hybrid model in ungauged basins for real-time hourly water level forecasting – A case study on the Lancang-Mekong mainstream
Zhiqiang Dong, Hongchang Hu, Hui Liu, et al.
Journal of Hydrology (2024) Vol. 633, pp. 130941-130941
Closed Access | Times Cited: 6
Enhancing long short-term memory (LSTM)-based streamflow prediction with a spatially distributed approach
Qiutong Yu, Bryan A. Tolson, Hongren Shen, et al.
Hydrology and earth system sciences (2024) Vol. 28, Iss. 9, pp. 2107-2122
Open Access | Times Cited: 6
Machine learning in financial forecasting: A U.S. review: Exploring the advancements, challenges, and implications of AI-driven predictions in financial markets
Odeyemi Olubusola, Noluthando Zamanjomane Mhlongo, Donald Obinna Daraojimba, et al.
World Journal of Advanced Research and Reviews (2024) Vol. 21, Iss. 2, pp. 1969-1984
Open Access | Times Cited: 5
Research on machine learning hybrid framework by coupling grid-based runoff generation model and runoff process vectorization for flood forecasting
Chengshuai Liu, Tianning Xie, Wenzhong Li, et al.
Journal of Environmental Management (2024) Vol. 364, pp. 121466-121466
Closed Access | Times Cited: 5
Hybrid modeling of first-principles and machine learning: A step-by-step tutorial review for practical implementation
Parth Shah, Silabrata Pahari, Raj Bhavsar, et al.
Computers & Chemical Engineering (2024), pp. 108926-108926
Closed Access | Times Cited: 5
Soft Computing Paradigm for Climate Change Adaptation and Mitigation in Iran, Pakistan, and Turkey: A Systematic Review
Muhammad Talha, A. Pouyan Nejadhashemi, Kieron Moller
Heliyon (2025) Vol. 11, Iss. 2, pp. e41974-e41974
Open Access
A pioneering approach to deterministic rainfall forecasting for wet period in the Northern Territory of Australia using machine learning
Rashid Farooq, Monzur Alam Imteaz, Fatemeh Mekanik
Earth Science Informatics (2025) Vol. 18, Iss. 2
Open Access
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
Marieke Wesselkamp, Matthew Chantry, Ewan Pinnington, et al.
Geoscientific model development (2025) Vol. 18, Iss. 4, pp. 921-937
Open Access
Enhancing representation of data-scarce reservoir-regulated river basins using a hybrid DL-process based approach
Liangkun Deng, Xiang Zhang, Louise Slater
Journal of Hydrology (2025) Vol. 655, pp. 132895-132895
Closed Access
Enhancing seasonal fire predictions with hybrid dynamical and random forest models
Miguel Ángel Torres‐Vázquez, Sixto Herrera, Andrina Gincheva, et al.
npj natural hazards. (2025) Vol. 2, Iss. 1
Open Access
STAT-LSTM: A multivariate spatiotemporal feature aggregation model for SPEI-based drought prediction
Ying Chen, Huanping Wu, Nengfu Xie, et al.
Earth Science Informatics (2025) Vol. 18, Iss. 3
Open Access
Artificial Intelligence in Hydrology: Advancements in Soil, Water Resource Management, and Sustainable Development
Seyed Mostafa Biazar, Golmar Golmohammadi, Rohit R. Nedhunuri, et al.
Sustainability (2025) Vol. 17, Iss. 5, pp. 2250-2250
Open Access
How suitable are copula models for post-processing global precipitation forecasts?
Zeqing Huang, Tongtiegang Zhao
Journal of Hydrology (2025), pp. 133005-133005
Closed Access
Ensemble Streamflow Simulations in a Qinghai–Tibet Plateau Basin Using a Deep Learning Method with Remote Sensing Precipitation Data as Input
Jinqiang Wang, Zhanjie Li, Ling Zhou, et al.
Remote Sensing (2025) Vol. 17, Iss. 6, pp. 967-967
Open Access
Analyzing the generalization capabilities of a hybrid hydrological model for extrapolation to extreme events
Eduardo Acuña Espinoza, Ralf Loritz, Frederik Kratzert, et al.
Hydrology and earth system sciences (2025) Vol. 29, Iss. 5, pp. 1277-1294
Open Access
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