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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:

Probing the limit of hydrologic predictability with the Transformer network
Jiangtao Liu, Yuchen Bian, Kathryn Lawson, et al.
Journal of Hydrology (2024) Vol. 637, pp. 131389-131389
Open Access | Times Cited: 12

Showing 12 citing articles:

Long-term streamflow forecasting in data-scarce regions: Insightful investigation for leveraging satellite-derived data, Informer architecture, and concurrent fine-tuning transfer learning
Fatemeh Ghobadi, Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Doosun Kang
Journal of Hydrology (2024) Vol. 631, pp. 130772-130772
Closed Access | Times Cited: 12
Are Deep Learning Models in Hydrology Entity Aware?
Benedikt Heudorfer, Hoshin V. Gupta, Ralf Loritz
Geophysical Research Letters (2025) Vol. 52, Iss. 6
Open Access
Time series predictions in unmonitored sites: a survey of machine learning techniques in water resources
Jared Willard, Charuleka Varadharajan, Xiaowei Jia, et al.
Environmental Data Science (2025) Vol. 4
Open Access
Fine-tuning long short-term memory models for seamless transition in hydrological modelling: From pre-training to post-application
Xueying Chen, Yuhang Zhang, Aizhong Ye, et al.
Environmental Modelling & Software (2025), pp. 106350-106350
Open Access
Enhancing Hydro-climatic and land parameter forecasting using Transformer networks
Suchismita Subhadarsini, D. Nagesh Kumar, Rao S. Govindaraju
Journal of Hydrology (2025), pp. 132906-132906
Closed Access
Research on multi-objective optimization of bioreactor cupped impeller CFD based on improved proxy model
Quan Shi, Xiaoliang Xu, Huafeng Deng, et al.
Thermal Science and Engineering Progress (2025), pp. 103508-103508
Closed Access
Hyperparameter optimization of regional hydrological LSTMs by random search: A case study from Basque Country, Spain
Fateme Hosseini, Cristina Prieto, César Álvarez
Journal of Hydrology (2024), pp. 132003-132003
Open Access | Times Cited: 3
Deep dive into hydrologic simulations at global scale: harnessing the power of deep learning and physics-informed differentiable models (δHBV-globe1.0-hydroDL)
Dapeng Feng, Hylke E. Beck, Jens de Bruijn, et al.
Geoscientific model development (2024) Vol. 17, Iss. 18, pp. 7181-7198
Open Access | Times Cited: 3
Comparison of transformer, LSTM and coupled algorithms for soil moisture prediction in shallow-groundwater-level areas with interpretability analysis
Yue Wang, Yuanyuan Zha
Agricultural Water Management (2024) Vol. 305, pp. 109120-109120
Open Access | Times Cited: 2
Ensemble learning of catchment-wise optimized LSTMs enhances regional rainfall-runoff modelling − case Study: Basque Country, Spain
Farzad Hosseini Hossein Abadi, Cristina Prieto, César Álvarez
Journal of Hydrology (2024), pp. 132269-132269
Open Access | Times Cited: 1
Hydrograph and recession flows simulations using deep learning: Watershed uniqueness and objective functions
Abhinav Gupta, Sean Andrew McKenna
Journal of Hydrology X (2024), pp. 100198-100198
Open Access | Times Cited: 1
A differentiable, physics-based hydrological model and its evaluation for data-limited basins
Wenyu Ouyang, Lei Ye, Yikai CHAI, et al.
Journal of Hydrology (2024), pp. 132471-132471
Closed Access
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