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:

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: 7

Showing 7 citing articles:

Machine Learning for a Heterogeneous Water Modeling Framework
Jonathan Frame, Ryoko Araki, Soelem Aafnan Bhuiyan, et al.
JAWRA Journal of the American Water Resources Association (2025) Vol. 61, Iss. 1
Open Access | Times Cited: 1

Physics-encoded deep learning for integrated modeling of watershed hydrology and reservoir operations
Bofu Yu, Yi Zheng, Shaokun He, et al.
Journal of Hydrology (2025), pp. 133052-133052
Closed Access

Modelling and Optimisation of Hysteresis and Sensitivity of Multicomponent Flexible Sensing Materials
Kai Chen, Qiang Gao, Yijin Ouyang, et al.
Applied Sciences (2025) Vol. 15, Iss. 6, pp. 3271-3271
Open Access

Long Short-Term Memory (LSTM) Networks for Accurate River Flow Forecasting: A Case Study on the Morava River Basin (Serbia)
Igor Leščešen, Mitra Tanhapour, Pavla Pekárová, et al.
Water (2025) Vol. 17, Iss. 6, pp. 907-907
Open Access

A national-scale hybrid model for enhanced streamflow estimation – consolidating a physically based hydrological model with long short-term memory (LSTM) networks
Jun Liu, Julian Koch, Simon Stisen, et al.
Hydrology and earth system sciences (2024) Vol. 28, Iss. 13, pp. 2871-2893
Open Access | Times Cited: 4

Advancing streamflow prediction in data-scarce regions through vegetation-constrained distributed hybrid ecohydrological models
L. Zhong, Huimin Lei, Zhiyuan Li, et al.
Journal of Hydrology (2024) Vol. 645, pp. 132165-132165
Closed Access | Times Cited: 3

Incorporating hydrological constraints with deep learning for streamflow prediction
Yi Zhou, Yilin Duan, Hong Yao, et al.
Expert Systems with Applications (2024), pp. 125379-125379
Closed Access | Times Cited: 1

Modeling forest growth under climate change
Issam Boukhris, Gina Marano, Daniela Dalmonech, et al.
Authorea (Authorea) (2024)
Open Access

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