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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:

Machine learning for hydrologic sciences: An introductory overview
Tianfang Xu, Feng Liang
Wiley Interdisciplinary Reviews Water (2021) Vol. 8, Iss. 5
Closed Access | Times Cited: 152

Showing 1-25 of 152 citing articles:

The role of deep learning in urban water management: A critical review
Guangtao Fu, Yiwen Jin, Siao Sun, et al.
Water Research (2022) Vol. 223, pp. 118973-118973
Open Access | Times Cited: 221
Deep learning for water quality
Wei Zhi, Alison P. Appling, Heather E. Golden, et al.
Nature Water (2024) Vol. 2, Iss. 3, pp. 228-241
Closed Access | Times Cited: 69
Prioritizing environmental determinants of urban heat islands: A machine learning study for major cities in China
Haoran Hou, Qianqiu Longyang, Hongbo Su, et al.
International Journal of Applied Earth Observation and Geoinformation (2023) Vol. 122, pp. 103411-103411
Open Access | Times Cited: 50
Conceptualizing future groundwater models through a ternary framework of multisource data, human expertise, and machine intelligence
Chuanjun Zhan, Zhenxue Dai, Shangxian Yin, et al.
Water Research (2024) Vol. 257, pp. 121679-121679
Closed Access | Times Cited: 35
Incorporating multiple grid-based data in CNN-LSTM hybrid model for daily runoff prediction in the source region of the Yellow River Basin
Feichi Hu, Qinli Yang, Junran Yang, et al.
Journal of Hydrology Regional Studies (2024) Vol. 51, pp. 101652-101652
Open Access | Times Cited: 28
A critical review of machine learning algorithms in maritime, offshore, and oil & gas corrosion research: A comprehensive analysis of ANN and RF models
Md Mahadi Hasan Imran, Shahrizan Jamaludin, Ahmad Faisal Mohamad Ayob
Ocean Engineering (2024) Vol. 295, pp. 116796-116796
Closed Access | Times Cited: 24
Distributed Hydrological Modeling With Physics‐Encoded Deep Learning: A General Framework and Its Application in the Amazon
Chao Wang, Shijie Jiang, Yi Zheng, et al.
Water Resources Research (2024) Vol. 60, Iss. 4
Open Access | Times Cited: 20
Use of one-dimensional CNN for input data size reduction in LSTM for improved computational efficiency and accuracy in hourly rainfall-runoff modeling
Kei Ishida, Ali Ercan, Takeyoshi Nagasato, et al.
Journal of Environmental Management (2024) Vol. 359, pp. 120931-120931
Closed Access | Times Cited: 18
Enhancing Water Level Prediction Using Ensemble Machine Learning Models: A Comparative Analysis
Saleh Alsulamy, Vijendra Kumar, Özgür Kişi, et al.
Water Resources Management (2025)
Closed Access | Times Cited: 4
Integrating machine learning with process-based glacio-hydrological model for improving the performance of runoff simulation in cold regions
Babak Mohammadi, Hongkai Gao, Petter Pilesjö, et al.
Journal of Hydrology (2025), pp. 132963-132963
Open Access | Times Cited: 2
A novel ensemble-based conceptual-data-driven approach for improved streamflow simulations
Anna E. Sikorska‐Senoner, John Quilty
Environmental Modelling & Software (2021) Vol. 143, pp. 105094-105094
Open Access | Times Cited: 66
Can machine learning accelerate process understanding and decision‐relevant predictions of river water quality?
Charuleka Varadharajan, Alison P. Appling, Bhavna Arora, et al.
Hydrological Processes (2022) Vol. 36, Iss. 4
Open Access | Times Cited: 54
Deep insight into daily runoff forecasting based on a CNN-LSTM model
Huiqi Deng, Wenjie Chen, Guoru Huang
Natural Hazards (2022) Vol. 113, Iss. 3, pp. 1675-1696
Closed Access | Times Cited: 48
Revolutionizing Groundwater Management with Hybrid AI Models: A Practical Review
Mojtaba Zaresefat, Reza Derakhshani
Water (2023) Vol. 15, Iss. 9, pp. 1750-1750
Open Access | Times Cited: 34
Forecasting of stage-discharge in a non-perennial river using machine learning with gamma test
Dinesh Kumar Vishwakarma, Alban Kuriqi, Salwan Ali Abed, et al.
Heliyon (2023) Vol. 9, Iss. 5, pp. e16290-e16290
Open Access | Times Cited: 31
Recent advancements of landslide hydrology
Roberto Greco, Pasquale Marino, Thom Bogaard
Wiley Interdisciplinary Reviews Water (2023) Vol. 10, Iss. 6
Open Access | Times Cited: 30
A New Benchmark on Machine Learning Methodologies for Hydrological Processes Modelling: A Comprehensive Review for Limitations and Future Research Directions
Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬
Knowledge-Based Engineering and Sciences (2023) Vol. 4, Iss. 3, pp. 65-103
Open Access | Times Cited: 25
Application of machine learning and emerging remote sensing techniques in hydrology: A state-of-the-art review and current research trends
Asish Saha, Subodh Chandra Pal
Journal of Hydrology (2024) Vol. 632, pp. 130907-130907
Closed Access | Times Cited: 16
Toward interpretable LSTM-based modeling of hydrological systems
Luis De La Fuente, Mohammad Reza Ehsani, Hoshin V. Gupta, et al.
Hydrology and earth system sciences (2024) Vol. 28, Iss. 4, pp. 945-971
Open Access | Times Cited: 14
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: 11
Cryosphere–groundwater connectivity is a missing link in the mountain water cycle
Marit Van Tiel, Caroline Aubry‐Wake, Lauren Somers, et al.
Nature Water (2024) Vol. 2, Iss. 7, pp. 624-637
Closed Access | Times Cited: 11
SnO2-Co3O4 Nanocomposite Sensor: Achieving Ultra-Selective Hydrogen Detection in Mixed Gas Environments
Yuxiang Qin, Yizhe Zhang, Peilun Qiu, et al.
Sensors and Actuators B Chemical (2024) Vol. 422, pp. 136521-136521
Closed Access | Times Cited: 10
River discharge prediction based multivariate climatological variables using hybridized long short-term memory with nature inspired algorithm
Sandeep Samantaray, Abinash Sahoo, Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, et al.
Journal of Hydrology (2024), pp. 132453-132453
Closed Access | Times Cited: 9
HydroEcoLSTM: A Python package with graphical user interface for hydro-ecological modeling with long short-term memory neural network
Van Tam Nguyen, Vinh Ngoc Tran, Hoang Tran, et al.
Ecological Informatics (2025) Vol. 85, pp. 102994-102994
Open Access | Times Cited: 1
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 | Times Cited: 1
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