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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:

Multiscale groundwater level forecasting: Coupling new machine learning approaches with wavelet transforms
A. T. M. Sakiur Rahman, Takahiro Hosono, John Quilty, et al.
Advances in Water Resources (2020) Vol. 141, pp. 103595-103595
Closed Access | Times Cited: 154

Showing 1-25 of 154 citing articles:

Groundwater level prediction using machine learning models: A comprehensive review
Tao Hai, Mohammed Majeed Hameed, Haydar Abdulameer Marhoon, et al.
Neurocomputing (2022) Vol. 489, pp. 271-308
Open Access | Times Cited: 265
Predictive modeling of groundwater nitrate pollution and evaluating its main impact factors using random forest
Song He, Jianhua Wu, Dan Wang, et al.
Chemosphere (2021) Vol. 290, pp. 133388-133388
Closed Access | Times Cited: 178
Coupling a hybrid CNN-LSTM deep learning model with a Boundary Corrected Maximal Overlap Discrete Wavelet Transform for multiscale Lake water level forecasting
Rahim Barzegar, Mohammad Taghi Aalami, Jan Adamowski
Journal of Hydrology (2021) Vol. 598, pp. 126196-126196
Closed Access | Times Cited: 165
Groundwater level prediction using machine learning algorithms in a drought-prone area
Quoc Bao Pham, Manish Kumar, Fabio Di Nunno, et al.
Neural Computing and Applications (2022) Vol. 34, Iss. 13, pp. 10751-10773
Closed Access | Times Cited: 130
Deep learning in hydrology and water resources disciplines: concepts, methods, applications, and research directions
Kumar Puran Tripathy, Ashok K. Mishra
Journal of Hydrology (2023) Vol. 628, pp. 130458-130458
Closed Access | Times Cited: 101
Groundwater Level Modeling with Machine Learning: A Systematic Review and Meta-Analysis
Arman Ahmadi, Mohammad Ali Olyaei, Zahra Heydari, et al.
Water (2022) Vol. 14, Iss. 6, pp. 949-949
Open Access | Times Cited: 89
Interfacing finite elements with deep neural operators for fast multiscale modeling of mechanics problems
Minglang Yin, Enrui Zhang, Yue Yu, et al.
Computer Methods in Applied Mechanics and Engineering (2022) Vol. 402, pp. 115027-115027
Open Access | Times Cited: 75
Applications of machine learning to water resources management: A review of present status and future opportunities
Ashraf Ahmed, Sakina Sayed, Antoifi Abdoulhalik, et al.
Journal of Cleaner Production (2024) Vol. 441, pp. 140715-140715
Open Access | Times Cited: 63
A secondary modal decomposition ensemble deep learning model for groundwater level prediction using multi-data
Xuefei Cui, Zhaocai Wang, Nannan Xu, et al.
Environmental Modelling & Software (2024) Vol. 175, pp. 105969-105969
Closed Access | Times Cited: 23
Groundwater level prediction using an improved ELM model integrated with hybrid particle swarm optimisation and grey wolf optimisation
Sandeep Samantaray, Abinash Sahoo
Groundwater for Sustainable Development (2024) Vol. 26, pp. 101178-101178
Closed Access | Times Cited: 22
Research on Water Resource Modeling Based on Machine Learning Technologies
Liu Ze, Jingzhao Zhou, Xiaoyang Yang, et al.
Water (2024) Vol. 16, Iss. 3, pp. 472-472
Open Access | Times Cited: 21
Enhancing the accuracy of groundwater level prediction at different scales using spatio-temporal graph convolutional model
Long Chen, Dezheng Zhang, Jianwei Xu, et al.
Earth Science Informatics (2025) Vol. 18, Iss. 2
Closed Access | Times Cited: 2
Evaluating the predictive power of different machine learning algorithms for groundwater salinity prediction of multi-layer coastal aquifers in the Mekong Delta, Vietnam
Dang An Tran, Maki Tsujimura, Nam Thang Ha, et al.
Ecological Indicators (2021) Vol. 127, pp. 107790-107790
Open Access | Times Cited: 96
Deep Learning Based Modeling of Groundwater Storage Change
Mohd Anul Haq, Abdul Khadar Jilani, P. Prabu
Computers, materials & continua/Computers, materials & continua (Print) (2021) Vol. 70, Iss. 3, pp. 4599-4617
Open Access | Times Cited: 95
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: 68
A Review on Interpretable and Explainable Artificial Intelligence in Hydroclimatic Applications
Hakan Başağaoğlu, Debaditya Chakraborty, Cesar Do Lago, et al.
Water (2022) Vol. 14, Iss. 8, pp. 1230-1230
Open Access | Times Cited: 60
Mathematical and Machine Learning Models for Groundwater Level Changes: A Systematic Review and Bibliographic Analysis
Stephen Afrifa, Tao Zhang, Peter Appiahene, et al.
Future Internet (2022) Vol. 14, Iss. 9, pp. 259-259
Open Access | Times Cited: 52
Modelling groundwater level fluctuations by ELM merged advanced metaheuristic algorithms using hydroclimatic data
Rana Muhammad Adnan, Hongliang Dai, Reham R. Mostafa, et al.
Geocarto International (2022) Vol. 38, Iss. 1
Open Access | Times Cited: 49
Groundwater Potential Mapping in Hubei Region of China Using Machine Learning, Ensemble Learning, Deep Learning and AutoML Methods
Zhigang Bai, Qimeng Liu, Yu Liu
Natural Resources Research (2022) Vol. 31, Iss. 5, pp. 2549-2569
Closed Access | Times Cited: 43
Prediction of soil salinity parameters using machine learning models in an arid region of northwest China
Chao Xiao, Qingyuan Ji, Junqing Chen, et al.
Computers and Electronics in Agriculture (2022) Vol. 204, pp. 107512-107512
Closed Access | Times Cited: 42
Development of wavelet-based Kalman Online Sequential Extreme Learning Machine optimized with Boruta-Random Forest for drought index forecasting
Mehdi Jamei, Iman Ahmadianfar, Masoud Karbasi, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 117, pp. 105545-105545
Closed Access | Times Cited: 40
Combination of discretization regression with data-driven algorithms for modeling irrigation water quality indices
Dimple Dimple, Pradeep Kumar Singh, Jitendra Rajput, et al.
Ecological Informatics (2023) Vol. 75, pp. 102093-102093
Closed Access | Times Cited: 34
An explainable multiscale LSTM model with wavelet transform and layer-wise relevance propagation for daily streamflow forecasting
Lizhi Tao, Zhichao Cui, Yufeng He, et al.
The Science of The Total Environment (2024) Vol. 929, pp. 172465-172465
Closed Access | Times Cited: 13
Groundwater Level Forecasting Using Machine Learning: A Case Study of the Baekje Weir in Four Major Rivers Project, South Korea
Sooyeon Yi, G. Mathias Kondolf, Samuel Sandoval‐Solis, et al.
Water Resources Research (2024) Vol. 60, Iss. 5
Open Access | Times Cited: 13
A hybrid framework based on LSTM for predicting karst spring discharge using historical data
Wenrui Zhang, Limin Duan, Tingxi Liu, et al.
Journal of Hydrology (2024) Vol. 633, pp. 130946-130946
Closed Access | Times Cited: 12
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