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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:

Optimized Conditioning Factors Using Machine Learning Techniques for Groundwater Potential Mapping
Bahareh Kalantar, Husam A. H. Al-Najjar, Biswajeet Pradhan, et al.
Water (2019) Vol. 11, Iss. 9, pp. 1909-1909
Open Access | Times Cited: 72

Showing 26-50 of 72 citing articles:

Mapping groundwater potentiality by using hybrid machine learning models under the scenario of climate variability: a national level study of Bangladesh
Showmitra Kumar Sarkar, Fahad Alshehri, Shahfahad, et al.
Environment Development and Sustainability (2024)
Closed Access | Times Cited: 6
Multi-criteria decision-making techniques for groundwater potentiality mapping in arid regions: A case study of Wadi Yiba, Kingdom of Saudi Arabia
Nuaman Ejaz, Aftab Haider Khan, Muhammad Waqar Saleem, et al.
Groundwater for Sustainable Development (2024) Vol. 26, pp. 101223-101223
Closed Access | Times Cited: 6
Machine-Learning-Based Classification Approaches toward Recognizing Slope Stability Failure
Hossein Moayedi, Dieu Tien Bui, Bahareh Kalantar, et al.
Applied Sciences (2019) Vol. 9, Iss. 21, pp. 4638-4638
Open Access | Times Cited: 41
Assessing, mapping, and optimizing the locations of sediment control check dams construction
Hamid Reza Pourghasemi, Saleh Yousefi, Nitheshnirmal Sãdhasivam, et al.
The Science of The Total Environment (2020) Vol. 739, pp. 139954-139954
Closed Access | Times Cited: 35
A comparative study on machine learning modeling for mass movement susceptibility mapping (a case study of Iran)
Sayed Naeim Emami, Saleh Yousefi, Hamid Reza Pourghasemi, et al.
Bulletin of Engineering Geology and the Environment (2020) Vol. 79, Iss. 10, pp. 5291-5308
Closed Access | Times Cited: 35
A comparative assessment of modeling groundwater vulnerability using DRASTIC method from GIS and a novel classification method using machine learning classifiers
Qasim Khan, Muhammad Usman Liaqat, Mohamed Mostafa Mohamed
Geocarto International (2021) Vol. 37, Iss. 20, pp. 5832-5850
Closed Access | Times Cited: 30
Integrating a GIS-Based Multi-Influence Factors Model with Hydro-Geophysical Exploration for Groundwater Potential and Hydrogeological Assessment: A Case Study in the Karak Watershed, Northern Pakistan
Umair Khan, Haris Faheem, Zhengwen Jiang, et al.
Water (2021) Vol. 13, Iss. 9, pp. 1255-1255
Open Access | Times Cited: 29
Assessment of groundwater potential in terms of the availability and quality of the resource: a case study from Iraq
Alaa M. Al-Abadi, Alan E. Fryar, Arjan A. Rasheed, et al.
Environmental Earth Sciences (2021) Vol. 80, Iss. 12
Closed Access | Times Cited: 28
Solving water scarcity challenges in arid regions: A novel approach employing human-based meta-heuristics and machine learning algorithm for groundwater potential mapping
Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi‐Niaraki, Farbod Farhangi, et al.
Chemosphere (2024) Vol. 363, pp. 142859-142859
Open Access | Times Cited: 4
Review: Theory-guided machine learning applied to hydrogeology—state of the art, opportunities and future challenges
Adoubi Vincent De Paul Adombi, Romain Chesnaux, Marie‐Amélie Boucher
Hydrogeology Journal (2021) Vol. 29, Iss. 8, pp. 2671-2683
Open Access | Times Cited: 27
Spatial assessment of groundwater potential using Quantum GIS and multi-criteria decision analysis (QGIS-AHP) in the Sawla-Tuna-Kalba district of Ghana
Prosper Kpiebaya, Ebenezer Ebo Yahans Amuah, Shaibu Abdul-Ganiyu, et al.
Journal of Hydrology Regional Studies (2022) Vol. 43, pp. 101197-101197
Open Access | Times Cited: 18
Identification of groundwater potential zones in data-scarce mountainous region using explainable machine learning
Kshitij Dahal, Sandesh Sharma, Amin Shakya, et al.
Journal of Hydrology (2023) Vol. 627, pp. 130417-130417
Closed Access | Times Cited: 10
Comparison Between Machine Learning and Bivariate Statistical Models for Groundwater Recharge Zones
Bilal Aslam, Ahsen Maqsoom, Usman Hassan, et al.
Iranian Journal of Science and Technology Transactions of Civil Engineering (2025)
Closed Access
The use of radar-optical remote sensing data and geographic information system–analytical hierarchy process–multicriteria decision analysis techniques for revealing groundwater recharge prospective zones in arid-semi arid lands
Yuxia Wang, Yuhui Han, Yue Guo, et al.
Open Geosciences (2025) Vol. 17, Iss. 1
Open Access
Comparative Evaluation of Multi-Influence Factor, Shannon Entropy, and Frequency Ratio Techniques for Groundwater Potential Mapping in the Maze and Zenti Catchments, Omo Basin, Ethiopia
Yonas Oyda, Samuel Dagalo Hatiye, Muralitharan Jothimani
Heliyon (2025) Vol. 11, Iss. 4, pp. e42473-e42473
Open Access
Positive–Unlabeled Learning-Based Hybrid Models and Interpretability for Groundwater Potential Mapping in Karst Areas
Benteng Bi, Jingwen Li, Tianyu Luo, et al.
Water (2025) Vol. 17, Iss. 10, pp. 1422-1422
Open Access
The Predictive Capability of a Novel Ensemble Tree-Based Algorithm for Assessing Groundwater Potential
Soyoung Park, Jinsoo Kim
Sustainability (2021) Vol. 13, Iss. 5, pp. 2459-2459
Open Access | Times Cited: 23
Machine Learning and Hyperparameters Algorithms for Identifying Groundwater Aflaj Potential Mapping in Semi-Arid Ecosystems Using LiDAR, Sentinel-2, GIS Data, and Analysis
Khalifa M. Al‐Kindi, Saeid Janizadeh
Remote Sensing (2022) Vol. 14, Iss. 21, pp. 5425-5425
Open Access | Times Cited: 16
Effects of DEM resolution and application of solely DEM-derived indicators on groundwater potential mapping in the mountainous area
Hanxiang Xiong, Shilong Yang, Jiayao Tan, et al.
Journal of Hydrology (2024) Vol. 636, pp. 131349-131349
Closed Access | Times Cited: 3
Machine Learning Self-Diffusion Prediction for Lennard-Jones Fluids in Pores
Calen J. Leverant, Jacob Harvey, Todd M. Alam, et al.
The Journal of Physical Chemistry C (2021) Vol. 125, Iss. 46, pp. 25898-25906
Open Access | Times Cited: 20
Developing a new method for future groundwater potentiality mapping under climate change in Bisha watershed, Saudi Arabia
Javed Mallick, Mohammed K. Al Mesfer, Majed Alsubih, et al.
Geocarto International (2022) Vol. 37, Iss. 26, pp. 14495-14527
Closed Access | Times Cited: 12
A hybrid intelligent model for spatial analysis of groundwater potential around Urmia Lake, Iran
Omid Asadi Nalivan, Seyed Ali Mousavi Tayebi, Mohammad Mehrabi, et al.
Stochastic Environmental Research and Risk Assessment (2022) Vol. 37, Iss. 5, pp. 1821-1838
Closed Access | Times Cited: 12
Mapping Groundwater Prospective Zones Using Remote Sensing and Geographical Information System Techniques in Wadi Fatima, Western Saudi Arabia
Mohamed Abdelkareem, Fathy Abdalla, Fahad Alshehri, et al.
Sustainability (2023) Vol. 15, Iss. 21, pp. 15629-15629
Open Access | Times Cited: 6
Comparing numerical modelling, traditional machine learning and theory-guided machine learning in inverse modeling of groundwater dynamics: A first study case application
Adoubi Vincent De Paul Adombi, Romain Chesnaux, Marie‐Amélie Boucher
Journal of Hydrology (2022) Vol. 615, pp. 128600-128600
Closed Access | Times Cited: 9
Potentialities and development of groundwater resources applying machine learning models in the extended section of Manbhum-Singhbhum Plateau, India
Arijit Ghosh, Biswajit Bera
HydroResearch (2023) Vol. 7, pp. 1-14
Open Access | Times Cited: 5

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