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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:

A review of machine learning methods for drought hazard monitoring and forecasting: Current research trends, challenges, and future research directions
Foyez Ahmed Prodhan, Jiahua Zhang, Shaikh Shamim Hasan, et al.
Environmental Modelling & Software (2022) Vol. 149, pp. 105327-105327
Closed Access | Times Cited: 123

Showing 1-25 of 123 citing articles:

Assessment and prediction of index based agricultural drought vulnerability using machine learning algorithms
Abdulla – Al Kafy, Arpita Bakshi, Milan Saha, et al.
The Science of The Total Environment (2023) Vol. 867, pp. 161394-161394
Closed Access | Times Cited: 68
Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research directions
Tao Hai, Sani I. Abba, Ahmed M. Al‐Areeq, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 129, pp. 107559-107559
Closed Access | Times Cited: 57
Research progress on the impact of climate change on wheat production in China
Yu‐Chen Fan, Yadong Yuan, Yadong Yuan, et al.
PeerJ (2025) Vol. 13, pp. e18569-e18569
Open Access | Times Cited: 2
Comparative assessment of empirical and hybrid machine learning models for estimating daily reference evapotranspiration in sub-humid and semi-arid climates
Siham Acharki, Ali Raza, Dinesh Kumar Vishwakarma, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Explainable machine learning for the prediction and assessment of complex drought impacts
Beichen Zhang, Fatima K. Abu Salem, Michael J. Hayes, et al.
The Science of The Total Environment (2023) Vol. 898, pp. 165509-165509
Closed Access | Times Cited: 27
Leveraging multisource data for accurate agricultural drought monitoring: A hybrid deep learning model
Xin Xiao, Wenting Ming, Xuan Luo, et al.
Agricultural Water Management (2024) Vol. 293, pp. 108692-108692
Open Access | Times Cited: 13
Artificial intelligence for climate prediction of extremes: State of the art, challenges, and future perspectives
Stefano Materia, Lluís Palma García, Chiem van Straaten, et al.
Wiley Interdisciplinary Reviews Climate Change (2024)
Open Access | Times Cited: 13
Utilizing machine learning and CMIP6 projections for short-term agricultural drought monitoring in central Europe (1900–2100)
Safwan Mohammed, Sana Arshad, Firas Alsilibe, et al.
Journal of Hydrology (2024) Vol. 633, pp. 130968-130968
Open Access | Times Cited: 12
Unleashing the power of machine learning and remote sensing for robust seasonal drought monitoring: A stacking ensemble approach
Xinlei Xu, Fangzheng Chen, Bin Wang, et al.
Journal of Hydrology (2024) Vol. 634, pp. 131102-131102
Closed Access | Times Cited: 11
An interpretable model for landslide susceptibility assessment based on Optuna hyperparameter optimization and Random Forest
Xin Xiao, Yi Zou, Jiangcheng Huang, et al.
Geomatics Natural Hazards and Risk (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 11
Advancements in drought using remote sensing: assessing progress, overcoming challenges, and exploring future opportunities
Vijendra Kumar, Kul Vaibhav Sharma, Quoc Bao Pham, et al.
Theoretical and Applied Climatology (2024) Vol. 155, Iss. 6, pp. 4251-4288
Closed Access | Times Cited: 10
Response of winter wheat to different drought levels based on Google Earth Engine in the Huang-Huai-Hai Region, China
Junfang Zhao, Huiwen Peng, Jia-Qi Yang, et al.
Agricultural Water Management (2024) Vol. 292, pp. 108662-108662
Open Access | Times Cited: 8
Modelling agricultural drought: a review of latest advances in big data technologies
Ismaguil Hanadé Houmma, Loubna El Mansouri, Sébastien Gadal, et al.
Geomatics Natural Hazards and Risk (2022) Vol. 13, Iss. 1, pp. 2737-2776
Open Access | Times Cited: 29
LSTM-CM: a hybrid approach for natural drought prediction based on deep learning and climate models
Tuong Quang Vo, Seon‐Ho Kim, Duc Hai Nguyen, et al.
Stochastic Environmental Research and Risk Assessment (2023) Vol. 37, Iss. 6, pp. 2035-2051
Closed Access | Times Cited: 20
The Drought Regime in Southern Africa: A Systematic Review
Fernando Maliti Chivangulula, Malik Amraoui, Mário Pereira
Climate (2023) Vol. 11, Iss. 7, pp. 147-147
Open Access | Times Cited: 19
Spatio-temporal distribution and prediction of agricultural and meteorological drought in a Mediterranean coastal watershed via GIS and machine learning
Siham Acharki, Sudhir Kumar Singh, Edivando Vítor do Couto, et al.
Physics and Chemistry of the Earth Parts A/B/C (2023) Vol. 131, pp. 103425-103425
Closed Access | Times Cited: 18
High Resolution Forecasting of Summer Drought in the Western United States
Ronnie Abolafia‐Rosenzweig, Cenlin He, Fei Chen, et al.
Water Resources Research (2023) Vol. 59, Iss. 3
Open Access | Times Cited: 17
Basin-Scale Daily Drought Prediction Using Convolutional Neural Networks in Fenhe River Basin, China
Zixuan Chen, Guojie Wang, Xikun Wei, et al.
Atmosphere (2024) Vol. 15, Iss. 2, pp. 155-155
Open Access | Times Cited: 6
A Novel Fusion-Based Methodology for Drought Forecasting
Huihui Zhang, Hugo A. Loáiciga, Tobias Sauter
Remote Sensing (2024) Vol. 16, Iss. 5, pp. 828-828
Open Access | Times Cited: 6
Forest fire mapping: a comparison between GIS-based random forest and Bayesian models
Farzaneh Noroozi, Gholamabbas Ghanbarian, Roja Safaeian, et al.
Natural Hazards (2024) Vol. 120, Iss. 7, pp. 6569-6592
Open Access | Times Cited: 6
Estimating evapotranspiration and drought dynamics of winter wheat under climate change: A case study in Huang-Huai-Hai region, China
Junfang Zhao, Jia-Qi Yang, Ruixi Huang, et al.
The Science of The Total Environment (2024) Vol. 949, pp. 175114-175114
Closed Access | Times Cited: 6
Research on runoff process vectorization and integration of deep learning algorithms for flood forecasting
Chengshuai Liu, Wenzhong Li, Caihong Hu, et al.
Journal of Environmental Management (2024) Vol. 362, pp. 121260-121260
Closed Access | Times Cited: 5
Characterizing drought prediction with deep learning: A literature review
Aldo Márquez-Grajales, Ramiro Villegas-Vega, Fernando Salas-Martínez, et al.
MethodsX (2024) Vol. 13, pp. 102800-102800
Open Access | Times Cited: 5
Long-term drought prediction using deep neural networks based on geospatial weather data
Alexander Marusov, Vsevolod Grabar, Yury Maximov, et al.
Environmental Modelling & Software (2024) Vol. 179, pp. 106127-106127
Open Access | Times Cited: 5
Forecasting water levels using ConvLSTM algorithm in the Everglades, USA
Raidan Bassah, Gerald Corzo, Biswa Bhattacharya, et al.
Journal of Hydrology (2025), pp. 132195-132195
Closed Access
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