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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 hybrid deep learning applications for streamflow forecasting
Kin‐Wang Ng, Yuk Feng Huang, Chai Hoon Koo, et al.
Journal of Hydrology (2023) Vol. 625, pp. 130141-130141
Closed Access | Times Cited: 72

Showing 1-25 of 72 citing articles:

Spatio-temporal deep learning model for accurate streamflow prediction with multi-source data fusion
Zhaocai Wang, Nannan Xu, Xiaoguang Bao, et al.
Environmental Modelling & Software (2024) Vol. 178, pp. 106091-106091
Closed Access | Times Cited: 33
Enhancing carbon price point-interval multi-step-ahead prediction using a hybrid framework of autoformer and extreme learning machine with multi-factors
Baoli Wang, Zhaocai Wang, Zhiyuan Yao
Expert Systems with Applications (2025), pp. 126467-126467
Closed Access | Times Cited: 4
DTTR: Encoding and decoding monthly runoff prediction model based on deep temporal attention convolution and multimodal fusion
Wenchuan Wang, Wei-can Tian, Xiao-xue Hu, et al.
Journal of Hydrology (2024) Vol. 643, pp. 131996-131996
Closed Access | Times Cited: 13
Long-term streamflow forecasting in data-scarce regions: Insightful investigation for leveraging satellite-derived data, Informer architecture, and concurrent fine-tuning transfer learning
Fatemeh Ghobadi, Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Doosun Kang
Journal of Hydrology (2024) Vol. 631, pp. 130772-130772
Closed Access | Times Cited: 12
An interpretable hybrid deep learning model for flood forecasting based on Transformer and LSTM
Wenzhong Li, Chengshuai Liu, Yingying Xu, et al.
Journal of Hydrology Regional Studies (2024) Vol. 54, pp. 101873-101873
Open Access | Times Cited: 12
A novel additive regression model for streamflow forecasting in German rivers
Francesco Granata, Fabio Di Nunno, Quoc Bao Pham
Results in Engineering (2024) Vol. 22, pp. 102104-102104
Open Access | Times Cited: 11
In-depth simulation of rainfall–runoff relationships using machine learning methods
Mehdi Fuladipanah, Alireza Shahhosseini, Namal Rathnayake, et al.
Water Practice & Technology (2024) Vol. 19, Iss. 6, pp. 2442-2459
Open Access | Times Cited: 10
Enhancing Streamflow Prediction Physically Consistently Using Process-Based Modeling and Domain Knowledge: A Review
Bisrat Ayalew Yifru, Kyoung Jae Lim, Seoro Lee
Sustainability (2024) Vol. 16, Iss. 4, pp. 1376-1376
Open Access | Times Cited: 9
A state-of-the-art review of long short-term memory models with applications in hydrology and water resources
Zhong-kai Feng, J. Zhang, Wen-jing Niu
Applied Soft Computing (2024), pp. 112352-112352
Closed Access | Times Cited: 8
Deep learning algorithms and their fuzzy extensions for streamflow prediction in climate change framework
Rishith Kumar Vogeti, Rahul Jauhari, Bhavesh Rahul Mishra, et al.
Journal of Water and Climate Change (2024) Vol. 15, Iss. 2, pp. 832-848
Open Access | Times Cited: 5
Meta-LSTM in hydrology: Advancing runoff predictions through model-agnostic meta-learning
Kaixuan Cai, Jinxin He, Qingliang Li, et al.
Journal of Hydrology (2024) Vol. 639, pp. 131521-131521
Closed Access | Times Cited: 5
River Water Temperature Prediction Using a Hybrid Model Based on Variational Mode Decomposition (VMD) and Outlier Robust Extreme Learning Machine
Ehsan Mirzania, Thendiyath Roshni, Mohammad Ali Ghorbani, et al.
Environmental Processes (2024) Vol. 11, Iss. 3
Closed Access | Times Cited: 5
Enhanced multi-step streamflow series forecasting using hybrid signal decomposition and optimized reservoir computing models
José Henrique Kleinübing Larcher, Stéfano Frizzo Stefenon, Leandro dos Santos Coelho, et al.
Expert Systems with Applications (2024) Vol. 255, pp. 124856-124856
Closed Access | Times Cited: 5
Framework for multivariate carbon price forecasting: A novel hybrid model
Xuankai Zhang, Ying Zong, Pei Du, et al.
Journal of Environmental Management (2024) Vol. 369, pp. 122275-122275
Closed Access | Times Cited: 5
Advanced streamflow forecasting for Central European Rivers: The Cutting-Edge Kolmogorov-Arnold networks compared to Transformers
Francesco Granata, Senlin Zhu, Fabio Di Nunno
Journal of Hydrology (2024), pp. 132175-132175
Closed Access | Times Cited: 5
A deep learning-based probabilistic approach to flash flood warnings in mountainous catchments
Yuting Zhao, Xuemei Wu, Wenjiang Zhang, et al.
Journal of Hydrology (2025) Vol. 652, pp. 132677-132677
Closed Access
Twin extreme learning machine model and cooperation search algorithm for multi-step-ahead point and interval runoff prediction
Zhong-kai Feng, Pan Liu, Wen-jing Niu, et al.
Journal of Hydrology (2025), pp. 132778-132778
Closed Access
Advanced groundwater level forecasting with hybrid deep learning model: Tackling water challenges in Taiwan’s largest alluvial fan
Yu-Wen Chang, Wei Sun, Pu-Yun Kow, et al.
Journal of Hydrology (2025), pp. 132887-132887
Closed Access
Improve streamflow simulations by combining machine learning pre-processing and post-processing
Yuhang Zhang, Aizhong Ye, Jinyang Li, et al.
Journal of Hydrology (2025), pp. 132904-132904
Closed Access
Enhancing seasonal streamflow prediction using multistage hybrid stochastic data-driven deep learning methodology with deep feature selection
Asif Iqbal, Tanveer Ahmed Siddiqi
Environmental and Ecological Statistics (2025)
Closed Access
Improving multi-model ensemble streamflow forecasts by combining lumped, distributed and deep learning hydrological models
William F. Armstrong, Richard Arsenault, Jean‐Luc Martel, et al.
Hydrological Sciences Journal (2025)
Closed Access
A review of recent hybridized machine learning methodologies for time series forecasting on water-related variables
Van Kwan Zhi Koh, Ye Li, Xing Yong Kek, et al.
Journal of Hydrology (2025), pp. 132909-132909
Closed Access
The multi-GPU Wetland DEM Ponding Model
Tonghe Liu, S. J. Trim, Seok‐Bum Ko, et al.
Computers & Geosciences (2025), pp. 105912-105912
Closed Access
Using Deep Learning in Ensemble Streamflow Forecasting: Exploring the Predictive Value of Explicit Snowpack Information
Parthkumar Modi, Keith S. Jennings, Joseph Kasprzyk, et al.
Journal of Advances in Modeling Earth Systems (2025) Vol. 17, Iss. 3
Open Access
Protocols for Water and Environmental Modeling Using Machine Learning in California
Minxue He, Prabhjot Sandhu, Peyman Namadi, et al.
Hydrology (2025) Vol. 12, Iss. 3, pp. 59-59
Open Access
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