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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:

Generalization of an Encoder-Decoder LSTM model for flood prediction in ungauged catchments
Yikui Zhang, Silvan Ragettli, Péter Molnár, et al.
Journal of Hydrology (2022) Vol. 614, pp. 128577-128577
Open Access | Times Cited: 48

Showing 1-25 of 48 citing articles:

Continuous streamflow prediction in ungauged basins: long short-term memory neural networks clearly outperform traditional hydrological models
Richard Arsenault, Jean‐Luc Martel, Frédéric Brunet, et al.
Hydrology and earth system sciences (2023) Vol. 27, Iss. 1, pp. 139-157
Open Access | Times Cited: 102
Time-series generative adversarial networks for flood forecasting
Peiyao Weng, Yu Tian, Yingfei Liu, et al.
Journal of Hydrology (2023) Vol. 622, pp. 129702-129702
Closed Access | Times Cited: 22
Improving urban flood prediction using LSTM-DeepLabv3+ and Bayesian optimization with spatiotemporal feature fusion
Zuxiang Situ, Qi Wang, Shuai Teng, et al.
Journal of Hydrology (2024) Vol. 630, pp. 130743-130743
Closed Access | Times Cited: 14
Comparison of strategies for multistep-ahead lake water level forecasting using deep learning models
Gang Li, Zhangkang Shu, Miaoli Lin, et al.
Journal of Cleaner Production (2024) Vol. 444, pp. 141228-141228
Closed Access | Times Cited: 12
Streamflow prediction in ungauged catchments through use of catchment classification and deep learning
Miao He, S. S. Jiang, Liliang Ren, et al.
Journal of Hydrology (2024) Vol. 639, pp. 131638-131638
Closed 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
Research on machine learning hybrid framework by coupling grid-based runoff generation model and runoff process vectorization for flood forecasting
Chengshuai Liu, Tianning Xie, Wenzhong Li, et al.
Journal of Environmental Management (2024) Vol. 364, pp. 121466-121466
Closed Access | Times Cited: 5
A Lake-Flood Forecasting Method Coupling the Ce-Qual-W2 and Pinn Models
M. Shi, Hongyuan Fang, Yangyang Xie, et al.
(2025)
Closed Access
VMDI-LSTM-ED: A novel enhanced decomposition ensemble model incorporating data integration for accurate non-stationary daily streamflow forecasting
Jiadong Liu, Teng Xu, Chunhui Lu
Journal of Hydrology (2025), pp. 132769-132769
Closed Access
A diversity-centric strategy for the selection of spatio-temporal training data for LSTM-based streamflow forecasting
Everett Snieder, Usman T. Khan
Hydrology and earth system sciences (2025) Vol. 29, Iss. 3, pp. 785-798
Open Access
A spatiotemporal watershed-scale machine-learning model for hourly and daily flood-water level prediction: the case of the tidal Beigang River, Taiwan
Wen‐Dar Guo, Wei‐Bo Chen, Chih-Hsin Chang
Natural Hazards (2025)
Closed Access
Transforming Prediction into Decision: Leveraging Transformer-Long Short-Term Memory Networks and Automatic Control for Enhanced Water Treatment Efficiency and Sustainability
Cheng Qiu, Qingchuan Li, Jing Jiang, et al.
Sensors (2025) Vol. 25, Iss. 6, pp. 1652-1652
Open Access
Rainfall-based flood prediction by hybrid deep architecture with entropy and statistical feature set
Vanam Yoganand, Sheela Rani B, Nagamani Kattukota, et al.
International Journal of Image and Data Fusion (2025) Vol. 16, Iss. 1
Closed Access
Exploring a spatiotemporal hetero graph-based long short-term memory model for multi-step-ahead flood forecasting
Yuxuan Luo, Yanlai Zhou, Hua Chen, et al.
Journal of Hydrology (2024) Vol. 633, pp. 130937-130937
Closed Access | Times Cited: 4
A national-scale hybrid model for enhanced streamflow estimation – consolidating a physically based hydrological model with long short-term memory (LSTM) networks
Jun Liu, Julian Koch, Simon Stisen, et al.
Hydrology and earth system sciences (2024) Vol. 28, Iss. 13, pp. 2871-2893
Open Access | Times Cited: 4
Predicting the Evolution of Extreme Water Levels With Long Short‐Term Memory Station‐Based Approximated Models and Transfer Learning Techniques
Samuel Daramola, David F. Muñoz, Paúl Muñoz, et al.
Water Resources Research (2025) Vol. 61, Iss. 3
Open Access
Utilizing sequential modeling in collaborative method for flood forecasting
Wandee Thaisiam, Konlawat Yomwilai, Papis Wongchaisuwat
Journal of Hydrology (2024) Vol. 636, pp. 131290-131290
Closed Access | Times Cited: 3
Value of process understanding in the era of machine learning: A case for recession flow prediction
Prashant Istalkar, Akshay Kadu, Basudev Biswal
Journal of Hydrology (2023) Vol. 626, pp. 130350-130350
Closed Access | Times Cited: 9
Enhancing generalizability of data-driven urban flood models by incorporating contextual information
Tabea Cache, Milton Gomez, Tom Beucler, et al.
Hydrology and earth system sciences (2024) Vol. 28, Iss. 24, pp. 5443-5458
Open Access | Times Cited: 3
Bias correcting discharge simulations from the GEOGloWS global hydrologic model
Riley Chad Hales, Gustavious P. Williams, E. James Nelson, et al.
Journal of Hydrology (2023) Vol. 626, pp. 130279-130279
Open Access | Times Cited: 7
Prediction of flash flood peak discharge in hilly areas with ungauged basins based on machine learning
Weilin Wang, Guoqing Sang, Qiang Zhao, et al.
Hydrology Research (2024) Vol. 55, Iss. 8, pp. 801-814
Closed Access | Times Cited: 2
Factors influencing calibration of a semi-distributed mixed runoff hydrological model: A study on nine small mountain catchments in China
Lei Wen, Zhongbo Yu, Ke Zhang, et al.
Journal of Hydrology Regional Studies (2023) Vol. 47, pp. 101418-101418
Open Access | Times Cited: 6
Training LSTMS with circular-shift epochs for accurate event forecasting in imbalanced time series
Xiaoqian Chen, Lalit Gupta
Expert Systems with Applications (2023) Vol. 238, pp. 121701-121701
Closed Access | Times Cited: 6
Revisit hydrological modeling in ungauged catchments comparing regionalization, satellite observations, and machine learning approaches
Rijurekha Dasgupta, Subhasish Das, Gourab Banerjee, et al.
HydroResearch (2023) Vol. 7, pp. 15-31
Open Access | Times Cited: 6
Investigation of Runoff and Flooding in Urban Areas based on Hydrology Models: A Literature Review
Eissa Alshammari, Alias Abdul Rahman, R. Ranis, et al.
International Journal of Geoinformatics (2024)
Open Access | Times Cited: 1
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