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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:

Benchmarking data-driven rainfall–runoff models in Great Britain: a comparison of long short-term memory (LSTM)-based models with four lumped conceptual models
Thomas Lees, Marcus Buechel, Bailey Anderson, et al.
Hydrology and earth system sciences (2021) Vol. 25, Iss. 10, pp. 5517-5534
Open Access | Times Cited: 164

Showing 1-25 of 164 citing articles:

Hydrological concept formation inside long short-term memory (LSTM) networks
Thomas Lees, Steven Reece, Frederik Kratzert, et al.
Hydrology and earth system sciences (2022) Vol. 26, Iss. 12, pp. 3079-3101
Open Access | Times Cited: 127
Hybrid forecasting: blending climate predictions with AI models
Louise Slater, Louise Arnal, Marie‐Amélie Boucher, et al.
Hydrology and earth system sciences (2023) Vol. 27, Iss. 9, pp. 1865-1889
Open Access | Times Cited: 84
Enhancing predictive skills in physically-consistent way: Physics Informed Machine Learning for hydrological processes
Pravin Bhasme, Jenil Vagadiya, Udit Bhatia
Journal of Hydrology (2022) Vol. 615, pp. 128618-128618
Open Access | Times Cited: 78
The Great Lakes Runoff Intercomparison Project Phase 4: the Great Lakes (GRIP-GL)
Juliane Mai, Hongren Shen, Bryan A. Tolson, et al.
Hydrology and earth system sciences (2022) Vol. 26, Iss. 13, pp. 3537-3572
Open Access | Times Cited: 78
RR-Former: Rainfall-runoff modeling based on Transformer
Hanlin Yin, Zilong Guo, Xiuwei Zhang, et al.
Journal of Hydrology (2022) Vol. 609, pp. 127781-127781
Closed Access | Times Cited: 74
In Defense of Metrics: Metrics Sufficiently Encode Typical Human Preferences Regarding Hydrological Model Performance
Martin Gauch, Frederik Kratzert, Oren Gilon, et al.
Water Resources Research (2023) Vol. 59, Iss. 6
Open Access | Times Cited: 46
Improving LSTM hydrological modeling with spatiotemporal deep learning and multi-task learning: A case study of three mountainous areas on the Tibetan Plateau
Bu Li, Ruidong Li, Ting Sun, et al.
Journal of Hydrology (2023) Vol. 620, pp. 129401-129401
Open Access | Times Cited: 44
Comparing a long short-term memory (LSTM) neural network with a physically-based hydrological model for streamflow forecasting over a Canadian catchment
Behmard Sabzipour, Richard Arsenault, Magali Troin, et al.
Journal of Hydrology (2023) Vol. 627, pp. 130380-130380
Open Access | Times Cited: 44
DeepGR4J: A deep learning hybridization approach for conceptual rainfall-runoff modelling
Arpit Kapoor, Sahani Pathiraja, Lucy Marshall, et al.
Environmental Modelling & Software (2023) Vol. 169, pp. 105831-105831
Open Access | Times Cited: 42
Alternate pathway for regional flood frequency analysis in data-sparse region
Nikunj K. Mangukiya, Ashutosh Sharma
Journal of Hydrology (2024) Vol. 629, pp. 130635-130635
Closed Access | Times Cited: 22
Urban real-time rainfall-runoff prediction using adaptive SSA-decomposition with dual attention
Yuan Tian, Weiming Fu, Yi Xiang, et al.
Journal of Hydrology (2025), pp. 132701-132701
Closed Access | Times Cited: 1
IHACRES, GR4J and MISD-based multi conceptual-machine learning approach for rainfall-runoff modeling
Babak Mohammadi, Mir Jafar Sadegh Safari, Saeed Vazifehkhah
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 65
Improving hydrologic models for predictions and process understanding using neural ODEs
Marvin Höge, Andreas Scheidegger, Marco Baity‐Jesi, et al.
Hydrology and earth system sciences (2022) Vol. 26, Iss. 19, pp. 5085-5102
Open Access | Times Cited: 46
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: 46
A new seq2seq architecture for hourly runoff prediction using historical rainfall and runoff as input
Shuai Gao, Shuo Zhang, Yuefei Huang, et al.
Journal of Hydrology (2022) Vol. 612, pp. 128099-128099
Closed Access | Times Cited: 37
Benchmarking hydrological models for an uncertain future
Keith Beven
Hydrological Processes (2023) Vol. 37, Iss. 5
Open Access | Times Cited: 31
Runoff predictions in new-gauged basins using two transformer-based models
Hanlin Yin, Wu Zhu, Xiuwei Zhang, et al.
Journal of Hydrology (2023) Vol. 622, pp. 129684-129684
Closed Access | Times Cited: 30
Enhancing process-based hydrological models with embedded neural networks: A hybrid approach
Bu Li, Ting Sun, Fuqiang Tian, et al.
Journal of Hydrology (2023) Vol. 625, pp. 130107-130107
Open Access | Times Cited: 27
Long short-term memory models of water quality in inland water environments
JongCheol Pyo, Yakov Pachepsky, Soobin Kim, et al.
Water Research X (2023) Vol. 21, pp. 100207-100207
Open Access | Times Cited: 24
A Novel Smoothing-Based Deep Learning Time-Series Approach for Daily Suspended Sediment Load Prediction
Bibhuti Bhusan Sahoo, Sovan Sankalp, Özgür Kişi
Water Resources Management (2023) Vol. 37, Iss. 11, pp. 4271-4292
Closed Access | Times Cited: 23
Application of a New Hybrid Deep Learning Model That Considers Temporal and Feature Dependencies in Rainfall–Runoff Simulation
Feng Zhou, Yangbo Chen, Jun Liu
Remote Sensing (2023) Vol. 15, Iss. 5, pp. 1395-1395
Open Access | Times Cited: 22
Predicting streamflow with LSTM networks using global datasets
Katharina Wilbrand, Riccardo Taormina, Marie‐Claire ten Veldhuis, et al.
Frontiers in Water (2023) Vol. 5
Open Access | Times Cited: 22
Deep learning-based algorithms for long-term prediction of chlorophyll-a in catchment streams
Ather Abbas, Minji Park, Sang‐Soo Baek, et al.
Journal of Hydrology (2023) Vol. 626, pp. 130240-130240
Open Access | Times Cited: 22
Enhancing streamflow simulation in large and human-regulated basins: Long short-term memory with multiscale attributes
Arken Tursun, Xianhong Xie, Yibing Wang, et al.
Journal of Hydrology (2024) Vol. 630, pp. 130771-130771
Closed Access | Times Cited: 10
A Comprehensive Review of Methods for Hydrological Forecasting Based on Deep Learning
Xinfeng Zhao, Hongyan Wang, Mingyu Bai, et al.
Water (2024) Vol. 16, Iss. 10, pp. 1407-1407
Open Access | Times Cited: 10
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