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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:

Technical note: Data assimilation and autoregression for using near-real-time streamflow observations in long short-term memory networks
Grey Nearing, Daniel Klotz, Jonathan Frame, et al.
Hydrology and earth system sciences (2022) Vol. 26, Iss. 21, pp. 5493-5513
Open Access | Times Cited: 24

Showing 24 citing articles:

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
Global prediction of extreme floods in ungauged watersheds
Grey Nearing, Déborah Cohen, Vusumuzi Dube, et al.
Nature (2024) Vol. 627, Iss. 8004, pp. 559-563
Open Access | Times Cited: 73
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
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
HESS Opinions: Never train a Long Short-Term Memory (LSTM) network on a single basin
Frederik Kratzert, Martin Gauch, Daniel Klotz, et al.
Hydrology and earth system sciences (2024) Vol. 28, Iss. 17, pp. 4187-4201
Open Access | Times Cited: 16
Optimal Postprocessing Strategies With LSTM for Global Streamflow Prediction in Ungauged Basins
Senlin Tang, Fubao Sun, Wenbin Liu, et al.
Water Resources Research (2023) Vol. 59, Iss. 7
Closed Access | Times Cited: 32
Robust Runoff Prediction With Explainable Artificial Intelligence and Meteorological Variables From Deep Learning Ensemble Model
Junhao Wu, Zhaocai Wang, Jinghan Dong, et al.
Water Resources Research (2023) Vol. 59, Iss. 9
Closed Access | Times Cited: 29
On the need for physical constraints in deep learning rainfall–runoff projections under climate change: a sensitivity analysis to warming and shifts in potential evapotranspiration
Sungwook Wi, Scott Steinschneider
Hydrology and earth system sciences (2024) Vol. 28, Iss. 3, pp. 479-503
Open Access | Times Cited: 13
Enhancing Flooding Depth Forecasting Accuracy in an Urban Area Using a Novel Trend Forecasting Method
Song-Yue Yang, You-Da Jhong, Bing-Chen Jhong, et al.
Water Resources Management (2024) Vol. 38, Iss. 4, pp. 1359-1380
Closed Access | Times Cited: 9
Long short-term memory models to quantify long-term evolution of streamflow discharge and groundwater depth in Alabama
Hossein Gholizadeh, Zhang Yong, Jonathan Frame, et al.
The Science of The Total Environment (2023) Vol. 901, pp. 165884-165884
Closed Access | Times Cited: 19
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
Improving trans-regional hydrological modelling by combining LSTM with big hydrological data
Senlin Tang, Fubao Sun, Qiang Zhang, et al.
Journal of Hydrology Regional Studies (2025) Vol. 58, pp. 102257-102257
Closed Access
Metamodeling of a Physically Based Pesticide Runoff Model with a Long Short-Term Memory Approach
Guillaume Métayer, Cécile Dagès, Marc Voltz, et al.
(2025)
Closed Access
How to enhance hydrological predictions in hydrologically distinct watersheds of the Indian subcontinent?
Nikunj K. Mangukiya, Ashutosh Sharma, Chaopeng Shen
Hydrological Processes (2023) Vol. 37, Iss. 7
Open Access | Times Cited: 13
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
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
Hyperparameter optimization of regional hydrological LSTMs by random search: A case study from Basque Country, Spain
Fateme Hosseini, Cristina Prieto, César Álvarez
Journal of Hydrology (2024), pp. 132003-132003
Open Access | Times Cited: 3
Inverse Modeling for Subsurface Flow Based on Deep Learning Surrogates and Active Learning Strategies
Nanzhe Wang, Haibin Chang, Dongxiao Zhang
Water Resources Research (2023) Vol. 59, Iss. 7
Open Access | Times Cited: 9
Ensemble learning of catchment-wise optimized LSTMs enhances regional rainfall-runoff modelling − case Study: Basque Country, Spain
Farzad Hosseini Hossein Abadi, Cristina Prieto, César Álvarez
Journal of Hydrology (2024), pp. 132269-132269
Open Access | Times Cited: 1
Precise Tuning of Regional Hydrological Lstm Networks: Simultaneous Systematic Random Search Optimization
Farzad Hosseini Hosseini Abadi, Cristina Prieto, Cesar Álvarez Díaz
(2024)
Closed Access
A diversity centric strategy for the selection of spatio-temporal training data for LSTM-based streamflow forecasting
Everett Snieder, Usman T. Khan
(2024)
Open Access
Machine Learning for Bayesian Experimental Design in the Subsurface
Robin Thibaut
Authorea (Authorea) (2023)
Open Access | Times Cited: 1
Constraining Flood Forecasting Uncertainties through Streamflow Data Assimilation in the Tropical Andes of Peru: Case of the Vilcanota River Basin
Harold Llauca, Miguel Arestegui, Waldo Lavado‐Casimiro
(2023)
Open Access | Times Cited: 1
Constraining Flood Forecasting Uncertainties through Streamflow Data Assimilation in the Tropical Andes of Peru: Case of the Vilcanota River Basin
Harold Llauca, Miguel Arestegui, Waldo Lavado‐Casimiro
Water (2023) Vol. 15, Iss. 22, pp. 3944-3944
Open Access
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