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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:

Toward interpretable LSTM-based modeling of hydrological systems
Luis De La Fuente, Mohammad Reza Ehsani, Hoshin V. Gupta, et al.
Hydrology and earth system sciences (2024) Vol. 28, Iss. 4, pp. 945-971
Open Access | Times Cited: 14

Showing 14 citing articles:

Soil Moisture Memory: State‐Of‐The‐Art and the Way Forward
Mehdi Rahmati, Wulf Amelung, Cosimo Brogi, et al.
Reviews of Geophysics (2024) Vol. 62, Iss. 2
Open Access | Times Cited: 12
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 | Times Cited: 1
Runoff Simulation in Data-Scarce Alpine Regions: Comparative Analysis Based on LSTM and Physically Based Models
Jiajia Yue, Li Zhou, Juan Du, et al.
Water (2024) Vol. 16, Iss. 15, pp. 2161-2161
Open Access | Times Cited: 4
Understanding the inter-event variability of recession flow characteristics and its drivers
Owees Rashid, Tushar Apurv
Journal of Hydrology (2025), pp. 133033-133033
Closed Access
Improved streamflow prediction accuracy in Boreal climate watershed using a LSTM model: A comparative study
Kamal Islam, J. A. Daraio, Mumtaz Cheema, et al.
PLOS Water (2025) Vol. 4, Iss. 4, pp. e0000359-e0000359
Open Access
MACHINE LEARNING-BASED HYDROGRAPH MODELING WITH LSTM: A CASE STUDY IN THE JATIGEDE RESERVOIR CATCHMENT, INDONESIA
Neil Andika, Piter Wongso, Faizal Immaddudin Wira Rohmat, et al.
Results in Earth Sciences (2025), pp. 100090-100090
Open Access
Comparative Analysis of LSTM and HEC-HMS Models for Streamflow Prediction: A Case Study of the Upper Turtle River
Adewale Ajao, Yeo Lim Howe
World Environmental and Water Resources Congress 2011 (2025), pp. 1121-1130
Closed Access
An adaptive rainfall-runoff model for daily runoff prediction under the changing environment: Stream-LSTM
Feichi Hu, Qinli Yang, Junran Yang, et al.
Environmental Modelling & Software (2025), pp. 106524-106524
Closed Access
Integrated hydrological modelling and streamflow characterization of Gangotri Glacier meltwater
Manohar Arora, N. K. Goel, Kapil Kesarwani, et al.
Applied Water Science (2024) Vol. 14, Iss. 10
Open Access | Times Cited: 2
Towards Interpretable Physical‐Conceptual Catchment‐Scale Hydrological Modeling Using the Mass‐Conserving‐Perceptron
Yuan‐Heng Wang, Hoshin V. Gupta
Water Resources Research (2024) Vol. 60, Iss. 10
Open Access | Times Cited: 2
Uncovering the Dynamic Drivers of Floods Through Interpretable Deep Learning
Yuanhao Xu, Kairong Lin, Caihong Hu, et al.
Earth s Future (2024) Vol. 12, Iss. 10
Open Access | Times Cited: 2
Investigating the Model Hypothesis Space: Benchmarking Automatic Model Structure Identification With a Large Model Ensemble
Diana Spieler, Niels Schütze
Water Resources Research (2024) Vol. 60, Iss. 7
Open Access | Times Cited: 1
Characterizing the Evolution of Extreme Water Levels with Long Short-Term Memory Station-Based Approximated Models and Transfer Learning Techniques
Samuel Daramola, Paúl Muñoz, Jennifer L. Irish, et al.
(2024)
Closed Access
Streamflow Forecasting: A Comparative Analysis of Arimax, Rolling Forecasting Lstm Neural Network and Physical-Based Models in an Italian Natural Catchment
Diego Perazzolo, Gianluca Lazzaro, Alvise Fiume, et al.
(2024)
Open Access
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