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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:

Hybrid Physically Based and Deep Learning Modeling of a Snow Dominated, Mountainous, Karst Watershed
Tianfang Xu, Qianqiu Longyang, Conor Tyson, et al.
Water Resources Research (2022) Vol. 58, Iss. 3
Open Access | Times Cited: 35

Showing 1-25 of 35 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
Distributed Hydrological Modeling With Physics‐Encoded Deep Learning: A General Framework and Its Application in the Amazon
Chao Wang, Shijie Jiang, Yi Zheng, et al.
Water Resources Research (2024) Vol. 60, Iss. 4
Open Access | Times Cited: 17
Transformer Versus LSTM: A Comparison of Deep Learning Models for Karst Spring Discharge Forecasting
Anna Pölz, Alfred Paul Blaschke, Jürgen Komma, et al.
Water Resources Research (2024) Vol. 60, Iss. 4
Open Access | Times Cited: 12
How does the climate change effect on hydropower potential, freshwater fisheries, and hydrological response of snow on water availability?
Shan‐e‐hyder Soomro, Abdul Razzaque Soomro, Sahar Batool, et al.
Applied Water Science (2024) Vol. 14, Iss. 4
Open Access | Times Cited: 11
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
Evaluation and Interpretation of Runoff Forecasting Models Based on Hybrid Deep Neural Networks
Xin Yang, Jianzhong Zhou, Qianyi Zhang, et al.
Water Resources Management (2024) Vol. 38, Iss. 6, pp. 1987-2013
Closed Access | Times Cited: 9
Spatiotemporal deep learning rainfall-runoff forecasting combined with remote sensing precipitation products in large scale basins
Shuang Zhu, Jianan Wei, Hairong Zhang, et al.
Journal of Hydrology (2022) Vol. 616, pp. 128727-128727
Closed Access | Times Cited: 34
An Outlook for Deep Learning in Ecosystem Science
George L. W. Perry, Rupert Seidl, André M. Bellvé, et al.
Ecosystems (2022) Vol. 25, Iss. 8, pp. 1700-1718
Open Access | Times Cited: 33
ML-Based Streamflow Prediction in the Upper Colorado River Basin Using Climate Variables Time Series Data
Pouya Hosseinzadeh, Ayman Nassar, Soukaïna Filali Boubrahimi, et al.
Hydrology (2023) Vol. 10, Iss. 2, pp. 29-29
Open Access | Times Cited: 17
Augmenting geophysical interpretation of data-driven operational water supply forecast modeling for a western US river using a hybrid machine learning approach
Sean W. Fleming, Velimir V. Vesselinov, Angus G. Goodbody
Journal of Hydrology (2021) Vol. 597, pp. 126327-126327
Closed Access | Times Cited: 38
Enhancing Flood Simulation in Data-Limited Glacial River Basins through Hybrid Modeling and Multi-Source Remote Sensing Data
Weiwei Ren, Xin Li, Donghai Zheng, et al.
Remote Sensing (2023) Vol. 15, Iss. 18, pp. 4527-4527
Open Access | Times Cited: 13
An LSTM approach to deciphering irrigation operations from remote sensing and groundwater levels records
Shiqi Wei, Tianfang Xu
Agricultural Water Management (2025) Vol. 308, pp. 109273-109273
Open Access
Prediction of runoff in the upper reaches of the Hei River based on the LSTM model guided by physical mechanisms
Huazhu Xue, Chao Guo, Guotao Dong, et al.
Journal of Hydrology Regional Studies (2025) Vol. 58, pp. 102218-102218
Closed Access
Deep learning model for flood probabilistic forecasting considering spatiotemporal rainfall distribution and hydrologic uncertainty
Xin Xiang, Shenglian Guo, C. Li, et al.
Journal of Hydrology (2025), pp. 132879-132879
Closed Access
Probabilistic runoff forecasting by integrating improved conceptual hydrological model with interpretable deep learning approach in a typical karst basin, Southwest China
Shufeng Lai, Chongxun Mo, Xingbi Lei, et al.
Journal of Hydrology (2025), pp. 132950-132950
Closed Access
Performance and modeling of infiltration flow in cracked saline soils
Haoxuan Feng, Xuguang Xing, Jiahao Xing, et al.
Journal of Hydrology (2025), pp. 133054-133054
Closed Access
Revealing the positive influence of young water fractions derived from stable isotopes on the robustness of karst water resources predictions
Kübra Özdemir Çallı, Daniel Bittner, Yan Liu, et al.
Journal of Hydrology (2023) Vol. 621, pp. 129549-129549
Closed Access | Times Cited: 9
Enhancing Monthly Streamflow Prediction Using Meteorological Factors and Machine Learning Models in the Upper Colorado River Basin
Saichand Thota, Ayman Nassar, Soukaïna Filali Boubrahimi, et al.
Hydrology (2024) Vol. 11, Iss. 5, pp. 66-66
Open Access | Times Cited: 3
On the Sensitivity of Future Hydrology in the Colorado River to the Selection of the Precipitation Partitioning Method
Zhaocheng Wang, Enrique R. Vivoni, Kristen M. Whitney, et al.
Water Resources Research (2024) Vol. 60, Iss. 6
Open Access | Times Cited: 3
Hydrologically Informed Machine Learning for Rainfall-Runoff Modelling: Towards Distributed Modelling
Herath Mudiyanselage Viraj Vidura Herath, Jayashree Chadalawada, Vladan Babovic
(2020)
Open Access | Times Cited: 23
Effects of meteorological forcing uncertainty on high-resolution snow modeling and streamflow prediction in a mountainous karst watershed
Conor Tyson, Qianqiu Longyang, Bethany T. Neilson, et al.
Journal of Hydrology (2023) Vol. 619, pp. 129304-129304
Open Access | Times Cited: 7
Dissolving the mystery of subsurface controls on snowmelt–discharge dynamics in karst mountain watersheds using hydrologic timeseries
Daniel Thurber, Belize Lane, Tianfang Xu, et al.
Hydrological Processes (2024) Vol. 38, Iss. 5
Closed Access | Times Cited: 1
3PG-MT-LSTM: A Hybrid Model under Biomass Compatibility Constraints for the Prediction of Long-Term Forest Growth to Support Sustainable Management
Jushuang Qin, Menglu Ma, Yutong Zhu, et al.
Forests (2023) Vol. 14, Iss. 7, pp. 1482-1482
Open Access | Times Cited: 4
Ecological Flow Management Identified as Leading Driver of Grassland Greening in the Gobi Desert Using Deep Learning
Siqi Li, Yi Zheng, Feng Han, et al.
Geophysical Research Letters (2023) Vol. 50, Iss. 11
Open Access | Times Cited: 3
Multiscale Learnable Physical Modeling and Data Assimilation Framework: Application to High-Resolution Regionalized Hydrological Simulation of Flash Floods
Ngo Nghi Truyen Huynh, Pierre‐André Garambois, Benjamin Renard, et al.
Authorea (Authorea) (2024)
Open Access
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