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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:

A hybrid deep learning framework with physical process description for simulation of evapotranspiration
Han Chen, Jinhui Jeanne Huang‬‬‬‬, Sonam Sandeep Dash, et al.
Journal of Hydrology (2022) Vol. 606, pp. 127422-127422
Closed Access | Times Cited: 44

Showing 1-25 of 44 citing articles:

A deep learning-based hybrid model of global terrestrial evaporation
Akash Koppa, Dominik Rains, Petra Hulsman, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 101
Evaluation of seven satellite-based and two reanalysis global terrestrial evapotranspiration products
Zijing Xie, Yunjun Yao, Qingxin Tang, et al.
Journal of Hydrology (2024) Vol. 630, pp. 130649-130649
Closed Access | Times Cited: 15
Estimating reference crop evapotranspiration using improved convolutional bidirectional long short-term memory network by multi-head attention mechanism in the four climatic zones of China
Juan Dong, Liwen Xing, Ningbo Cui, et al.
Agricultural Water Management (2024) Vol. 292, pp. 108665-108665
Open Access | Times Cited: 14
A Deep Learning Approach Based on Physical Constraints for Predicting Soil Moisture in Unsaturated Zones
Yi Wang, Wenke Wang, Zhitong Ma, et al.
Water Resources Research (2023) Vol. 59, Iss. 11
Closed Access | Times Cited: 17
Enhancing Soil Moisture Forecasting Accuracy with REDF-LSTM: Integrating Residual En-Decoding and Feature Attention Mechanisms
Xiaoning Li, Ziyin Zhang, Qingliang Li, et al.
Water (2024) Vol. 16, Iss. 10, pp. 1376-1376
Open Access | Times Cited: 7
The high spatial resolution Drought Response Index (HiDRI): An integrated framework for monitoring vegetation drought with remote sensing, deep learning, and spatiotemporal fusion
Zhenheng Xu, Hao Sun, Tian Zhang, et al.
Remote Sensing of Environment (2024) Vol. 312, pp. 114324-114324
Closed Access | Times Cited: 5
Characterisation of Water and Heat Fluxes of Typical Crops and Simulation of Evapotranspiration in Saline‐Alkali Soil of the Yellow River Delta, China
Qiu Haonan, Shihong Yang, Guangmei Wang, et al.
Journal of Agronomy and Crop Science (2025) Vol. 211, Iss. 1
Closed Access
Integrating machine learning with thermal-driven analytical energy balance model improved terrestrial evapotranspiration estimation through enhanced surface conductance
Yun Bai, Kanishka Mallick, Tian Hu, et al.
Remote Sensing of Environment (2024) Vol. 311, pp. 114308-114308
Closed Access | Times Cited: 4
Improving high uncertainty of evapotranspiration products under extreme climatic conditions based on deep learning and ERA5 reanalysis data
Long Qian, Xingjiao Yu, Lifeng Wu, et al.
Journal of Hydrology (2024) Vol. 641, pp. 131755-131755
Closed Access | Times Cited: 4
Can system dynamics explain long-term hydrological behaviors? The role of endogenous linking structure
Xinyao Zhou, Zhuping Sheng, Kiril Manevski, et al.
Hydrology and earth system sciences (2025) Vol. 29, Iss. 1, pp. 159-177
Open Access
Estimating global transpiration from TROPOMI SIF with angular normalization and separation for sunlit and shaded leaves
Zheng Chen, Shaoqiang Wang, Jing M. Chen, et al.
Remote Sensing of Environment (2025) Vol. 319, pp. 114586-114586
Closed Access
Multi-layer grid-scale soil moisture estimation using spatiotemporal deep learning methods with physical constraints
Tuantuan Zhang, Zhongmin Liang, Jianhong Zhou, et al.
Journal of Hydrology (2025), pp. 133086-133086
Closed Access
Enhancing runoff simulation by combining superflex with deep learning methods in China's Qinghai Lake Basin, Northeast Tibetan Plateau
Kaixun Liu, Na Li, Sihai Liang
Journal of Hydrology Regional Studies (2025) Vol. 59, pp. 102331-102331
Closed Access
Increased Compound Droughts and Heatwaves in a Double Pack in Central Asia
Chuan Wang, Zhi Li, Yaning Chen, et al.
Remote Sensing (2022) Vol. 14, Iss. 13, pp. 2959-2959
Open Access | Times Cited: 18
Estimating daily reference evapotranspiration using a novel hybrid deep learning model
Liwen Xing, Ningbo Cui, Li Guo, et al.
Journal of Hydrology (2022) Vol. 614, pp. 128567-128567
Closed Access | Times Cited: 17
LandBench 1.0: A benchmark dataset and evaluation metrics for data-driven land surface variables prediction
Qingliang Li, Cheng Zhang, Wei Shangguan, et al.
Expert Systems with Applications (2023) Vol. 243, pp. 122917-122917
Open Access | Times Cited: 10
Forecasting the potential of reclaimed water using signal decomposition and deep learning
Yinglong Chen, Hongling Zhang, Jingkai Peng, et al.
Journal of Water Process Engineering (2024) Vol. 65, pp. 105770-105770
Closed Access | Times Cited: 3
Estimation of global land surface evapotranspiration and its trend using a surface energy balance constrained deep learning model
Han Chen, A. Ghani Razaqpur, Yizhao Wei, et al.
Journal of Hydrology (2023) Vol. 627, pp. 130224-130224
Closed Access | Times Cited: 8
Evaluating data-driven and hybrid modeling of terrestrial actual evapotranspiration based on an automatic machine learning approach
Ning Guo, Hao Chen, Qiong Han, et al.
Journal of Hydrology (2023) Vol. 628, pp. 130594-130594
Closed Access | Times Cited: 7
Application and Uncertainty Analysis of Data-Driven and Process-Based Evapotranspiration Models Across Various Ecosystems
Qinghe Wang, Na Liu, Shunqing Zhong, et al.
Water Resources Management (2024) Vol. 38, Iss. 7, pp. 2359-2376
Closed Access | Times Cited: 2
Enhancing high-resolution reconstruction of flow fields using physics-informed diffusion model with probability flow sampling
Yanan Guo, Xiaoqun Cao, Mengge Zhou, et al.
Physics of Fluids (2024) Vol. 36, Iss. 11
Closed Access | Times Cited: 2
Hybrid residual deep learning models with physical knowledge for improving plant transpiration estimation
Binrui Liu, Xinguang He, Na Liu
Computers and Electronics in Agriculture (2023) Vol. 212, pp. 108135-108135
Closed Access | Times Cited: 4
Evaluating the ability of deep learning on actual daily evapotranspiration estimation over the heterogeneous surfaces
Jiaojiao Feng, Weizhen Wang, Feinan Xu, et al.
Agricultural Water Management (2023) Vol. 291, pp. 108627-108627
Open Access | Times Cited: 4
Integrating machine learning with analytical surface energy balance model improved terrestrial evaporation through biophysical regulation
Yun Bai, Kanishka Mallick, Tain Hu, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 1
Identification of Time-Varying Conceptual Hydrological Model Parameters with Differentiable Parameter Learning
Lian Xie, Xiaolong Hu, Liangsheng Shi, et al.
Water (2024) Vol. 16, Iss. 6, pp. 896-896
Open Access | Times Cited: 1
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