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:

Detection of extreme hydrological droughts in the poyang lake basin during 2021–2022 using GNSS-derived daily terrestrial water storage anomalies
Yujie Peng, Gang Chen, Nengfang Chao, et al.
The Science of The Total Environment (2024) Vol. 919, pp. 170875-170875
Closed Access | Times Cited: 16

Showing 16 citing articles:

The dominant role of human activity intensity in spatial pattern of ecosystem health in the Poyang Lake ecological economic zone
Qing Lu, Fan Huanhuan, Zhang Fuqing, et al.
Ecological Indicators (2024) Vol. 166, pp. 112347-112347
Open Access | Times Cited: 9

Unveiling the hidden dynamics of intermittent surface water: A remote sensing framework
Zhen Xiao, Runkui Li, Mingjun Ding, et al.
Remote Sensing of Environment (2024) Vol. 311, pp. 114285-114285
Closed Access | Times Cited: 5

Spatiotemporal variations of water levels and river-lake interaction in the Poyang Lake basin under the extreme drought
Hexiang Chen, Guangqiu Jin, Hongwu Tang, et al.
Journal of Hydrology Regional Studies (2025) Vol. 57, pp. 102165-102165
Closed Access

Spatiotemporally non-stationary evolution of groundwater levels in Poyang Lake Basin driven by meteorological and hydrological factors
Yu Liu, Chengpeng Lu, Baozhong Qiu, et al.
The Science of The Total Environment (2024) Vol. 950, pp. 175244-175244
Closed Access | Times Cited: 3

Attribution of hydrological droughts in large river-connected lakes: Insights from an explainable machine learning model
Chenyang Xue, Qi Zhang, Yuxue Jia, et al.
The Science of The Total Environment (2024) Vol. 952, pp. 175999-175999
Closed Access | Times Cited: 2

Detecting the extreme hydrological events over China in 2022 using sparse GNSS and GRACE/GRACE-FO
Ze Wang, Weiping Jiang, Jian Wang, et al.
Remote Sensing of Environment (2024) Vol. 315, pp. 114488-114488
Closed Access

Using hydrological modeling and satellite observations to elucidate subsurface and surface hydrological responses to the extreme drought
Zixuan Tang, Yongqiang Zhang, Jing Tian, et al.
Journal of Hydrology (2024), pp. 132174-132174
Closed Access

Distinctive water bodies surrounding lakes: An effective indicator for drought monitoring and assessment
Zhen Zhang, Bingsun Chen, Junjie Li, et al.
Journal of Hydrology (2024), pp. 132179-132179
Closed Access

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