Yueling Ma

1.5k total citations · 1 hit paper
19 papers, 921 citations indexed

About

Yueling Ma is a scholar working on Environmental Engineering, Water Science and Technology and Health, Toxicology and Mutagenesis. According to data from OpenAlex, Yueling Ma has authored 19 papers receiving a total of 921 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Environmental Engineering, 8 papers in Water Science and Technology and 7 papers in Health, Toxicology and Mutagenesis. Recurrent topics in Yueling Ma's work include Hydrology and Watershed Management Studies (8 papers), Air Quality and Health Impacts (6 papers) and Hydrological Forecasting Using AI (4 papers). Yueling Ma is often cited by papers focused on Hydrology and Watershed Management Studies (8 papers), Air Quality and Health Impacts (6 papers) and Hydrological Forecasting Using AI (4 papers). Yueling Ma collaborates with scholars based in China, United States and Germany. Yueling Ma's co-authors include Jingping Niu, Jiangtao Liu, Xiaotao He, Bin Luo, Shihua Fu, Ji Zhou, Jun Yan, Bo Wang, Ya-Dong Zhao and Stefan Kollet and has published in prestigious journals such as The Science of The Total Environment, Environmental Pollution and Chemosphere.

In The Last Decade

Yueling Ma

17 papers receiving 906 citations

Hit Papers

Effects of temperature variation and humidity on the deat... 2020 2026 2022 2024 2020 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yueling Ma China 10 463 400 300 258 125 19 921
Wei Tu United States 13 298 0.6× 249 0.6× 231 0.8× 154 0.6× 110 0.9× 31 791
Liane Yuri Kondo Nakada Brazil 9 160 0.3× 518 1.3× 163 0.5× 412 1.6× 55 0.4× 13 810
Xiaotao He China 9 808 1.7× 605 1.5× 512 1.7× 372 1.4× 191 1.5× 11 1.3k
Ya-Dong Zhao China 11 439 0.9× 333 0.8× 283 0.9× 341 1.3× 117 0.9× 13 986
Yongjian Zhu China 9 798 1.7× 941 2.4× 535 1.8× 625 2.4× 175 1.4× 15 1.6k
Liqing Cao China 5 319 0.7× 590 1.5× 217 0.7× 488 1.9× 64 0.5× 9 912
Yumiao Zhang China 13 259 0.6× 113 0.3× 179 0.6× 143 0.6× 81 0.6× 28 711
Shihua Fu China 6 808 1.7× 598 1.5× 507 1.7× 286 1.1× 191 1.5× 6 1.2k
Rodrigo Custódio Urban Brazil 8 138 0.3× 534 1.3× 167 0.6× 390 1.5× 20 0.2× 23 807
M. Benjamin Sabath United States 12 342 0.7× 617 1.5× 190 0.6× 1.4k 5.3× 88 0.7× 13 1.9k

Countries citing papers authored by Yueling Ma

Since Specialization
Citations

This map shows the geographic impact of Yueling Ma's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yueling Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yueling Ma more than expected).

Fields of papers citing papers by Yueling Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yueling Ma. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yueling Ma. The network helps show where Yueling Ma may publish in the future.

Co-authorship network of co-authors of Yueling Ma

This figure shows the co-authorship network connecting the top 25 collaborators of Yueling Ma. A scholar is included among the top collaborators of Yueling Ma based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yueling Ma. Yueling Ma is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
1.
Ma, Yueling, et al.. (2026). High resolution US water table depth estimates reveal quantity of accessible groundwater. Communications Earth & Environment. 7(1).
3.
Bennett, Andrew, Hoang Tran, Yueling Ma, et al.. (2024). Spatio‐Temporal Machine Learning for Regional to Continental Scale Terrestrial Hydrology. Journal of Advances in Modeling Earth Systems. 16(6). 8 indexed citations
4.
Ma, Yueling, et al.. (2024). Perceived Social Support and Presenteeism Among Nurses. JONA The Journal of Nursing Administration. 54(9). 495–502. 2 indexed citations
5.
Ma, Yueling, Julian Koch, & R. M. Maxwell. (2024). Using random forests to explore the feasibility of groundwater knowledge transfer between the contiguous US and Denmark. Environmental Research Communications. 6(12). 121005–121005.
6.
Naz, Bibi S., Wendy Sharples, Yueling Ma, Klaus Goergen, & Stefan Kollet. (2023). Continental-scale evaluation of a fully distributed coupled land surface and groundwater model, ParFlow-CLM (v3.6.0), over Europe. Geoscientific model development. 16(6). 1617–1639. 24 indexed citations
7.
Ma, Yueling, et al.. (2023). Water Table Depth Estimates over the Contiguous United States Using a Random Forest Model. Ground Water. 62(1). 34–43. 10 indexed citations
8.
Ma, Yueling, Carsten Montzka, Bibi S. Naz, & Stefan Kollet. (2022). Advancing AI-based pan-European groundwater monitoring. Environmental Research Letters. 17(11). 114037–114037. 8 indexed citations
9.
Ma, Yueling, Carsten Montzka, Bagher Bayat, & Stefan Kollet. (2021). Using Long Short-Term Memory networks to connect water table depth anomalies to precipitation anomalies over Europe. Hydrology and earth system sciences. 25(6). 3555–3575. 20 indexed citations
10.
Ma, Yueling, Carsten Montzka, Bagher Bayat, & Stefan Kollet. (2021). An Indirect Approach Based on Long Short-Term Memory Networks to Estimate Groundwater Table Depth Anomalies Across Europe With an Application for Drought Analysis. Frontiers in Water. 3. 6 indexed citations
11.
Ma, Yueling, Ya-Dong Zhao, Jiangtao Liu, et al.. (2020). Effects of temperature variation and humidity on the death of COVID-19 in Wuhan, China. The Science of The Total Environment. 724. 138226–138226. 659 indexed citations breakdown →
12.
Li, Lanyu, Aimin Yang, Xiaotao He, et al.. (2020). Corrigendum:“Indoor air pollution from solid fuels and hypertension: A systematic review and meta-analysis” [Environ. Pollut. 259(2020) 113914]. Environmental Pollution. 266(Pt 1). 115085–115085. 4 indexed citations
13.
Yang, Aimin, Xiaotao He, Jiangtao Liu, et al.. (2020). Indoor air pollution from solid fuels and hypertension: A systematic review and meta-analysis. Environmental Pollution. 259. 113914–113914. 61 indexed citations
14.
Ma, Yueling, Yue Li, Jiangtao Liu, et al.. (2020). Association of air pollution with outpatient visits for respiratory diseases of children in an ex-heavily polluted Northwestern city, China. BMC Public Health. 20(1). 816–816. 28 indexed citations
15.
Fu, Shihua, Bo Wang, Ji Zhou, et al.. (2020). Meteorological factors, governmental responses and COVID-19: Evidence from four European countries. Environmental Research. 194. 110596–110596. 33 indexed citations
16.
He, Xiaotao, Guangqiang Zhou, Yueling Ma, et al.. (2020). Winter vacation, indoor air pollution and respiratory health among rural college students: A case study in Gansu Province, China. Building and Environment. 188. 107481–107481. 17 indexed citations
17.
Liu, Jiangtao, Ye Ruan, Qi Wu, et al.. (2019). Has the mortality risk declined after the improvement of air quality in an ex-heavily polluted Chinese city-Lanzhou?. Chemosphere. 242. 125196–125196. 25 indexed citations
18.
Liu, Jiangtao, Yueling Ma, Yuhong Wang, et al.. (2019). The Impact of Cold and Heat on Years of Life Lost in a Northwestern Chinese City with Temperate Continental Climate. International Journal of Environmental Research and Public Health. 16(19). 3529–3529. 10 indexed citations
19.
Ma, Yueling, et al.. (2019). CAN MACHINE LEARNING IMPROVE THE ACCURACY OF WATER LEVEL FORECASTS FOR INLAND NAVIGATION? CASE STUDY: RHINE RIVER BASIN, GERMANY. Proceedings of the IAHR World Congress. 38. 1979–1989. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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