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Dr. Fupeng Li

Scientific staff member

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© Li

Biography

Dr. Fupeng Li joined the Institute for Geodesy and Geoinformation (IGG), Astronomical, Physical and mathematical Geodesy Group at the University of Bonn, in April 2021, as a postdoc researcher. Before joining the University of Bonn, Dr. Fupeng Li studied at the Information Engineering University (China, 2013-2016) and Wuhan University (China, 2016-2020). He earned the Ph.D. degree in Geodesy and Geomatics Engineering (2020) at Wuhan University. His main research interest focuses on the application of machine learning techniques in Geodetic and Hydrological studies, including reconstruction/prediction of the GRACE/-FO total water storage changes, drought forecasting, and GRACE/-FO data assimilation.

  • Ph.D.
  • M.Sc.
  • B.Sc.
  • Since Apr. 2021 Postdoctoral researcher at the Institute of Geodesy and Geoinformation, University of Bonn, Germany.
  • 2016 – 2020 Ph.D. candidate at the School of Geodesy and Geomatics, Wuhan University, China.
  • 2018 – 2019 Visiting Ph.D. student at the Institute of Geodesy and Geoinformation, University of Bonn, Germany.
  • 2013 – 2016 M. Eng. at the School of Navigation and Aerospace Engineering, Information Engineering University, China.
  • 2009 – 2013 B. Eng. at the College of Geomatics, Shandong University of Science and Technology, China.
  • Reconstruction and prediction of the GRACE total water storage changes.
  • Assimilation of GRACE data into hydrological models.
  • Forecasting climate extremes
  • 2020 The Academic Innovation Award of Wuhan University.
  • 2020 The Sino-German (CSC-DAAD) Postdoc Scholarship.
  • 2018 Li Qinghai Surveying and Mapping Scholarship for Outstanding Students of Wuhan University.

  1. Hu Y., Chao N., Yang Y., Wang J., Yin W., Xie J., Duan G., Zhang M., Wan X., Li, F., et al. Integrating GRACE/GRACE Follow-On and Wells Data to Detect Groundwater Storage Recovery at a Small-Scale in Beijing Using Deep Learning. Remote Sensing. 2023; 15(24):5692. https://doi.org/10.3390/rs15245692.

  2. Yin, J., Slater, L. J., Khouakhi, A., Yu, L., Liu, P., Li, F., Pokhrel, Y., and Gentine, P. (2023): GTWS-MLrec: global terrestrial water storage reconstruction by machine learning from 1940 to present, Earth Syst. Sci. Data, 15, 5597–5615, https://doi.org/10.5194/essd-15-5597-2023.

  3. Li, X., Jin, T., Liu, B., Chao, N., Li, F., & Cai, Z. (2023). The influence of ENSO on the long-term water storage anomalies in the Middle-Lower reaches of the Yangtze River basin: Evaluation and analysis. Earth and Space Science, 10, e2023EA003007. https://doi.org/10.1029/2023EA003007.

  4. Wan, X., You, W., Kusche, J., Li, F., Yang, X., Fan, D., ... & Jiang, Z. (2023). Evaluating different predictive strategies for filling the global GRACE/-FO terrestrial water storage anomalies gap. Journal of Hydrology, 626, 130216. https://doi.org/10.1016/j.jhydrol.2023.130216.

  5. Chao, N., Wan, X., Zhong, Y., Yin, W., Yue, L., Li, F., et al. (2023) Reconstructing a new terrestrial water storage deficit index to detect and quantify drought in the Yangtze River Basin. Journal of Hydrology, 625, 129972. https://doi.org/10.1016/j.jhydrol.2023.129972.

  6. Chao, N., Wang, J., Yue, L., Yeh, P. J. F., Hu, Y., Wan, X., Li. F, et al. (2023) Multi-Lagrange multiplier method to improve the region-specific GRACE estimation of water storage change in eleven sub-basins of the Yangtze River. Journal of Hydrology: Regional Studies, 47, 101426. https://doi.org/10.1016/j.ejrh.2023.101426.

  7. Yue, L., Chao, N., Chen, G., Chen, L., Zhang, B., Sun, R., Zhang Y, Wang S., Wang Z., Li, F., Yu N., Ouyang G.. (2023). Reconstructing continuous ice sheet elevation changes in the Amundsen Sea sector during 2003–2021 by merging Envisat, ICESat, CryoSat-2, and ICESat-2 multi-altimeter observations. Journal of Geophysical Research: Earth Surface, 128, e2022JF007020. https://doi.org/10.1029/2022JF007020.

  8. Zhang, Y., Chao, N., Li, F., Yue, L., Wang, S., Chen, G., ... & Ouyang, G. (2023). Reconstructing Long-Term Arctic Sea Ice Freeboard, Thickness, and Volume Changes from Envisat, CryoSat-2, and ICESat-2. Journal of Marine Science and Engineering, 11(5), 979. https://doi.org/10.3390/jmse11050979.

  9. Chao, N., Li, F., Yu, N., Chen, G., Wang, Z., Ouyang, G., Yeh, P. J. F. (2023) Divergent spatiotemporal variability of terrestrial water storage and eight hydroclimatic components over three different scales of the Yangtze River basin. Science of The Total Environment, 879, 162886. https://doi.org/10.1016/j.scitotenv.2023.162886.

  10. Li, F., Kusche, J., Chao, N., Wang, Z., Löcher, A. (2021). Long-term (1979-present) total water storage anomalies over the global land derived by reconstructing GRACE data. Geophysical Research Letters, 48, e2021GL093492. doi.org/10.1029/2021GL093492.

  11. Tian, K., Wang, Z., Li, F., Gao, Y., Liu, C. (2021). Drought events over the amazon river basin (1993–2019) as detected by the climate-driven total water storage change. Remote Sensing, 13(6), 1124. doi.org/10.3390/rs13061124.

  12. Li, F., Kusche, J., Rietbroek, R., Wang, Z., Forootan, E., Schulze, K., Lück, C. (2020) Comparison of Data-driven Techniques to Reconstruct (1992-2002) and Predict (2017-2018) GRACE-like Gridded Total Water Storage Changes using Climate Inputs. Water Resources Research, 56, e2019WR026551, doi.org/10.1029/2019WR026551.

  13. Li, F., Zhengtao, W., Nengfang, C., Jiandi, F., Bingbing, Z., Tian., K., Han, Y. (2020) 2015/2016 drought event in the Amazon River basin as measured by Swarm constellation [J]. Geomatics and Information Science of Wuhan University (In Chinese) 45(4): 595-602.

  14. Chao, N., Chen, G., Luo, Z., Sun, X., Wang, Z., Li, F. (2019) Detecting Water Diversion Fingerprints in the Danjiangkou Reservoir from Satellite Gravimetry and Altimetry Data. Sensors, 19(16), 3510. https://doi.org/10.3390/s19163510.

  15. Li, F., Wang, Z., Chao, N., Song, Q. (2018) Assessing the Influence of the Three Gorges Dam on Hydrological Drought Using GRACE Data[J]. Water, 10(5):669, doi.org/10.3390/w10050669.

  16. Li, F., Zhang, C., Wang, Z., Zhan, Y. (2017) Designation of Astronomical/GNSS Orientation System [J]. Journal of Geomatics (In Chinese), 2017(5):25-28.

  17. Qiu, Y., Wang, Z., Jiang, W., Zhang, B., Li, F., Guo, F. (2017). Combining champ and swarm satellite data to invert the lithospheric magnetic field in the tibetan plateau. Sensors, 17(2), 238-. doi.org/10.3390/s17020238.

  18. Zhang, B., Wang, Z., Zhou, L., Feng, J., Qiu, Y., Li, F. (2017). Precise orbit solution for swarm using space-borne gps data and optimized pseudo-stochastic pulses. Sensors, 17(3). doi.org/10.3390/s17030635.

  19. Li, F., Zhang, C., Li, C., Zhou P. (2016) An approach of improving the real-time of precise point positioning [J]. Engineering of Surveying and Mapping (In Chinese), 25(9):63-67.

  20. Li, F., Zhang, C. (2015) Analyzing the Precision of Precise Point Positioning by Using the Ultrafast Ephemeris [J]. GNSS World of China (In Chinese), 2015(6):64-67.

Contact

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Fupeng Li

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+49 228 73-3577

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