Universität Bonn

IGG | APMG

de

Dr. Fupeng Li

Scientific Staff Member

fupeng.jpeg
© 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. 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

DLR-WIKI

NCN-DFG

Geodetic Earth Observation.
Satellite Geodesy and Earth System.

  • 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. Li, F., Springer, A., Kusche, J., Gutknecht, B., Ewerdwalbesloh, Y. (2025). Reanalysis and Forecasting of Total Water Storage and Hydrological States by Combining Machine Learning With CLM Model Simulations and GRACE Data Assimilation. Water Resources Research, e2024WR037926, https://doi.org/10.1029/2024WR037926 .

  2. Liu, C., Wang, Z., Li, F., Gao, Y., & Xiao, Y. (2025). Efficient Solutions for Forward Modeling of the Earth's Topographic Potential in Spheroidal Harmonics. Surveys in Geophysics, 46(1), 169-196. https://doi.org/10.1007/s10712-024-09871-7. 

  3. Li, F., Kusche, J., Sneeuw, N., Siebert, S., Gerdener, H., Wang, Z., ... & Tian, ​​K. (2024). Forecasting next year's global land water storage using GRACE data. Geophysical Research Letters, 51(17), e2024GL109101. https://doi.org/10.1029/2024GL109101.

  4. Yin, J., Slater, LJ, 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.

  5. 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.

  6. 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.

  7. 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.

  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, PJF (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., Holes, 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. Li, Fupeng. (2021): Data from: Long-term (1979-present) total water storage anomalies over the global land derived by reconstructing GRACE data [Dataset]. Dryad. https://doi.org/10.5061/dryad.z612jm6bt. 

  12. 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.

  13. 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.

  14. Li, F & Rietbroek R. (2020): strawpants/twsc_recon: Software tools for the accepted WRR paper (Fupeng Li et al 2020). Zenodo. https://doi.org/10.5281/zenodo.3690609. 

  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.

Contact

Avatar Li

Fupeng Li Dr.

+49 228 73-3577

2.008

Nußallee 17

© Li | IGG