Dr. Xinyang Fan
Dr. Xinyang Fan
GeoZentrum Nordbayern
Professur für Angewandte Geologie und Modellierung von Umweltsystemen
Erlangen
- Telefon: -
- E-Mail: xinyang.fan@fau.de
Research interests
- Hydrological modelling
- Groundwater hydrology
- Alpine hydrology
- Stable water isotopes
Education:
03/2019 – 06/2023 | Joint PhD degree in Environmental Engineering, The University of Melbourne, Australia, and Karlsruhe Institute of Technology, Germany | Thesis: Quantifying the impact of climate variability and change on groundwater
10/2015 – 08/2018 | Master degree in Environmental Sciences, University of Cologne, Germany | Thesis: Electrical resistivity tomography and CMD-Explorer applications to investigate a waste deposit in Longerich, Cologne
09/2012 – 01/2013 | Exchange semester in the Department of Biological Science and Technology, I-Shou University, Taiwan
09/2011 – 06/2015 | Bachelor degree in Ecology, Ocean University of China
Professional Career:
10/2023 – today | Postdoc at University of Bern, Switzerland, and FAU, Germany | Research project: Sensitivity of high Alpine geosystems to climate change since c. 1850 (SEHAG), Hydrology Unit
Key publications:
1) Fan X., Peterson T., Henley B., Arora M. (2023), Groundwater sensitivity to climate variations in Australia. Water Resources Research, 59, https://doi.org/10.1029/2023WR035036.
2) Fan X., Goeppert N., Goldscheider, N. (2023), Quantifying the historic and future response of karst spring discharge to climate variability and change at a snow-influenced temperate catchment in central Europe. Hydrogeology Journal, 31, 2213–2229, https://doi.org/10.1007/s10040-023-02703-9.
2025
- Ji, H., Chiogna, G., Richieri, B., Fan, X., Huang, K., Chen, C.,... Zhao, H. (2025). High-frequency dual-tracer approach to identify contaminant transport pathways and quantify migration behaviors in karst underground river system. Journal of Hydrology, 662. https://doi.org/10.1016/j.jhydrol.2025.133935
2024
- Collenteur, R.A., Haaf, E., Bakker, M., Liesch, T., Wunsch, A., Soonthornrangsan, J.,... Meysami, R. (2024). Data-driven modelling of hydraulic-head time series: results and lessons learned from the 2022 Groundwater Time Series Modelling Challenge. Hydrology and Earth System Sciences, 28(23), 5193-5208. https://doi.org/10.5194/hess-28-5193-2024
Es wurden leider keine Projekte gefunden.