Yuan QIU
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Mail code: 7904Campus: Otheraz
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I am a research scientist in Dr. Jay Famiglietti's group. Before that, I was a postdoc in Dr. Guo-Yue Niu and Ali Behrangi's group in the Department of Hydrology and Atmospheric Sciences at the University of Arizona. Funded by the Arizona Water Innovation Initiative, my colleagues and I are developing an integrated modeling framework to project future water supply and demand for Arizona. I am also involved in the ATUR project, which aims to capture and enhance recharge in Arizona. I am interested in hydrological modeling and sub-seasonal to seasonal (S2S) prediction. My current scientific questions are 1) How does precipitation intensity affect groundwater recharge in arid and semi-arid regions? (paper) 2) How will Arizona's water supply and water demand change in a warmer future? 3) How can S2S prediction be improved by introducing land memory?
- Ph.D., September 2012 – June 2018; Cartography and Geography Information System; University of Chinese Academy of Sciences.
- B.S., September 2008 – June 2012; Cartography and Geography Information System; North China University of Water Resources and Electric Power.
Hydrological modeling; Sub-seasonal to seasonal (S2S) prediction
Jay Famiglietti's Group
- Qiu, Y., Famiglietti, J. S., Behrangi, A., Farmani, M. A., Yousefi Sohi, H., Gupta, A., Hung F., Abdelmohsen K., Niu G.: The strong impact of precipitation intensity on groundwater recharge and terrestrial water storage change in Arizona, a typical dryland. Geophysical Research Letters, https://doi.org/10.1029/ 2025GL114747, 2025.
- Qiu Y., Feng J., Wang J., Xue Y., and Xu Z.: Memory of land surface and subsurface temperature (LST/SUBT) initial anomalies over Tibetan Plateau in different land models, Climate Dynamics, 10.1007/s00382-021-05937-z, 2021.
- Qiu Y., Feng J., Yan Z., Wang J., and Li Z.: High-resolution dynamical downscaling for regional climate projection in Central Asia based on bias-corrected multiple GCMs, Climate Dynamics, 58, 777-791, 10.1007/s00382-021-05934-2, 2021.
- Qiu Y., Yan Z., Feng J., Hua L., Fan L., Li Z., Wang J., and Qian C.: Robust historical and future drying trends in Central Asia evidenced by the latest observation and modeling datasets, Atmospheric Research, https://doi.org/10.1016/j.atmosres.2023.107033, 2023.
- Qiu Y., Feng J., Yan Z., and Wang J.: Assessing the Land-Use Harmonization (LUH) 2 dataset in Central Asia for regional climate model projection, Environmental Research Letters, 10.1088/1748-9326/accfb2, 2023.
Funded by the Arizona Water Innovation Initiative, my colleagues and I are developing an integrated modeling framework—combining Noah-MP, RAPID, CRSS, and ParFlow—to project future water supply and demand for Arizona. I am also involved in the ATUR project, which aims to capture and enhance recharge in Arizona.
- July 2024 – present: Associate Research Professional; School of Sustainability, Arizona State University; Tempe, AZ, USA.
- August 2023 – July 2024: Postdoctoral Research Associate; Department of Hydrology and Atmospheric Sciences, University of Arizona; Tucson, AZ, USA.
- January 2019 – July 2023: Postdoctoral Research Associate; Institute of Atmospheric Physics, Chinese Academy of Sciences; Beijing, China.
- July 2018 – December 2018: Data Engineer; GAGO Inc.; Beijing, China.