 |
Yiming Wang, Ph.D.
Postdoctoral Research Associate
USDA-ARS Hydrology and Remote Sensing Laboratory
Bldg. 007, Rm. 104, BARC-West
Beltsville, MD 20705-2350 USA
Voice: (301) 504-7490
Fax: (301) 504-8931
Yiming.Wang@usda.gov |
Research Interests:
- Water use estimation at city to basin scales: Investigating and estimating water use dynamics in cities and basins, exploring innovative methods to quantify and manage water resources sustainably.
- Environmental sustainability of water resources: Employing regional and global hydrological models to comprehend and enhance the environmental sustainability of water resources, contributing to a more resilient and ecologically balanced future.
- Thermal environments and vegetation phenology monitoring: Studying the dynamics of thermal environments and vegetation phenology at regional to global scales, aiming to understand the interplay between climate variations and ecological systems.
Education:
- 2015 B.S. (Geology) China University of Geosciences (Beijing), Beijing, China.
- 2018 M.S. (Electronics and Communication Engineering) Chinese Academy of Sciences University, Beijing, China.
- 2023 Ph.D. (Geology & Environmental Science) Iowa State University, Ames, Iowa.
Professional Experience:
- 2023 - present: Postdoctoral Researcher, USDA-ARS Hydrology and Remote Sensing Laboratory, Beltsville, MD.
Awards:
- 2023: Research Excellence (REX) Awards – Iowa State University
- 2023: John Lemish Graduate Research Award - Department of Geological and Atmospheric Sciences, Iowa State University
- 2022: Professional Development Grant - Environmental Science, Iowa State University
- 2021: Outstanding Contributions Award - Department of Geological and Atmospheric Sciences, Iowa State University
- 2013: Outstanding student leaders - China University of Geosciences (Beijing)
- 2012: Specialty Scholarship - China University of Geosciences (Beijing)
Publication Databases:
Selected Publications:
Wang, Yiming, et al. "Irrigation plays significantly different roles in influencing hydrological processes in two breadbasket regions." Science of The Total Environment 844 (2022): 157253. https://doi.org/10.1016/j.scitotenv.2022.157253
Meng, Lin, et al. "Artificial light at night: an under-appreciated effect on phenology of deciduous woody plants." PNAS Nexus (2022). https://doi.org/10.1093/pnasnexus/pgac046
Thompson, Jan, et al. "Iowa Urban FEWS: Integrating Social and Biophysical Models for Exploration of Urban Food, Energy, and Water Systems." Frontiers in big Data 4 (2021): 662186. https://doi.org/10.3389/fdata.2021.662186
Wang, Yiming, et al. "An agent-based framework for high-resolution modeling of domestic water use." Resources, Conservation and Recycling 169 (2021): 105520. https://doi.org/10.1016/j.resconrec.2021.105520
Cheng, Zhiqiang, et al. "Preliminary study of soil available nutrient simulation using a modified WOFOST model and time-series remote sensing observations." Remote Sensing 10.1 (2018): 64. https://doi.org/10.3390/rs10010064
Wang, Yiming, Meng Jihua, and Cheng Zhiqiang. "Data Assimilation Experiment of Poor Quality of Remote Sensing Images in Critical Phenology." Remote Sensing Technology and Application 32.4 (2017): 615-623.
Cheng, Zhiqiang, Jihua Meng, and Yiming Wang. "Improving spring maize yield estimation at field scale by assimilating time-series HJ-1 CCD data into the WOFOST model using a new method with fast algorithms." Remote Sensing 8.4 (2016): 303. https://doi.org/10.3390/rs8040303
