CV

Education

Ph.D in Meteorology, The Pennsylvania State University, 2012
B.S. in Atmospheric Sciences, Peking University, 2007

Work experience

Research Assistant Professor: July 2018 – now
- Department of Ecosystem Science and Management, Penn State University
Research Associate: October 2014 – July 2018
- Department of Ecosystem Science and Management, Penn State University
Postdoctoral Researcher: October 2012 – September 2014
- Earth and Environmental Systems Institute, Penn State University

Publications

Kemanian, A. R., Y. Shi, C. M. White, F. Montes, C. O. Stöckle, D. R. Huggins, M. L. Cangiano, G. Stefani-Faé, and R. K. N. Rozum, 2024: The Cycles agroecosystem model: Fundamentals, testing, and applications. Computers and Electronics in Agriculture, 227, 109510. doi:10.1016/j.compag.2024.109510.

Kodero, J., B. Felzer, and Y. Shi, 2024: Future transition from forests to shrublands and grasslands in the western United States is expected to reduce carbon storage. Communications Earth & Environment, 5, 78. doi:10.1038/s43247-024-01253-6.

Weng, W., K. M. Cobourn, A. R. Kemanian, K. J. Boyle, Y. Shi, J. Stachelek, and C. White, 2023: Quantifying co-benefits of water quality policies: an integrated assessment model of land and nitrogen management. American Journal of Agricultural Economics, 1–26. doi:10.1111/ajae.12423.

Shi, Y., F. Montes, and A. R. Kemanian, 2023: Cycles-L: A coupled, 3-D, land surface, hydrologic, and agroecosystem landscape model. Water Resources Research, e2022WR033453. doi:10.1029/2022WR033453.

McConnell, C. A., R. K. N. Rozum, Y. Shi, and A. R. Kemanian, 2023: Tradeoffs when interseeding cover crops into corn across the Chesapeake Bay watershed. Agricultural Systems, 209, 103684. doi:10.1016/j.agsy.2023.103684.

Kopp, M., J. Kaye, Y. H. Smeglin, T. Adams, E. J. Primka IV, B. Bradley, Y. Shi, and D. Eissenstat, 2022: Topography mediates the response of soil CO₂ efflux to precipitation over days, seasons, and years. Ecosystems, . doi:10.1007/s10021-022-00786-1.

Novick, K. A., D. L. Ficklin, D. Baldocchi, K. J. Davis, T. A. Ghezzehei, A. G. Konings, N. MacBean, N. Raoult, R. L. Scott, Y. Shi, B. N. Sulman, and J. D. Wood, 2022: Confronting the water potential information gap. Nature Geoscience, 15, 158–164. doi:10.1038/s41561-022-00909-2.

Zhi, W., Y. Shi, H. Wen, L. Saberi, G.-H. C. Ng, K. Sadayappan, D. Kerins, B. Stewart, and L. Li, 2022: BioRT-Flux-PIHM v1.0: a biogeochemical reactive transport model at the watershed scale. Geoscientific Model Development, 15, 315–333. doi:10.5194/gmd-15-315-2022.

Gil, Y., D. Garijo, D. Khider, C. A. Knoblock, V. Ratnakar, M. Osorio, H. Vargas, M. Pham, J. Pujara, B. Shbita, B. Vu, Y.-Y. Chiang, D. Feldman, Y. Lin, H. Song, V. Kumar, A. Khandelwal, M. Steinbach, K. Tayal, S. Xu, S. A. Pierce, L. Pearson, D. Hardesty-Lewis, E. Deelman, R. F. Da Silva, R. Mayani, A. R. Kemanian, Y. Shi, L. Leonard, S. Peckham, M. Stoica, K. Cobourn, Z. Zhang, C. Duffy, and L. Shu, 2021: Artificial intelligence for modeling complex systems: Taming the complexity of expert models to improve decision making. ACM Transactions on Interactive Intelligent Systems, 11, 1–49. doi:10.1145/3453172.

Wlostowski A. N., N. Molotch, S. P. Anderson, S. L. Brantley, J. Chorover, D. Dralle, P. Kumar, L. Li, K. A. Lohse, J. M. Mallard, J. C. McIntosh, S. F. Murphy, E. Parrish, M. Safeeq, M. Seyfried, Y. Shi, and C. Harman, 2021: Signatures of hydrologic function across the critical zone observatory network. Water Resources Research, 57, e2019WR026635. doi:10.1029/2019WR026635.

He, Y., K. J. Davis, Y. Shi, D. M. Eissenstat, J. Kaye, and M. Kaye, 2020: Observing and simulating spatial variations of forest carbon stocks in complex terrain. Journal of Geophysical Research: Biogeosciences, 125, e2019JG005160. doi:10.1029/2019JG005160.

Da Silva, R. F., R. Mayani, Y. Shi, A. R. Kemanian, M. Rynge and E. Deelman, 2019: Empowering agroecosystem modeling with HTC scientific workflows: The Cycles model use case. 2019 IEEE International Conference on Big Data (Big Data), 4545–4552. doi:10.1109/BigData47090.2019.9006107.

Kaye, J. P., S. L. Brantley, J. Z. Williams, and the SSHCZO team, 2019: Ideas and perspectives: Proposed best practices for collaboration at cross-disciplinary observatories. Biogeosciences, 16, 4661–4669. doi:10.5194/bg-16-4661-2019.

Xiao, D., Y. Shi, S. Brantley, B. Forsythe, R. DiBiase, K. Davis, and L. Li, 2019: Streamflow generation from catchments of contrasting lithologies: The role of soil properties, topography, and catchment size. Water Resources Research, 55, 9234–9257. doi:10.1029/2018WR023736.

Sullivan, P. L., Y. Godderis, Y. Shi, X. Gu, J. Schott, E. A. Hasenmueller, J. Kaye, C. Duffy, L. Jin, and S. L. Brantley, 2019: Exploring the effect of aspect to inform future earthcasts of climate-driven changes in weathering of shale. Journal of Geophysical Research: Earth Surface, 124, 974–993. doi:10.1029/2017JF004556.

Pravia, M., A. R. Kemanian, J. A. Terra, Y. Shi, I. Macedo, and S. Goslee, 2019: Soil carbon saturation, productivity, and carbon and nitrogen cycling in crop-pasture rotations. Agricultural Systems, 171, 13–22. doi:10.1016/j.agsy.2018.11.001.

Crow, W. T., S. Milak, M. Moghaddam, A. Tabatabaeenejad, S.Jaruwatanadilok, X. Yu, Y. Shi, R. H. Reichle, Y. Hagimoto, and R. H. Cuenca, 2018: Spatial and temporal variability of root-zone soil moisture acquired from hydrologic modeling and AirMOSS P-band radar. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11, 4578–4590. doi:10.1109/JSTARS.2018.2865251.

Brantley, S. L., T. White, N. West, J. Z. Williams, B. Forsythe, D. Shapich, J. Kaye, H. Lin, Y. Shi, M. Kaye, E. Herndon, K. J. Davis, Y. He, D. Eissenstat, J. Weitzman, R. DiBiase, L. Li, W. Reed, K. Brubaker, and X. Gu, 2018: Susquehanna Shale Hills Critical Zone Observatory: Shale Hills in the context of Shaver's Creek watershed. Vadose Zone Journal, 17, 180092. doi:10.2136/vzj2018.04.0092.

Shi, Y., D. M. Eissenstat, Y. He, and K. J. Davis, 2018: Using a spatially-distributed hydrologic biogeochemistry model with a nitrogen transport module to study the spatial variation of carbon processes in a Critical Zone Observatory. Ecological Modelling, 380, 8–21. doi:10.1016/j.ecolmodel.2018.04.007.

Li, L., C. Bao, P. L. Sullivan, S. Brantley, Y. Shi, and C. Duffy, 2017: Understanding watershed hydrogeochemistry: 2. Synchronized hydrological and geochemical processes drive stream chemostatic behavior. Water Resources Research, 53, 2346–2367. doi:10.1002/2016WR018935.

Bao, C., L. Li, Y. Shi, and C. Duffy, 2017: Understanding watershed hydrogeochemistry: 1. Development of RT‐Flux‐PIHM. Water Resources Research, 53, 2328–2345. doi:10.1002/2016WR018934.

Yu, X., C. Duffy, Y. Zhang, G. Bhatt, and Y. Shi, 2016: Virtual experiments guide calibration strategies for a real-world watershed application of coupled surface-subsurface modeling. Journal of Hydrologic Engineering, 21, 1055779. doi:10.1061/(ASCE)HE.1943-5584.0001431.

Jepsen, S. M., T. C. Harmon, and Y. Shi, 2016: Watershed model calibration to the base flow recession curve with and without evapotranspiration effects. Water Resources Research, 52, 2919–2933. doi:10.1002/2015WR017827.

Brantley, S. L., R. A. DiBiase, T. A. Russo, Y. Shi, H. Lin, K. J. Davis, M. Kaye, L. Hill, J. Kaye, D. M. Eissenstat, B. Hoagland, A. L. Dere, A. L. Neal, K. M. Brubaker, and D. K. Arthur, 2016: Designing a suite of measurements to understand the critical zone. Earth Surface Dynamics, 4, 211–235. doi:10.5194/esurf-4-211-2016.

Shi, Y., D. C. Baldwin, K. J. Davis, X. Yu, C. J. Duffy, and H. Lin, 2015: Simulating high‐resolution soil moisture patterns in the Shale Hills watershed using a land surface hydrologic model. Hydrological Processes, 29, 4624–4637. doi:10.1002/hyp.10593.

Shi, Y., K. J. Davis, F. Zhang, C. J. Duffy, and X. Yu, 2015: Parameter estimation of a physically-based land surface hydrologic model using an ensemble Kalman filter: A multivariate real-data experiment. Advances in Water Resources, 83, 421–427. doi:10.1016/j.advwatres.2015.06.009.

Yu, X., C. Duffy, J. Kaye, W. Crow, G. Bhatt, and Y. Shi, 2014: Watershed reanalysis of water and carbon cycle models at a Critical Zone Observatory. Remote Sensing of the Terrestrial Water Cycle, in Remote Sensing of the Terrestrial Water Cycle (eds. Lakshmi, V. et al.), John Wiley & Sons, Inc., Hoboken, New Jersey. doi:10.1002/9781118872086.ch31.

Duffy, C., Y. Shi, K. Davis, R. Slingerland, L. Li, P. L. Sullivan, Y. Goddéris, and S. L. Brantley,, 2014: Designing a suite of models to explore critical zone function. Procedia Earth and Planetary Science, 10, 7–15. doi:10.1016/j.proeps.2014.08.003.

Shi, Y., K. J. Davis, F. Zhang, and C. J. Duffy, 2014: Evaluation of the parameter sensitivities of a coupled land surface hydrologic model at a critical zone observatory. Journal of Hydrometeorology, 15, 279–299. doi:10.1175/JHM-D-12-0177.1.

Shi, Y., K. J. Davis, F. Zhang, C. J. Duffy, and X. Yu, 2014: Parameter estimation of a physically based land surface hydrologic model using the ensemble Kalman filter: A synthetic experiment. Water Resources Research, 50, 706–724. doi:10.1002/2013WR014070.

Shi, Y., K. J. Davis, C. J. Duffy, and X. Yu, 2013: Development of a coupled land surface hydrologic model and evaluation at a critical zone observatory. Journal of Hydrometeorology, 14, 1401–1420. doi:10.1175/JHM-D-12-0145.1.

Yu, X., G. Bhatt, C. Duffy, and Y. Shi, 2013: Parameterization for distributed watershed modeling using national data and evolutionary algorithm. Computers & Geosciences, 58, 80–90. doi:10.1016/j.cageo.2013.04.025.

Xu, Y., S. Liu, F. Hu, N. Ma, Y. Wang, Y. Shi, and H. Jia, 2009: Influence of Beijing urbanization on the characteristics of atmospheric boundary layer. Chinese Journal of Atmospheric Sciences (in Chinese), 33, 859–867. doi:10.3878/j.issn.1006-9895.2009.04.18.

Talks

Towards an agricultural resilience kit: Food production in the shadow of nuclear soot

May 22, 2024

Invited talk at Engaging Communities in Developing Technologies for Community Flourishing Workshop, Bethlehem, PA

Hydrobiogeochemical data assimilation using ensemble-based simultaneous state and parameter estimation

January 09, 2018

Invited talk at AMS 98th Annual Meeting, Austin, TX

Using a spatially-distributed hydrologic biogeochemistry model with nitrogen transport to study the spatial variation of carbon stocks and fluxes in a Critical Zone Observatory

December 11, 2017

Talk at 2017 AGU Fall Meeting, New Orleans, LA

Towards improved high-resolution land surface hydrologic reanalysis using a physically-based land surface hydrologic model and data assimilation

May 23, 2016

Invited talk at Symposium on Advanced Assimilation and Uncertainty Quantification in Big Data Research for Weather, Climate and Earth System Monitoring and Prediction , State College, PA