Yeonuk Kim

Dr. Yeonuk Kim [he/him/his]

Assistant Research Professor, Hydrometeorology

E-Mail

Yeonuk.Kim@dri.edu

Campus

Reno Campus

Office

CRVB

Full Resume / CV

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Division

Hydrologic Sciences

Contact Card

Dr. Yeonuk Kim is an Assistant Research Professor of Hydrometeorology at the Desert Research Institute and a member of the OpenET technical team. His research focuses on satellite-based evapotranspiration modeling, landatmosphere interactions, and hydrological processes to improve water resource monitoring and management.

He joined DRI as a Sulo and Aileen Maki Postdoctoral Research Fellow and previously served as a Postdoctoral Research Fellow at the University of British Columbia (UBC). Dr. Kim received his Ph.D. from UBC, where he studied landatmosphere coupling and evapotranspiration dynamics using micrometeorological observations and remote sensing approaches.

He holds a Bachelor of Science in Agricultural Engineering from Seoul National University and previously worked at the National Centre for AgroMeteorology in South Korea.

Publications prior to DRI

Kim,Y.,Garca,M.,Black, T.A.&Johnson,M.S.(2023).Assessingthecomplementaryroleofsurfaceflux equilibrium (SFE) theory and maximum entropy production (MEP) principle in the estimation of actual evapotranspiration. Journal of Advances in Modeling Earth Systems. 15 (7). e2022MS003224.https://doi.org/10.1029/2022MS003224.
Kim,Y.,Garca,M.,&Johnson,M.S.(2023).Landatmospherecouplingconstrainsincreasestopotential evaporation in a warming climate: Implications at local and global scales. Earths Future. 11 (2). e2022EF002886. https://doi.org/10.1029/2022EF002886.
Kim,Y.,Morillas,L.,Garcia,M.,Weber,U.,Black,T.A.& Johnson,M.S.(2021). Relativehumiditygradients as a key constraint on terrestrial water and energy fluxes. Hydrology and Earth System Sciences. 25 (9), 5175- 5191. https://doi.org/10.5194/hess-25-5175-2021. EGU Highlight Paper
Kim,Y.,Johnson,M.S.,Knox,S.,Black,T.A.,Dalmagro,H.J.,Kang,M.,Kim,J.& Baldocchi,D.(2020).Gap- filling approaches for eddy covariance methane flux: a comparison of three machine learning algorithms and a traditional method with and without principal component analysis. Global Change Biology. 26 (3), 1499-1518. https://doi.org/10.1111/gcb.14845.
Kim,Y.,Talucder,M.S.A.,Kang,M.,Shim, K.-M.,Kang,N.& Kim,J.(2016).Interannualvariationsin methane emission from an irrigated rice paddy caused by rainfall during the aeration period. Agriculture, Ecosystems & Environment. 223, 67-75. https://doi.org/10.1016/j.agee.2016.02.032.
Choi,S.W.,Kim,H.,Kim,Y.,Kang,M.&Kim,J.(2016).Estimationandmappingofmethaneemissionfrom rice paddies in Gyunggi-do using the modified water management scaling factor. Korean Journal of Agricultural and Forest Meteorology. 18(4), 320-326. https://doi.org/10.5532/KJAFM.2016.18.4.320

Keywords

hydrometeorology, hydroclimatology, micrometeorology, ecohydrology, land-atmosphere interactions, evapotranspiration, satellite remote sensing, eddy covariance

Publications

2025

Kim, Y. & Johnson, M. (2025). Deciphering the role of evapotranspiration in declining relative humidity trends over land. Communications Earth & Environment, 6(1), 105. Nature Portfolio. https://doi.org/10.1038/s43247-025-02076-9

Kim, Y., Garcia, M., Andrew Black, T., & Johnson, M. (2025). Physically-constrained evapotranspiration models with machine learning parameterization outperform pure machine learning: Critical role of domain knowledge. PLOS ONE, 20(7), e0328798. Public Library of Science. https://doi.org/10.1371/journal.pone.0328798

Chignell, S., Kim, Y., & Johnson, M. (2025). Remote Sensing-Based Ecohydrogeological Characterisation and Perceptual Model of the Bale Mountains, Ethiopia. Hydrological Processes, 39(2), e70006. John Wiley & Sons, Ltd. https://doi.org/10.1002/hyp.70006

Riba, A., Garcia, M., Tarquís, A., Domingo, F., Antala, M., Feng, S., Liu, J., Johnson, M., Kim, Y., & Wang, S. (2025). Integrating Remotely Sensed Thermal Observations for Calibration of Process-Based Land-Surface Models: Accuracy, Revisit Windows, and Implications in a Dryland Ecosystem. Remote Sensing, 17(21), 3630. Multidisciplinary Digital Publishing Institute. https://doi.org/10.3390/rs17213630

Conference Proceedings

Kim, Y., Volk, J. M., Comini de Andrade, B., & Huntington, J. L. (2025). Inferring strong advection from surface flux equilibrium theory to diagnose surface energy balance. AGU Chapman Conference: Boulder, CO, September 15, 2025-September 19, 2025

Palou, R., Garcia, M., Tarquis, A., Oyonarte, C., Domingo, F., Liu, J., Johnson, M., Kim, Y., & Wang, S. (2025). Optimizing the revisiting frequency of remotely sensed thermal observations for continuous estimation of ecosystem evapotranspiration and productivity using Bayesian inference. EGU General Assembly: Vienna, Austria

Volk, J. M., Comini de Andrade, B., Kim, Y., Wang, T., Sueki, S., Huntington, J. L., Melton, F. S., Morton, C. G., Allen, R. G., Anderson, M., Fisher, J. B., Friedrichs, M., Jasoni, R. L., Kilic, A., Ruhoff, A., Senay, G. B., Halverson, G., Knipper, K., Minor, B. A., Pearson, C., Purdy, A. J., Yang, Y., French, A., Kustas, W. P., & Larsen, S. G. (2025). From Closure to Confidence: Using In Situ ET for Satellite Model Skill Assessment. AGU Chapman Conference: Boulder, CO, September 15, 2025-September 19, 2025

Kim, Y., Volk, J. M., Comini de Andrade, B., & Huntington, J. L. (2025). Inferring strong advection from surface flux equilibrium theory to diagnose surface energy balance. AGU Chapman Conference on the Energy Balance Closure Problem: Boulder, CO, September 15, 2025-September 19, 2025

Volk, J. M., Comini de Andrade, B., Kim, Y., Wang, T., Sueki, S., & Huntington, J. L. (2025). From Closure to Confidence: Using In Situ ET for Satellite Model Skill Assessment. AGU Chapman Conference on the Energy Balance Closure Problem: Boulder, CO, September 15, 2025-September 19, 2025