
Eunjin Han
Associate Research Scientist
Background
Eunjin is an Associate Research Scientist working on the integrations of advanced climate information, remote sensing data, and agro-hydrological models for crop yield predictions and climate risks assessment for informing decisions at the farm scale to the policy level. She received her Ph.D. degree in Civil Engineering from Purdue University. Before joining IRI, she worked at USDA-ARS Hydrology and Remote Sensing Lab focusing on improvement of a soil moisture data assimilation system for agricultural drought monitoring.
Under ACToday project, Eunjin has been contributing to development of agricultural decision/discussion support tools, adopting seasonal climate forecasts for enhanced agro-advisory system, and improving crop yield forecasting systems based on seasonal/subseasonal climate forecasts.
Research interests
- Integrations of advanced computational modeling (hydrologic and biophysical) techniques, climate information and remotely sensed observations for enhancing crop yield and hydrologic predictions.
- Translating seasonal and subseasonal climate information into agriculture-relevant terms for improving agricultural productivity and food security.
- Developing agro-advisory systems and agricultural decision support tools by linking seasonal/subseasonal climate forecasts with crop simulation models.
- Climate risk management at multiple spatial and temporal scales in agriculture and water resources.
Publications
Anderson, Weston B, E. Han, W. Baethgen, L. Goddard, Á.G. Muñoz, and A.W. Robertson, The Madden-Julian Oscillation Affects Maize Yields throughout the Tropics and Subtropics, Geophysical Research Letters (2020).
Han, Eunjin, A.V. Ines and J. Koo, Development of a 10-km resolution global soil profile dataset for crop modeling applications, Environmental Modeling & Software (2019). https://doi.org/10.1016/j.envsoft.2019.05.012
Han, Eunjin, et al. SIMAGRI: An agro-climate decision support tool, Computers and Electronics in Agriculture (2018). https://doi.org/10.1016/j.compag.2018.06.034
Han, Eunjin, A.V. Ines and W. Baethgen, Climate-Agriculture-Modeling and Decision Tool (CAMDT): A Software Framework for Climate Risk Management in Agriculture, Environmental Modeling & Software, 95, pp.102-114. (2017) https://doi.org/10.1016/j.envsoft.2017.06.024
Han, Eunjin and A.V. Ines, Downscaling Probabilistic Seasonal Climate Forecasts for Decision Support in Agriculture: A Comparison of Parametric and Non-parametric Approach, Climate Risk Management, 18, pp.51-65. (2017)https://doi.org/10.1016/j.crm.2017.09.003
Andreadis, Konstantinos, N. Das, D. Stampoulis, A.V. Ines, J. Fisher, S. Granger, J. Kawata, E. Han, and A. Behrangi, The Regional Hydrologic Extremes Assessment System: A software framework for hydrologic modeling and data assimilation, PLOS ONE 12.5 (2017) https://doi.org/10.1371/journal.pone.0176506
Crow, Wade, E. Han, D. Ryu, C.R. Hain and M.C. Anderson, Estimating annual water storage variations in medium-scale (2000 - 10,000km2) basins using microwave-based soil moisture retrievals, Hydrologic and Earth System Sciences, 21, pp.1849-1862. (2017) https://doi.org/10.5194/hess-21-1849-2017
Chinnachodteeranun, Rassarin, N. Hung, K. Honda, A.V. Ines, and E. Han, Designing and Implementing Weather Generators as Web Services, Future Internet, 8(4), 55 (2016) https://doi.org/10.3390/fi8040055
Capa-Morocho, Mirian, A.V. Ines, W. Baethgen, B. Rodriguez-Fonseca, E. Han and M. Ruiz-Ramosa, Crop yield outlooks in the Iberian Peninsula: Connecting Seasonal Climate Forecasts with Crop Simulation Models, Agricultural Systems, 149, pp.75-87. (2016) https://doi.org/10.1016/j.agsy.2016.08.008
Han, Eunjin, W.T. Crow, C.R. Hain and M.C. Anderson, On the Use of a Water Balance to Evaluate Inter-annual Terrestrial ET Variability, Journal of Hydrometeorology,16, pp.1102-1108. (2015) https://doi.org/10.1175/JHM-D-14-0175.1
Han, Eunjin, W. Crow, T. Holmes and J. Bolten, Benchmarking a Soil Moisture Data Assimilation System for Agricultural Drought Monitoring. Journal of Hydrometeorology, 15, pp.1117 - 1134. (2014) https://doi.org/10.1175/JHM-D-13-0125.1
Han, Eunjin, V. Merwade, G. Heathman and M. Cosh, Application of Observation Operators for Field-scale Soil Moisture Averages and Variances in Agricultural Landscapes, Journal of Hydrology, Vol. 444-445, pp. 34-50. (2012) https://doi.org/10.1016/j.jhydrol.2012.03.035
Han, Eunjin, V. Merwade and G. Heathman, Implementation of Surface Soil Moisture Data Assimilation with Watershed Scale Distributed Hydrologic Model, Journal of Hydrology, Vol. 416-417, pp. 98-117. (2012) https://doi.org/10.1016/j.jhydrol.2011.11.039
Han, Eunjin, V. Merwade and G. Heathman, Application of Data Assimilation with the Root Zone Water Quality Model for Soil Moisture Profile Estimation in the Upper Cedar Creek, Indiana, Hydrological Processes, 26, pp. 1707-1719. (2012) https://doi.org/10.1002/hyp.8292
Heathman, Gary, M. Cosh, E. Han, T. Jackson, L. McKee and S. McAfee, Field-scale Spatiotemporal Analysis of Surface Soil Moisture for Evaluating Point-scale in-situ Networks, Geoderma, Vol. 170, pp. 195-205. (2012) https://doi.org/10.1016/j.geoderma.2011.11.004
Heathman, Gary, M. Cosh, V. Merwade and E. Han, Multi-scale Temporal Stability Analysis of Surface and Subsurface Soil Moisture within the Upper Cedar Creek Watershed, Indiana, Catena, Vol. 95, pp. 91-103. (2012) https://doi.org/10.1016/j.catena.2012.03.008