Articles from the center, those using its research, and faculty associated with the center.
Ghaneei, P., and H. Moradkhani (2025), DeepBase: A Deep Learning-based Daily Baseflow Dataset across the United States, Scientific Data, doi:10.1038/s41597-025-04389-y.
Razavi, S., A. Duffy, L. Eamen, A. Jakeman,…, and H. Moradkhani (2025), Convergent and transdisciplinary integration: On the future of integrated modeling of human-water systems, Water Resources Research, doi:10.1029/2024WR038088.
Foroumandi, E., H. Moradkhani, F.L. Ogden, and W. Krajewski (2025), Ensemble Data Assimilation for Operational Streamflow Predictions in the Next Generation (NextGen) Framework, Environmental Modeling and Software, doi:10.1016/j.envsoft.2024.106306.
Magliocca, N., R. Pathak, A. Price, H. Tanveer, and H. Moradkhani (2025), Increasing behavioral richness and managing structural uncertainty in social-ecological system agent-based models, Socio-Environmental Systems Modeling, 6, 18749, 2024, doi:10.18174/sesmo.18749.
Abbaszadeh, P., K. Gavahi, and H. Moradkhani (2024), Towards a Robust Hydrologic Data Assimilation System for Hurricane-induced River Flow Forecasting, Hydrology and Earth System Science Discussion, doi:10.5194/hess-2024-209.
Sattari, A., K. Gavahi, E. Foroumandi, and H. Moradkhani (2025), A Probabilistic Machine Learning Framework for daily Extreme Events Forecasting, Expert Systems with Applications, 265 (2025) 126004, doi:10.1016/j.eswa.2024.126004.
Boumis, G., H. Moftakhari, D. Lee and H. Moradkhani (2025), In search of non-stationary dependence between estuarine river discharge and storm surge based on large-scale climate teleconnections, Advances in Water Resources, doi:10.1016/j.advwatres.2024.104858.
Radfar, S., E. Foroumandi, H. Moftakhari, H. Moradkhani, G.R. Foltz, and A.S. Gupta (2025), Global predictability of marine heatwave induced rapid intensification of tropical cyclones, Earth’s Future, doi:10.1029/2024EF004935.
Xu, L., Y. Lv, and H. Moradkhani (2024), Daily multistep soil moisture forecasting by combining linear and nonlinear causality and attention-based encoder-decoder model, Stochastic Environmental Research and Risk Assessment, doi: 10.1007/s00477-024-02846-5
Ghaneei, P., E. Foroumandi, and H. Moradkhani (2024), Enhancing Streamflow Prediction in Ungauged Basins Using a Nonlinear Knowledge-Based Framework and Deep Learning, Water Resources Research, doi: 10.1029/2024WR037152.
Roy, A., H. Moradkhani, M. Mekonnen, H. Moftakhari, and N. Magliocca (2024), Towards strategic interventions for global food security in 2050, Science of The Total Environment, doi: 10.1016/j.scitotenv.2024.176811.
Zafarmomen, N., H. Alizadeh, M. Bayat, M. Ehtiat, and H. Moradkhani (2024), Assimilation of Sentinel-Based Leaf Area Index for Modeling Surface-Ground Water Interactions in Irrigation Districts, Water Resources Research, doi: 10.1029/2023WR036080.
Samadi, A., K. Jafarzadegan, and H. Moradkhani (2024), DEM-based Pluvial Flood Inundation Modeling at a Metropolitan Scale, Environmental Modelling & Software, doi: 10.1016/j.envsoft.2024.106226.
Sattari, A., K. Jafarzadegan, and H. Moradkhani (2024), Enhancing streamflow predictions with machine learning and Copula-Embedded Bayesian model averaging, Journal of Hydrology, doi: 10.1016/j.jhydrol.2024.131986.
Radfar, S., H. Moftakhari, and H. Moradkhani (2024), Rapid intensification of tropical cyclones in the Gulf of Mexico is more likely during marine heatwaves, Communications Earth & Environment, 5, 421, doi: 10.1038/s43247-024-01578-2.
