Articles from the center, those using its research, and faculty associated with the center.
Dey, H., W. Shao, H. Moradkhani, B. Keim, and B. Peter (2024), Urban Flood Susceptibility Mapping Using Frequency Ratio and Multiple Decision Tree‑based Machine Learning Models, Natural Hazards, doi:10.1007/s11069-024-06609-x
Boumis, G., H. Moftakhari, and H. Moradkhani (2024), A MetastatisticalFrequency Analysis of Extreme Storm Surge Hazard Along the US Coastline, Coastal Engineering Journal, doi:10.1080/21664250.2024.2338323
Moftakhari, H., D. F. Muñoz, A. Akbari Asanjan, A. Aghakouchak, H. Moradkhani, and D. A. Jay (2024), Nonlinear Interactions of Sea-Level Rise and Storm Tide Alter Extreme Coastal Water Levels: How and Why?, AGU Advances, doi:10.1029/2023AV000996
Gomez, FJ., K. Jafarzadegan, H. Moftakhari, and H. Moradkhani (2024), Probabilistic Flood Inundation Mapping through Copula Bayesian Multi-Modelling of Precipitation Products, Natural Hazards and Earth System Sciences, doi:10.5194/nhess-2024-26
Muñoz, D., H. Moftakhari, and H. Moradkhani (2024), Quantifying Cascading Uncertainty in Compound Flood Modeling with Linked Process-based and Machine Learning Models, Hydrology and Earth System Sciences, doi:10.5194/hess-2024-9
Rashid, M., H. Moftakhari, and H. Moradkhani (2024), Stochastic Simulation of Storm Surge Extremes Along the Contiguous United States Coastlines Using the Max-stable Process, Communications Earth & Environment, doi:10.1038/s43247-024-01206-z
Tripathy, S., K. Jafarzadegan, H. Moftakhari, and H. Moradkhani (2024), Dynamic Bivariate Hazard Forecasting of Hurricanes for Improved Disaster Preparedness, Communications Earth & Environment, doi:10.1038/s43247-023-01198-2
Oruc, N., K. Jafarzadegan, and H. Moradkhani (2024), Improving flood inundation modeling skill: interconnection between model parameters and boundary conditions, Modeling Earth Systems and Environment, doi: 10.1007/s40808-023-01768-5
Zhang, B., S. Wang, J. Zscheischler, and H. Moradkhani (2023), Higher Exposure of Poorer People to Emerging Weather Whiplash in a Warmer World, Geophysical Research Letters, doi:10.1029/2023GL105640
Sohrabi, M., H. Moftakhari, and H. Moradkhani (2023), Efficient Tropical Cyclone Scenario Selection Based on Cumulative Likelihood of Potential Impacts, Earth’s Future, doi:10.1029/2023EF003731
Foroumandi, E., H. Moradkhani, X. Sanchez-Vila, K. Singha, A. Castelletti, and G. Destouni (2023), ChatGPT in Hydrology and Earth Sciences: Opportunities, Prospects, and Concerns, Water Resources Research, doi:10.1029/2023WR036288
Boumis, G., H. Moftakhari, and H. Moradkhani (2023), Storm surge hazard estimation along the US Gulf Coast: A Bayesian hierarchical approach, Coastal Engineering, doi:10.1016/j.coastaleng.2023.104371
Gavahi, K., E. Foroumandi, and H. Moradkhani (2023), A deep learning-based framework for multi-source precipitation fusion, Remote Sensing of Environment, doi:10.1016/j.rse.2023.113723
Yarveysi, F., A. Alipour, H. Moftakhari, K. Jafarzadegan, and H. Moradkhani (2023), Block-level vulnerability assessment reveals disproportionate impacts of natural hazards across the conterminous United States, Nature Communications, doi:10.1007/s11625-023-01298-0
Boumis, G., H. Moftakhari, and H. Moradkhani (2023), Coevolution of Extreme Sea Levels and Sea-Level Rise Under Global Warming, Earth’s Future, doi:10.1007/s11625-023-01298-0
