-
Hamed Moftakhari
The University of AlabamaMeeting roles in:
A Modular Game-Based Learning Platform for Advancing Coastal Resilience Education in K–12 and Undergraduate Classrooms
Enhanced Cumulative Likelihood of Potential Impacts using synthetic tropical cyclones for coastal flooding, a case study applied to Mobile, Alabama
Spatial Delineation of the Compound Flood Transition Zone Using DeepLearning
Bridging Return Period Gaps in Flood Inundation Mapping Using a Hybrid Deep Learning Approach
A Comparative Analysis of Operational Multi-Method Flood Inundation Mapping: Quantifying Fidelity–Accuracy Tradeoffs
GEE-FMF: A Google Earth Engine-Based Machine Learning Framework for Efficient Regional Flood Mapping
Advancing Physics-Informed Compound Flood Modeling through a Newton-Guided Deep Learning Model
Enhancing Compound Flood Forecasting Mapping Through Multi-Model Atmospheric Forcing and Machine Learning-Based Boundary Conditions
Coastal Hydrology: Observation, Modeling, and Prediction of Surface and Subsurface Processes and Patterns I Poster
Flood Inundation and Suspended Sediment Flux Projections Indicate Significant Toxic Metal Inputs in the NE Gulf of Mexico as a Result of Hurricane Impacts
Simplified Urban Risk of Flooding (SURF) Estimation due to Reduced Capacity under Compound Flooding
Coastal Hydrology: Observation, Modeling, and Prediction of Surface and Subsurface Processes and Patterns II Oral
The Coastal Coupling Community of Practice: Contributing to the Modeling Community
Coastal Hydrology: Observation, Modeling, and Prediction of Surface and Subsurface Processes and Patterns III Oral
Assessing Future Storm Surge Hazards on U.S. Coasts Through Statistical Downscaling of Climate Projections
Estimating Fine Resolution Local Sea Level Scaling Factors Using Ensemble Deep Learning
Standardizing Performance Evaluation for Compound Flooding: Challenges and Recommendations
Understanding Simulation Uncertainty in Compound Floods: Sensitivity to Forcing and Model Parameters
An Integrated Framework Towards Strengthening Transportation Infrastructure Resilience to Compound Flooding Impacts
GEE-FMF: A Google Earth Engine-Based Machine Learning Framework for Efficient Regional Flood Mapping
Enter Note
Go to previous page in this tab
Author/Chair
