Flood Inundation Modeling and Mapping: Application of Hydrodynamic Models, Remote Sensing and Machine Learning Tools
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".
Deadline for manuscript submissions: 30 April 2025 | Viewed by 35
Special Issue Editors
Interests: hydrology; floodplain hydraulics; inundation mapping; inundation modeling; water resources assessment; hydrological connectivity; linking hydrology and ecology
Special Issues, Collections and Topics in MDPI journals
Interests: mapping and monitoring of surface water dynamics using remote sensing; multi-temporal image analysis for environmental applications; synthetic aperture radar applications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
It is widely recognized that floods are one of the deadliest natural disasters on earth. Improved knowledge of flood frequency, duration, and inundation is a prerequisite for disaster management, infrastructure development, and environmental integrity. With recent advancements in computational methods and computing facilities, flood indicators are now estimated more accurately and efficiently.
We invite original research articles that contribute to the continuing efforts to understand complex hydrological and hydraulic processes and accurately estimate the frequency, duration, inundation areas, and wetland connectivity of floods. This Special Issue also welcomes manuscripts on uncertainty analysis and the application of flood modeling to support decision making.
The topics for this Special Issue include but are not limited to the following:
- Flood frequency analysis: advances in methods, regional case studies, variability, and trend analysis;
- Inundation modeling: advances in computational methods and computing facilities, comparison between methods and models;
- Inundation mapping: advances in remote sensing techniques, strengths/limitations of satellite data (e.g., Landsat, Sentinel-2, Synthetic Aperture Radar);
- The integration of remote sensing and hydrodynamic modeling;
- Machine learning tools for flood inundation modeling;
- The robustness of machine learning algorithms for generating flood informatics;
- The application of GIS and machine learning to predict flood inundation;
- The application of AI for flood risk assessment;
- Flood hazard assessments and risk mapping;
- The impacts of climate change on floods’ magnitude and frequency;
- The impacts of infrastructure development on flood inundation;
- Sea level rise and coastal flooding;
- Uncertainty in flood modeling.
Dr. Fazlul Karim
Dr. Catherine Ticehurst
Guest Editors
Manuscript Submission Information
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Keywords
- hydrology
- flood frequency
- hydrodynamic modeling
- remote sensing
- machine learning
- satellite imagery
- SRTM
- LiDAR
- Sentinel-1
- Sentinel-2
- Landsat
- floods
- inundation
- flood risk
- uncertainty analysis
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