Is this project an undergraduate, graduate, or faculty project?
Graduate
Project Type
individual
Campus
Daytona Beach
Authors' Class Standing
Keenan Hubbard, Graduate Student
Lead Presenter's Name
Keenan Hubbard
Lead Presenter's College
DB College of Engineering
Faculty Mentor Name
Stephen Medeiros
Abstract
Flooding dynamics in floodplains can be complex, with hysteresis potentially influencing the temporal relationship between river gage readings and the extent of floodwaters. This study uses Sentinel-1 SAR imagery to map floods in the Lake floodplains in the Middle St. John's River and investigates the potential presence of hysteresis during flood events. SAR scenes, each corresponding to analogous river gage readings, are analyzed—from a receding flood and from a rising flood. By comparing the resulting flood maps, we evaluate how the flooded area differs at each stage of the flood event. This research aims to contribute to flood monitoring systems by improving flood extent mapping during both rising and falling water levels, which is critical for accurate flood forecasting and response planning.
Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, Collaborative, Climbing, or Ignite Grants) from the Office of Undergraduate Research?
No
Mapping Inundation Extent in Middle St. Johns Lakes Floodplains Using SAR Data: Investigating Stage-Area Hysteresis in Flood Dynamics
Flooding dynamics in floodplains can be complex, with hysteresis potentially influencing the temporal relationship between river gage readings and the extent of floodwaters. This study uses Sentinel-1 SAR imagery to map floods in the Lake floodplains in the Middle St. John's River and investigates the potential presence of hysteresis during flood events. SAR scenes, each corresponding to analogous river gage readings, are analyzed—from a receding flood and from a rising flood. By comparing the resulting flood maps, we evaluate how the flooded area differs at each stage of the flood event. This research aims to contribute to flood monitoring systems by improving flood extent mapping during both rising and falling water levels, which is critical for accurate flood forecasting and response planning.