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The accuracy of the flood extent mapping shows a kappa value of 0.82.
This interaction results in floods of diverse characteristics, e.g. spatial flood extent and temporal flood progression.
Ground data include in situ observations of vegetation structure and flood extent as well as water level records.
Validation of stage and discharge predictions builds confidence in model predictions of flood extent and localized velocities, which are fundamental to reliable flash flood warning.
Furthermore, hydraulic models outperform equilibrium flood mapping methodologies which ignore hydraulic connectivity and are strongly biased towards over-prediction of flood extent.
Image analysis demonstrates that temporal variations of the radar backscatter can be used to monitor efficiently the flood extent regardless of the landscape units.
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This event was chosen as air photo and Synthetic Aperture Radar (SAR) data for flood inundation extent are available to enable rigorous validation of the developed model.
Additionally, HEC-RAS model generated flood inundation extents are used to validate the model performance at fifteen sites that lack FEMA maps.
On average, the error of predicted flood extents is around 14% across the CONUS.
Simply knowing whether the margin of error in mapped flood extents is a big or little number would help.
'Recorded Flood Outlines', May 2017 version, contains actual flood extents continuously recorded since 1946, with a limited number of events from earlier years as well77.
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