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- W1489420712 abstract "Improvements in the resolution of satellite imagery have enabled extraction of water surface elevations at themargins of the flood. Comparison between modelled and observed water surface elevations provides a newmeans for calibrating and validating flood inundation models, however the uncertainty in this observed data hasyet to be addressed. Here a flood inundation model is calibrated using a probabilistic treatment of the observed data.A LiDAR guided snake algorithm is used to determine an outline of a flood event in 2006 on the RiverDee, North Wales, UK, using a 12.5m ERS-1 image. Points at approximately 100m intervals along this outline areselected, and the water surface elevation recorded as the LiDAR DEM elevation at each point.With a planar water surface from the gauged upstream to downstream water elevations as an approximation,the water surface elevations at points along this flooded extent are compared to their ‘expected’ value. Thepattern of errors between the two show a roughly normal distribution, however when plotted against coordinatesthere is obvious spatial autocorrelation. The source of this spatial dependency is investigated by comparing errorsto the slope gradient and aspect of the LiDAR DEM.A LISFLOOD-FP model of the flood event is set-up to investigate the effect of observed data uncertaintyon the calibration of flood inundation models. Multiple simulations are run using different combinations offriction parameters, from which the optimum parameter set will be selected. For each simulation a T-test is used toquantify the fit between modelled and observed water surface elevations. The points chosen for use in this T-testare selected based on their error. The criteria for selection enables evaluation of the sensitivity of the choice ofoptimum parameter set to uncertainty in the observed data.This work explores the observed data in detail and highlights possible causes of error. The identification ofsignificant error (RMSE = 0.8m) between approximate expected and actual observed elevations from the remotelysensed data emphasises the limitations of using this data in a deterministic manner within the calibration process.These limitations are addressed by developing a new probabilistic approach to using the observed data." @default.
- W1489420712 created "2016-06-24" @default.
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- W1489420712 date "2010-05-01" @default.
- W1489420712 modified "2023-09-23" @default.
- W1489420712 title "Calibrating flood inundation models: identifying and addressing uncertainty in satellite observed flood extents" @default.
- W1489420712 hasPublicationYear "2010" @default.
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