Sources of uncertainty in flood inundation maps

Bales, Jerad D.; Wagner, Chad R.

doi:10.1111/j.1753-318x.2009.01029.x

Cited by 112 publications

(78 citation statements)

References 23 publications

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“…However, calibration using these data is not the most desirable approach because distributed model performance cannot be tested and stream gauge data can be affected by an error even more than 20% during extreme floods (Bales and Wagner, 2009). Recently a number of authors have therefore used spatial information about the extent of the inundation area derived form post-event flood line surveys, aerial photos, satellite or airborne radar imagery (SAR) data, or LIDAR survey (Hunter et al, 2007) for calibration.…”

Section: Model Performance Evaluationmentioning

confidence: 99%

Towards automatic calibration of 2-D flood propagation models

Fabio

Aronica

Apel

2010

Hydrol. Earth Syst. Sci.

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Abstract. Hydraulic models for flood propagation description are an essential tool in many fields and are used, for example, for flood hazard and risk assessments, evaluation of flood control measures, etc. Nowadays there are many models of different complexity regarding the mathematical foundation and spatial dimensions available, and most of them are comparatively easy to operate due to sophisticated tools for model setup and control. However, the calibration of these models is still underdeveloped in contrast to other models like e.g. hydrological models or models used in ecosystem analysis. This has two primary reasons: first, lack of relevant data against which the models can be calibrated, because flood events are very rarely monitored due to the disturbances inflicted by them and the lack of appropriate measuring equipment in place. Second, 2-D models are computationally very demanding and therefore the use of available sophisticated automatic calibration procedures is restricted in many cases. This study takes a well documented flood event in August 2002 at the Mulde River in Germany as an example and investigates the most appropriate calibration strategy for a simplified 2-D hyperbolic finite element model. The model independent optimiser PEST, that enables automatic calibrations without changing model code, is used and the model is calibrated against over 380 surveyed maximum water levels. The application of the parallel version of the optimiser showed that (a) it is possible to use automatic calibration in combination of 2-D hydraulic model, and (b) equifinality of Correspondence to: P. Fabio (fabio@idra.unipa.it) model parameterisation can also be caused by a too large number of degrees of freedom in the calibration data in contrast to a too simple model setup. In order to improve model calibration and reduce equifinality, a method was developed to identify calibration data, resp. model setup with likely errors that obstruct model calibration.

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Section: Model Performance Evaluationmentioning

confidence: 99%

Towards automatic calibration of 2-D flood propagation models

Fabio

Aronica

Apel

2010

Hydrol. Earth Syst. Sci.

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“…In addition to the horizontal resolution, vertical accuracy of DEM used in this study has the root mean square error of 2.44 m. This vertical error can directly be propagated to uncertainty in obtaining water surface elevation. Furthermore, it incorporates the uncertainties in the generation of the flood inundation area [39][40][41].…”

Section: Spatial Resolution Of the Satellite Images And Demmentioning

confidence: 99%

Simplified Flood Inundation Mapping Based On Flood Elevation-Discharge Rating Curves Using Satellite Images in Gauged Watersheds

Jung

Kim

et al. 2014

Water

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Abstract:This study suggests an approach to obtain flood extent boundaries using spatial analysis based on Landsat-5 Thematic Mapper imageries and the digital elevation model. The suggested approach firstly extracts the flood inundation areas using the ISODATA image-processing algorithm from four Landsat 5TM imageries. Then, the ground elevations at the intersections of the extracted flood extent boundaries and the specified river cross sections are read from the digital elevation to estimate the elevation-discharge relationship. Lastly, the flood extent is generated based on the estimated elevation-discharge relationship. The methodology was tested over two river reaches in Indiana, United States. The estimated elevation-discharge relationship showed a good match with the correlation coefficients varying between 0.82 and 0.99. In addition, self-validation was also performed for the estimated spatial extent of the flood by comparing it to the waterbody extracted from the Landsat images used to develop the elevation-discharge relationship. The result indicated that the match between the estimated and the extracted flood extents was better with higher flood magnitude. We expect that the suggested methodology will help under-developed and OPEN ACCESSWater 2014, 6 1281 developing countries to obtain flood maps, which have difficulties getting flood maps through traditional approaches based on computer modeling.

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“…Generally when hydraulic models are used to develop inundation maps, the largest source of uncertainty is associated with the terrain data (Bales and Wagner, 2009;Merwade and others, 2008;Werner, 2001). However, provided the methods used in this particular study, a greater source of error may be related to the interpolation of the water-surface elevation between HWMs.…”

Section: Uncertainty In Flood-peak Inundation Mapsmentioning

confidence: 99%