The use of remotely sensed land cover to derive floodplain friction coefficients for flood inundation modelling
Wilson, M.D. and Atkinson, P.M. (2007) The use of remotely sensed land cover to derive floodplain friction coefficients for flood inundation modelling. Hydrological Processes, 21, 3576-3586. (doi:10.1002/hyp.6584).
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Remotely sensed land cover was used to generate spatially-distributed friction coefficients for use in a two-dimensional model
of flood inundation. Such models are at the forefront of research into the prediction of river flooding. Standard practice,
however, is to use single (static) friction coefficients on both the channel and floodplain, which are varied in a calibration
procedure to provide a “best fit” to a known inundation extent. Spatially-distributed friction provides a physically grounded
estimate of friction that does not require fitting to a known inundation extent, but which can be fitted if desired. Remote
sensing offers the opportunity to map these friction coefficients relatively straightforwardly and for low cost. Inundation was
predicted using the LISFLOOD-FP model for a reach on the River Nene, UK. Friction coefficients were produced from land
cover predicted from Landsat TM imagery using both ML and fuzzy c-means classifiction. The elevetion data used were
from combined contour and differential global positioning system (GPS) elevation data. Predicted inundation using spatiallydistributed
and static friction were compared. Spatially-distributed friction had the greatest effect on the timing of flood
inundation, but a small effect on predicted inundation extent. The results indicate that spatially-distributed friction should be
considered where the timing of initial flooding (e.g. for early warning) is important.
|Keywords:||floodplain friction coefficients; remote sensing; flood inundation modelling|
|Subjects:||G Geography. Anthropology. Recreation > G Geography (General)
G Geography. Anthropology. Recreation > GE Environmental Sciences
G Geography. Anthropology. Recreation > GB Physical geography
|Divisions:||University Structure - Pre August 2011 > School of Geography > Remote Sensing and Spatial Analysis
|Date Deposited:||01 Aug 2008|
|Last Modified:||27 Mar 2014 18:37|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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