Matthew S. Horritt

Modeling large‐scale inundation of Amazonian seasonally flooded wetlands

This paper presents the first application and validation of a 2D hydrodynamic model of the Amazon at a large spatial scale. The simulation results suggest that a significantly higher proportion of total flow is routed through the floodplain than previously thought. We use the hydrodynamic model LISFLOOD-FP with topographic data from the Shuttle Radar Topography Mission to predict floodplain inundation for a 240 × 125 km section of the central Amazon floodplain in Brazil and compare our results to satellite-derived estimates of inundation extent, existing gauged data and satellite altimetry. We find that model accuracy is good at high water (72% spatial fit; 0.99 m root mean square error in water stage heights), while accuracy drops at low water (23%; 3.17 m) due to incomplete drainage of the floodplain resulting from errors in topographic data and omission of floodplain hydrologic processes from this initial model.

Waterline mapping in flooded vegetation from airborne SAR imagery

Multifrequency, polarimetric airborne synthetic aperture radar (SAR) survey of a salt marsh on the east coast of the UK is used to investigate the radar backscattering properties of emergent salt marsh vegetation. Two characteristics of flooded vegetation are observed: backscatter enhanced by approximately 1.2 dB at C-band, and 180° HH-VV phase differences at L-band. Both are indicative of a double bounce backscattering mechanism between the horizontal water surface and upright emergent vegetation. The mapping of inundated vegetation is demonstrated for both these signatures, using a statistical active contour model for the C-band enhanced backscatter, and median filtering and thresholding for the L-band HH-VV phase difference. The two techniques are validated against the waterline derived from tidal elevation measured at the time of overpass intersected with an intertidal DEM derived from airborne laser altimetry. The inclusion of flooded vegetation is found to reduce errors in waterline location by a factor of approximately 2, equivalent to a reduction in waterline location error from 120 to 70 m. The DEM is also used to derive SAR waterline heights, which are observed to underpredict the tidal elevation due to the effects of vegetation. The underprediction can be corrected for vegetation effects using canopy height maps derived from the laser altimetry. This third technique is found to improve the systematic error in waterline heights from 20 to 4 cm, but little improvement in random error is evident, chiefly due to significant noise in the vegetation height map.

Improving River Flood Extent Delineation From Synthetic Aperture Radar Using Airborne Laser Altimetry

Flood extent maps that are derived from synthetic aperture radar (SAR) images provide spatially distributed data for validating hydraulic models of river flood flow. The accuracy of such maps is reduced by a number of factors, including variation in backscatter from the different land cover types that are adjacent to the flood, changes in returns from the water surface that are caused by different meteorological conditions, and the presence of emergent vegetation. This paper describes how improved accuracy can be achieved by modifying an existing flood extent delineation algorithm to use airborne laser altimetry [light detection and ranging (lidar)] as well as SAR data. The lidar data provide an additional constraint that water line heights should vary smoothly along the flooded reach. The method was tested on a SAR image of a flood for which contemporaneous aerial photography existed, together with lidar data of the un flooded reach. The water line heights of the SAR flood extent that was conditioned on both SAR and lidar data matched the corresponding heights from the aerial photograph water line significantly more closely than those from the SAR flood extent that was conditioned only on SAR data. For water line heights in areas of low slope and vegetation, the root-mean-square error on the height differences reduced from 221.1 cm for the latter case to 55.5 cm for the former.

Obtaining accurate maps of topography and vegetation to improve 2D hydraulic flood models

Airborne scanning laser altimetry (LiDAR) is an important new data source for environmental applications, mapping topographic and surface object heights to high vertical and spatial accuracy over large areas. We present results of a segmentation system for LiDAR data for a reach of the river Severn, UK. The system has been developed to improve the 3 main data required by a leading numerical flood model predicting inundation extent, namely (i) a map of topographic height providing model bathymetry. A comparison with ground control points gives an accuracy of ±17cm (decreasing in the presence of steeply wooded slopes), (ii) the meandering location of the river channel and a suitable height contour which denote the extent of the model domain, and allow immediate finite element mesh generation, and (iii) a map of vegetation height (to an accuracy of ±14cm for grass and cereal crops) which is converted to friction coefficients. Errors due to overlapping swaths are significantly reduced. A 3-class segmentation of vegetation types (short, intermediate and tall) allows optimal height extraction algorithms to be separately applied, and enables realistic conversion to friction coefficients. Short (grass and cereal crops) and intermediate (hedges) vegetation are assumed to be flexible and either emergent or submerged during a flood cycle. Trees (tall vegetation) are modelled as rigid, emergent, stems.

Using airborne laser altimetry to improve river flood extents delineated from SAR data

Flood extent maps derived from SAR images are a useful source of data for validating hydraulic models of river flood flow. The accuracy of such maps is reduced by a number of factors, including changes in returns from the water surface caused by different meteorological conditions and the presence of emergent vegetation. The paper describes how improved accuracy can be achieved by modifying an existing flood extent delineation algorithm to use airborne laser altimetry (LiDAR) as well as SAR data. The LiDAR data provide an additional constraint that waterline (land-water boundary) heights should vary smoothly along the flooded reach. The method was tested on a SAR image of a flood for which contemporaneous aerial photography existed, together with LiDAR data of the un-flooded reach. Waterline heights of the SAR flood extent conditioned on both SAR and LiDAR data matched the corresponding heights from the aerial photo waterline significantly more closely than those from the SAR flood extent conditioned only on SAR data.