Floodplain friction parameterization in two‐dimensional river flood models using vegetation heights derived from airborne scanning laser altimetry

Two‐dimensional (2‐D) hydraulic models are currently at the forefront of research into river flood inundation prediction. Airborne scanning laser altimetry is an important new data source that can provide such models with spatially distributed floodplain topography together with vegetation heights for parameterization of model friction. The paper investigates how vegetation height data can be used to realize the currently unexploited potential of 2‐D flood models to specify a friction factor at each node of the finite element model mesh. The only vegetation attribute required in the estimation of floodplain node friction factors is vegetation height. Different sets of flow resistance equations are used to model channel sediment, short vegetation, and tall and intermediate vegetation. The scheme was tested in a modelling study of a flood event that occurred on the River Severn, UK, in October 1998. A synthetic aperture radar image acquired during the flood provided an observed flood extent against which to validate the predicted extent. The modelled flood extent using variable friction was found to agree with the observed extent almost everywhere within the model domain. The variable‐friction model has the considerable advantage that it makes unnecessary the unphysical fitting of floodplain and channel friction factors required in the traditional approach to model calibration. Copyright © 2003 John Wiley & Sons, Ltd.     

Predicting floodplain inundation: raster‐based modelling versus the finite‐element approach

We compare two approaches to modelling floodplain inundation: a raster‐based approach, which uses a relatively simple process representation, with channel flows being resolved separately from the floodplain using either a kinematic or diffusive wave approximation, and a finite‐element hydraulic model aiming to solve the full two‐dimensional shallow‐water equations. A flood event on a short (c. 4 km) reach of the upper River Thames in the UK is simulated, the models being validated against inundation extent as determined from satellite synthetic aperture radar (SAR) imagery. The unconstrained friction parameters are found through a calibration procedure, where a measure of fit between predicted and observed shorelines is maximized. The raster and finite‐element models offer similar levels of performance, both classifying approximately 84% of the model domain correctly, compared with 65% for a simple planar prediction of water surface elevation. Further discrimination between models is not possible given the errors in the validation data. The simple raster‐based model is shown to have considerable advantages in terms of producing a straightforward calibration process, and being robust with respect to channel specification. Copyright © 2001 John Wiley & Sons, Ltd.     

Urban fluvial flood modelling using a two‐dimensional diffusion‐wave treatment,part 1: mesh resolution effects

High‐resolution data obtained from airborne remote sensing is increasing opportunities for representation of small‐scale structural elements (e.g. walls, buildings) in complex floodplain systems using two‐dimensional (2D) models of flood inundation. At the same time, 2D inundation models have been developed and shown to provide good predictions of flood inundation extent, with respect to both full solution of the depth‐averaged Navier–Stokes equations and simplified diffusion‐wave models. However, these models have yet to be applied extensively to urban areas. This paper applies a 2D raster‐based diffusion‐wave model to determine patterns of fluvial flood inundation in urban areas using high‐resolution topographic data and explores the effects of spatial resolution upon estimated inundation extent and flow routing process. Model response shows that even relatively small changes in model resolution have considerable effects on the predicted inundation extent and the timing of flood inundation. Timing sensitivity would be expected, given the relatively poor representation of inertial processes in a diffusion‐wave model. Sensitivity to inundation extent is more surprising, but is associated with: (1) the smoothing effect of mesh coarsening upon input topographical data; (2) poorer representation of both cell blockage and surface routing processes as the mesh is coarsened, where the flow routing is especially complex; and (3) the effects of (1) and (2) upon water levels and velocities, which in turn determine which parts of the floodplain the flow can actually travel to. It is shown that the combined effects of wetting and roughness parameters can compensate in part for a coarser mesh resolution. However, the coarser the resolution, the poorer the ability to control the inundation process, as these parameters not only affect the speed, but also the direction of wetting. Thus, high‐resolution data will need to be coupled to a more sophisticated representation of the inundation process in order to obtain effective predictions of flood inundation extent. This is explored in a companion paper. Copyright © 2005 John Wiley & Sons, Ltd.     

A comparison of one‐ and two‐dimensional approaches to modelling flood inundation over complex upland floodplains

A much understudied aspect of flood inundation is examined, i.e. upland environments with topographically complex floodplains. Although the presence of high‐resolution topographic data (e.g. lidar) has improved the quality of river flood inundation predictions, the optimum dimensionality of hydraulic models for this purpose has yet to be fully evaluated for situations of both topographic and topological (i.e. the connectivity of floodplain features) complexity. In this paper, we present the comparison of three treatments of upland flood inundation using: (a) a one‐dimensional (1D) model (HEC‐RAS v. 3·1·2) with the domain defined as series of extended cross‐sections; (b) the same 1D model, but with the floodplain defined by a series of storage cells, hydraulically connected to the main river channel and other storage cells on the floodplain according to floodplain topological characteristics; (c) a two‐dimensional (2D) diffusion wave treatment, again with explicit representation of floodplain structural features. The necessary topographic and topological data were derived using lidar and Ordnance Survey Landline data. The three models were tested on a 6 km upland reach of the River Wharfe, UK. The models were assessed by comparison with measured inundation extent. The results showed that both the extended cross‐section and the storage cell 1D modes were conceptually problematic. They also resulted in poorer model predictions, requiring incorrect parameterization of the main river to floodplain flux in order to approach anything like the level of agreement observed when the 2D diffusion wave treatment was assessed. We conclude that a coupled 1D–2D treatment is likely to provide the best modelling approach, with currently available technology, for complex floodplain configurations. Copyright © 2007 John Wiley & Sons, Ltd.     

Evaluating the effect of scale in flood inundation modelling in urban environments

Cellular‐based approaches for flood inundation modelling have been extensively calibrated and evaluated for the prediction of flood flows on rural river reaches. However, there has only been limited application of these approaches to urban environments, where the need for flood management is greatest. Practical application of two‐dimensional (2D) flood inundation models is often limited by computation time and processing power on standard desktop PCs when attempting to resolve flows on the high‐resolution grids necessary to replicate urban features. Consequently, it is necessary to evaluate the effectiveness of coarse grids to represent flood flows through urban environments. To examine these effects, LISFLOOD‐FP, a 2D storage cell model, is applied to hypothetical flooding scenarios in Greenfields, Glasgow. Grid resampling techniques in GIS software packages are evaluated and a bilinear gridding technique appears to provide the most accurate and physically intuitive results. A gridding method maintaining sharp elevation changes at building interfaces and neighbouring land is presented and estimates of the discretization noise associated with the coarse resolution grids suggest little improvement over current gridding methods. The variation in model results from the friction sensitivity analysis suggests a non‐stationary response to Manning's n with changing model resolution. Model results suggests that a coarse resolution model for urban applications is limited by the representation of urban media in coarse model grids. Furthermore, critical length scales related to building dimensions and building separation distances exist in urban areas that determine maximum possible grid resolutions for hydraulic models of urban flooding. Copyright ©, 2008 John Wiley & Sons, Ltd.     

The use of remotely sensed land cover to derive floodplain friction coefficients for flood inundation modelling

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 spatially‐distributed 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. Copyright © 2007 John Wiley & Sons, Ltd.     

Interactions between subgrid‐scale resolution,feature representation and grid‐scale resolution in flood inundation modelling

Numerical modelling of flood inundation over large and complex floodplains often requires mesh resolutions coarser than the structural features (e.g. buildings) that are known to influence the inundation process. Recent research has shown that this mismatch is not well represented by conventional roughness treatments, but that finer‐scale features can be represented through porosity‐based subgrid‐scale treatments. This paper develops this work by testing the interactions between feature representation, subgrid‐scale resolution and mesh resolution. It uses as the basis for this testing a 2D diffusion‐based flood inundation model which is applied to a 2004 flood event in a topologically complex upland floodplain in northern England. This study formulated simulations with different grid mesh resolution and subgrid mesh ratio. The sensitivity of the model to mesh resolution and roughness specification was investigated. Model validation and verification suggest that the subgrid treatment with higher subgrid mesh ratio can give much improved predictions of flood propagation, in particular, in terms of the predicted water depth. This study also highlighted the limitation of using at‐a‐point in time inundation extent for validation of flood models of this type. Copyright © 2010 John Wiley & Sons, Ltd.     

Two‐dimensional hydraulic flood modelling using a finite‐element mesh decomposed according to vegetation and topographic features derived from airborne scanning laser altimetry

Airborne scanning laser altimetry (LiDAR) is an important new data source that can provide two‐dimensional river flood models with spatially distributed floodplain topography for model bathymetry, together with vegetation heights for parameterization of model friction. Methods are described for improving such models by decomposing the model's finite‐element mesh to reflect floodplain vegetation features such as hedges and trees having different frictional properties to their surroundings, and significant floodplain topographic features having high height curvatures. The decomposition is achieved using an image segmentation system that converts the LiDAR height image into separate images of surface topography and vegetation height at each point. The vegetation height map is used to estimate a friction factor at each mesh node. The spatially distributed friction model has the advantage that it is physically based, and removes the need for a model calibration exercise in which free parameters specifying friction in the channel and floodplain are adjusted to achieve best fit between modelled and observed flood extents. The scheme was tested in a modelling study of a flood that occurred on the River Severn, UK, in 1998. A satellite synthetic aperture radar image of flood extent was used to validate the model predictions. The simulated hydraulics using the decomposed mesh gave a better representation of the observed flood extent than the more simplistic but computationally efficient approach of sampling topography and vegetation friction factors on to larger floodplain elements in an undecomposed mesh, as well as the traditional approach using no LiDAR‐derived data but simply using a constant floodplain friction factor. Use of the decomposed mesh also allowed velocity variations to be predicted in the neighbourhood of vegetation features such as hedges. These variations could be of use in predicting localized erosion and deposition patterns that might result in the event of a flood. Copyright © 2003 John Wiley & Sons, Ltd.     

Comparing the performance of a 2‐D finite element and a 2‐D finite volume model of floodplain inundation using airborne SAR imagery

The performances of a finite volume model (SFV) and finite element model (TELEMAC‐2D) in reproducing inundation on a 16 km reach of the river Severn, United Kingdom, are compared. Predicted inundation extents are compared with 4 airborne synthetic aperture radar images of a major flood event in November 2000, and these are used to calibrate 2 values of Manning's n for the channel and floodplain. The four images are shown to have different capacities to constrain roughness parameters, with the image acquired at low flow rate doing better in determining these parameters than the image acquired at approximately peak flow. This is assigned to the valley filling nature of the flood and the associated insensitivity of flood extent to changes in water level. The level of skill demonstrated by the models, when compared with inundation derived using a horizontal water free surface, also increases as flow rate drops. The two models show markedly different behaviours to the calibration process, with TELEMAC showing less sensitivity and lower optimum values for Manning's n than SFV. When the models are used in predictive mode, calibrated against one image and predicting another, SFV performs better than TELEMAC. Copyright © 2007 John Wiley & Sons, Ltd.     

Assessing the uncertainty in distributed model predictions using observed binary pattern information within GLUE

In this paper we extend the generalized likelihood uncertainty estimation (GLUE) technique to estimate spatially distributed uncertainty in models conditioned against binary pattern data contained in flood inundation maps. Untransformed binary pattern data already have been used within GLUE to estimate domain‐averaged (zero‐dimensional) likelihoods, yet the pattern information embedded within such sources has not been used to estimate distributed uncertainty. Where pattern information has been used to map distributed uncertainty it has been transformed into a continuous function prior to use, which may introduce additional errors. To solve this problem we use here ‘raw’ binary pattern data to define a zero‐dimensional global performance measure for each simulation in a Monte Carlo ensemble. Thereafter, for each pixel of the distributed model we evaluate the probability that this pixel was inundated. This probability is then weighted by the measure of global model performance, thus taking into account how well a given parameter set performs overall. The result is a distributed uncertainty measure mapped over real space. The advantage of the approach is that it both captures distributed uncertainty and contains information on global likelihood that can be used to condition predictions of further events for which observed data are not available. The technique is applied to the problem of flood inundation prediction at two test sites representing different hydrodynamic conditions. In both cases, the method reveals the spatial structure in simulation uncertainty and simultaneously enables mapping of flood probability predicted by the model. Spatially distributed uncertainty analysis is shown to contain information over and above that available from global performance measures. Overall, the paper highlights the different types of information that may be obtained from mappings of model uncertainty over real and n‐dimensional parameter spaces. Copyright © 2002 John Wiley & Sons, Ltd.     

Validation of a full hydrodynamic model for large‐scale hydrologic modelling in the Amazon

A key aspect of large river basins partially neglected in large‐scale hydrological models is river hydrodynamics. Large‐scale hydrologic models normally simulate river hydrodynamics using simplified models that do not represent aspects such as backwater effects and flood inundation, key factors for some of the largest rivers of the world, such as the Amazon. In a previous paper, we have described a large‐scale hydrodynamic approach resultant from an improvement of the MGB‐IPH hydrological model. It uses full Saint Venant equations, a simple storage model for flood inundation and GIS‐based algorithms to extract model parameters from digital elevation models. In the present paper, we evaluate this model in the Solimões River basin. Discharge results were validated using 18 stream gauges showing that the model is accurate. It represents the large delay and attenuation of flood waves in the Solimões basin, while simplified models, represented here by Muskingum Cunge, provide hydrographs are wrongly noisy and in advance. Validation against 35 stream gauges shows that the model is able to simulate observed water levels with accuracy, representing their amplitude of variation and timing. The model performs better in large rivers, and errors concentrate in small rivers possibly due to uncertainty in river geometry. The validation of flood extent results using remote sensing estimates also shows that the model accuracy is comparable to other flood inundation modelling studies. Results show that (i) river‐floodplain water exchange and storage, and (ii) backwater effects play an important role for the Amazon River basin hydrodynamics. Copyright © 2011 John Wiley & Sons, Ltd.     

HAND contour: a new proxy predictor of inundation extent

Tools for accurately predicting environmental risks, such as the location and spatial extent of potential inundation, are not widely available. A dependence on calibration and a lack of available flood data have prevented the widespread application of existing hydrodynamic methods for predicting the extent of inundation. We use the height above the nearest drainage (HAND) terrain model to develop a simple static approach for mapping the potential extent of inundation that does not depend on flood observations and extends beyond methods for mapping low‐lying areas. While relying on the contour concept, the method utilizes drainage‐normalized topography and flowpaths to delineate the relative vertical distances (drop) to the nearest river. The HAND‐delineated relative drop is an effective distributed predictor of flood potential, which is directly related to the river stage height. We validated the new HAND contour approach using a flood event in Southern Brazil for which high‐resolution maps were available. The results indicated that the flood hazard‐mapping method accurately predicted the inundation extent of the channel carrying the flood wave and the channels influenced by flooding. For channels positioned outside of the flood‐wave area, the method overestimated the actual flood extent. As an original static assessment of floodwaters across the landscape, the HAND contour method could be used to map flood hazards in areas with poor information and could promote the development of new methods for predicting hydrological hazards. Copyright © 2015 John Wiley & Sons, Ltd.     

Interactions between sediment delivery,channel change,climate change and flood risk in a temperate upland environment

This paper uses numerical simulation of flood inundation based on a coupled one‐dimensional–two‐dimensional treatment to explore the impacts upon flood extent of both long‐term climate changes, predicted to the 2050s and 2080s, and short‐term river channel changes in response to sediment delivery, for a temperate upland gravel‐bed river. Results show that 16 months of measured in‐channel sedimentation in an upland gravel‐bed river cause about half of the increase in inundation extent that was simulated to arise from climate change. Consideration of the joint impacts of climate change and sedimentation emphasized the non‐linear nature of system response, and the possibly severe and synergistic effects that come from combined direct effects of climate change and sediment delivery. Such effects are likely to be exacerbated further as a result of the impacts of climate change upon coarse sediment delivery. In generic terms, these processes are commonly overlooked in flood risk mapping exercises and are likely to be important in any river system where there are high rates of sediment delivery and long‐term transfer of sediment to floodplain storage (i.e. alluviation involving active channel aggradation and migration). Similarly, attempts to reduce channel migration through river bank stabilization are likely to exacerbate this process as without bank erosion, channel capacity cannot be maintained. Finally, many flood risk mapping studies rely upon calibration based upon combining contemporary bed surveys with historical flood outlines, and this will lead to underestimation of the magnitude and frequency of floodplain inundation in an aggrading system for a flood of a given magnitude. Copyright © 2006 John Wiley & Sons, Ltd.     

Sampling-based flood risk analysis for fluvial dike systems

A dike system of moderate size has a large number of potential system states, and the loading imposed on the system is inherently random. If the system should fail, in one of its many potential failure modes, the topography of UK floodplains is usually such that hydrodynamic modelling of flood inundation is required to generate realistic estimates of flood depth and hence damage. To do so for all possible failure states may require 1,000s of computationally expensive inundation simulations. A risk-based sampling technique is proposed in order to reduce the computational resources required to estimate flood risk. The approach is novel in that the loading and dike system states (obtained using a simplified reliability analysis) are sampled according to the contribution that a given region of the space of basic variables makes to risk. The methodology is demonstrated in a strategic flood risk assessment for the city of Burton-upon-Trent in the UK. 5,000 inundation model simulations were run although it was shown that the flood risk estimate converged adequately after approximately half this number. The case study demonstrates that, amongst other factors, risk is a complex function of loadings, dike resistance, floodplain topography and the spatial distribution of floodplain assets. The application of this approach allows flood risk managers to obtain an improved understanding of the flooding system, its vulnerabilities and the most efficient means of allocating resource to improve performance. It may also be used to test how the system may respond to future external perturbations.     

Flood-plain mapping: a critical discussion of deterministic and probabilistic approaches

Abstract

Different methodologies for flood-plain mapping are analysed and discussed by comparing deterministic and probabilistic approaches using hydrodynamic numerical solutions. In order to facilitate the critical discussion, state-of-art techniques in the field of flood inundation modelling are applied to a specific test site (River Dee, UK). Specifically, different flood-plain maps are derived for this test site. A first map is built by applying an advanced deterministic approach: use of a fully two-dimensional finite element model (TELEMAC-2D), calibrated against a historical flood extent, to derive a 1-in-100 year flood inundation map. A second map is derived by using a probabilistic approach: use of a simple raster-based inundation model (LISFLOOD-FP) to derive an uncertain flood extent map predicting the 1-in-100 year event conditioned on the extent of the 2006 flood. The flood-plain maps are then compared and the advantages and disadvantages of the two different approaches are critically discussed.

Citation Di Baldassarre, G., Schumann, G., Bates, P. D., Freer, J. E. & Beven, K. J. (2010) Flood-plain mapping: a critical discussion of deterministic and probabilistic approaches. Hydrol. Sci. J. 55(3), 364–376.     

Bayesian updating of flood inundation likelihoods conditioned on flood extent data

Previously we have detailed an application of the generalized likelihood uncertainty estimation (GLUE) procedure to estimate spatially distributed uncertainty in models conditioned against binary pattern data contained in flood inundation maps. This method was applied to two sites where a single consistent synoptic image of inundation extent was available to test the simulation performance of the method. In this paper, we extend this to examine the predictive performance of the method for a reach of the River Severn, west‐central England. Uniquely for this reach, consistent inundation images of two major floods have been acquired from spaceborne synthetic aperture radars, as well as a high‐resolution digital elevation model derived using laser altimetry. These data thus allow rigorous split sample testing of the previous GLUE application. To achieve this, Monte Carlo analyses of parameter uncertainty within the GLUE framework are conducted for a typical hydraulic model applied to each flood event. The best 10% of parameter sets identified in each analysis are then used to map uncertainty in flood extent predictions using the method previously proposed for both an independent validation data set and a design flood. Finally, methods for combining the likelihood information derived from each Monte Carlo ensemble are examined to determine whether this has the potential to reduce uncertainty in spatially distributed measures of flood risk for a design flood. The results show that for this reach and these events, the method previously established is able to produce sharply defined flood risk maps that compare well with observed inundation extent. More generally, we show that even single, poor‐quality inundation extent images are useful in constraining hydraulic model calibrations and that values of effective friction parameters are broadly stationary between the two events simulated, most probably reflecting their similar hydraulics. Copyright © 2004 John Wiley & Sons, Ltd.     

A hydro‐economic modelling framework for flood damage estimation and the role of riparian vegetation

A modelling framework for the quick estimate of flood inundation and the resultant damages is developed in this paper. The model, called the flood economic impact analysis system (FEIAS), can be applied to a river reach of any hydrogeological river basin. For the development of the integrated modelling framework, three models were employed: (1) a modelling scheme based on the Hydrological Simulation Program FORTRAN model that was developed for any geomorphological river basin, (2) a river flow/floodplain model, and (3) a flood loss estimation model. The first sub‐model of the flood economic impact analysis system simulates the hydrological processes for extended periods of time, and its output is used as input to a second component, the river/floodplain model. The hydraulic model MIKE 11 (quasi‐2D) is the river/floodplain model employed in this study. The simulated flood parameters from the hydraulic model MIKE 11 (quasi‐2D) are passed, at the end of each time step, to a third component, the flood loss model for the estimation of flood damage. In the present work, emphasis was given to the seasonal variation of Manning's coefficient (n), which is an important parameter for the determination of the flood inundation in hydraulic modelling. High values of Manning's coefficient for a channel indicate high flow resistance. The riparian vegetation can have a large impact on channel resistance. The modelling framework developed in this paper was used to investigate the role of riparian vegetation in reducing flood damage. Moreover, it was used to investigate the influence of cutting riparian vegetation scenarios on the flow characteristics. The proposed framework was applied to the downstream part of the Koiliaris River basin in Crete, Greece, and was tested and validated with historical data. Copyright © 2012 John Wiley & Sons, Ltd.     

The Hat Yai 2000 flood: the worst flood in Thai history

Hat Yai, the largest commercial and tourist city in southern Thailand, is subjected to regular flood events, primarily during the northeast monsoon period. Flooding in this region is recognized as a serious disaster in terms of frequency, rate of risk, and affected areas. The monsoon of 21–25 November 2000 caused extremely heavy rain in the southern part of Thailand, resulting in a great flood occupying Hat Yai. This caused significant damage. Therefore, the use of both structural and non‐structural measures is mandatory to reduce the economic losses and the risk for society. This paper investigates two modelling approaches for flood prevention and mitigation of Hat Yai city. First, a hard computing approach by a physically distributed model was applied to study the flood behaviour in a two‐dimensional floodplain flow. Second, a soft computing approach using a neuro‐genetic algorithm was used to develop a flood‐forecasting tool. It was found that the great flood of 2000 can be simulated well by the FLO‐2D model. Computed discharges and flood level in the floodplain are close to the observed data. Countermeasures using diversion canals are guaranteed to accelerate the floodwater drainage to Songkla Lake, significantly reducing the flood impact to the people. In addition, the flood forecasting technique developed in this study can give satisfactory results. This would be very useful as a flood‐warning tool for the community Copyright © 2005 John Wiley & Sons, Ltd.     

Numerical simulation of overbank processes in topographically complex floodplain environments

This article presents results from an investigation of the hydraulic characteristics of overbank flows on topographically‐complex natural river floodplains. A two‐dimensional hydraulic model that solves the depth‐averaged shallow water form of the Navier–Stokes equations is used to simulate an overbank flow event within a multiple channel reach of the River Culm, Devon, UK. Parameterization of channel and floodplain roughness by the model is evaluated using monitored records of main channel water level and point measurements of floodplain flow depth and unit discharge. Modelled inundation extents and sequences are assessed using maps of actual inundation patterns obtained using a Global Positioning System, observational evidence and ground photographs. Simulation results suggest a two‐phase model of flooding at the site, which seems likely to be representative of natural floodplains in general. Comparison of these results with previous research demonstrates the complexity of overbank flows on natural river floodplains and highlights the limitations of laboratory flumes as an analogue for these environments. Despite this complexity, frequency distributions of simulated depth, velocity and unit discharge data closely follow a simple gamma distribution model, and are described by a shape parameter (α) that exhibits clear systematic trends with changing discharge and floodplain roughness. Such statistical approaches have the potential to provide the basis for computationally efficient flood routing and overbank sedimentation models. Copyright © 2002 John Wiley & Sons, Ltd.