High‐resolution interpretative geomorphological mapping of river valley environments using airborne LiDAR data

The availability of airborne LiDAR data provides a new opportunity to overcome some of the problems associated with traditional, field‐based, geomorphological mapping such as restrictions on access and constraints of time or cost. The combination of airborne LiDAR data and GIS technology facilitates the rapid production of geomorphological maps of floodplain environments; however, unfiltered LiDAR data, which include vegetation and buildings, are currently more suitable for geomorphological mapping than data that have been filtered to remove these features. Classification of LiDAR data according to elevation in a GIS enables the user to identify and delineate geomorphological features in a manner similar to field mapping, but it is necessary to use a range of classification intervals in order to map the various types of feature that occur within a single reach. Comparison of a LiDAR‐derived geomorphological map with an independently produced field geomorphological map showed a high degree of similarity between the results of the two methods, although ground‐truthing is essential in cases where a high degree of accuracy is required. Ground‐truthing of a LiDAR‐derived geomorphological map showed that around 80% of features mapped using both methods were identified from the LiDAR data, suggesting that the method is suitable for applications such as production of base maps for use in field mapping and selection of sites for detailed investigation. Copyright © 2007 John Wiley & Sons, Ltd.     

Remote measurement of river morphology via fusion of LiDAR topography and spectrally based bathymetry

This study developed and evaluated a hybrid approach to remote measurement of river morphology that combines LiDAR topography with spectrally based bathymetry. Comparison of filtered LiDAR point clouds with surveyed cross‐sections indicated that subtle features on low‐relief floodplains were accurately resolved by LiDAR but that submerged areas could not be detected due to strong absorption of near‐infrared laser pulses by water. The reduced number of returns made the active channel evident in a LiDAR point density map. A second dataset suggested that pulse intensity also could be used to discriminate land from water via a threshold‐based masking procedure. Fusion of LiDAR and optical data required accurate co‐registration of images to the LiDAR, and we developed an object‐oriented procedure for achieving this alignment. Information on flow depths was derived by correlating pixel values with field measurements of depth. Highly turbid conditions dictated a positive relation between green band radiance and flow depth and contributed to under‐prediction of pool depths. Water surface elevations extracted from the LiDAR along the water's edge were used to produce a continuous water surface that preserved along‐channel variations in slope. Subtracting local flow depths from this surface yielded estimates of the bed elevation that were then combined with LiDAR topography for exposed areas to create a composite representation of the riverine terrain. The accuracy of this terrain model was assessed via comparison with detailed field surveys. A map of elevation residuals showed that the greatest errors were associated with underestimation of pool depths and failure to capture cross‐stream differences in water surface elevation. Nevertheless, fusion of LiDAR and passive optical image data provided an efficient means of characterizing river morphology that would not have been possible if either dataset had been used in isolation. Copyright © 2011 John Wiley & Sons, Ltd.     

Comparison of LiDAR waveform processing methods for very shallow water bathymetry using Raman,near‐infrared and green signals

Airborne light detection and ranging (LiDAR) bathymetry appears to be a useful technology for bed topography mapping of non‐navigable areas, offering high data density and a high acquisition rate. However, few studies have focused on continental waters, in particular, on very shallow waters (<2 m) where it is difficult to extract the surface and bottom positions that are typically mixed in the green LiDAR signal. This paper proposes two new processing methods for depth extraction based on the use of different LiDAR signals [green, near‐infrared (NIR), Raman] of the SHOALS‐1000T sensor. They have been tested on a very shallow coastal area (Golfe du Morbihan, France) as an analogy to very shallow rivers. The first method is based on a combination of mathematical and heuristic methods using the green and the NIR LiDAR signals to cross validate the information delivered by each signal. The second method extracts water depths from the Raman signal using statistical methods such as principal components analysis (PCA) and classification and regression tree (CART) analysis. The obtained results are then compared to the reference depths, and the performances of the different methods, as well as their advantages/disadvantages are evaluated. The green/NIR method supplies 42% more points compared to the operator process, with an equivalent mean error (?4·2 cm verusu ?4·5 cm) and a smaller standard deviation (25·3 cm verusu 33·5 cm). The Raman processing method provides very scattered results (standard deviation of 40·3 cm) with the lowest mean error (?3·1 cm) and 40% more points. The minimum detectable depth is also improved by the two presented methods, being around 1 m for the green/NIR approach and 0·5 m for the statistical approach, compared to 1·5 m for the data processed by the operator. Despite its ability to measure other parameters like water temperature, the Raman method needed a large amount of reference data to provide reliable depth measurements, as opposed to the green/NIR method. Copyright © 2010 John Wiley & Sons, Ltd.     

Reach‐scale channel geometry of a mountain river

Mountain rivers can be subject to strong constraints imposed by changes in gradient and grain size supplied by processes such as glaciation and rockfall. Nonetheless, adjustments in the channel geometry and hydraulics of mountain rivers at the reach scale can produce discernible patterns analogous to those in fully alluvial rivers. Mountain rivers can differ in that imposed reach‐scale gradient is an especially important control on reach‐scale channel characteristics, as indicated by examination of North St Vrain Creek in Colorado. North St Vrain Creek drains 250 km² of the Rocky Mountains. We used 25 study reaches within the basin to examine controls on reach‐scale channel geometry. Variables measured included channel geometry, large woody debris, grain size, and mean velocity. Drainage area at the study reaches ranged from 2·2 to 245 km², and gradient from 0·013 to 0·147 m m^?1. We examined correlations among (1) potential reach‐scale response variables describing channel bankfull dimension and shape, hydraulics, bedform wavelength and amplitude, grain size, ?ow resistance, standard deviation of hydraulic radius, and volume of large woody debris, and (2) potential control variables that change progressively downstream (drainage area, discharge) or that are likely to re?ect a reach‐speci?c control (bed gradient). We tested the hypothesis that response variables correlate most strongly with local bed gradient because of the segmented nature of mountain channels. Results from simple linear regression analyses indicate that most response variables correlate best with gradient, although channel width and width/depth ratio correlate best with discharge. Multiple regression analyses using Mallow's C_p selection criterion and log‐transformation of all variables produced similar results in that most response variables correlate strongly with gradient. These results suggest that the hypothesis is partially supported: channel bed gradient is likely to be a good predictor for many reach‐scale response variables along mountain rivers, but discharge is also an important predictor for some response variables. Copyright © 2004 John Wiley & Sons, Ltd.     

Spectrally based remote sensing of river bathymetry

This paper evaluates the potential for remote mapping of river bathymetry by (1) examining the theoretical basis of a simple, ratio‐based technique for retrieving depth information from passive optical image data; (2) performing radiative transfer simulations to quantify the effects of suspended sediment concentration, bottom reflectance, and water surface state; (3) assessing the accuracy of spectrally based depth retrieval under field conditions via ground‐based reflectance measurements; and (4) producing bathymetric maps for a pair of gravel‐bed rivers from hyperspectral image data. Consideration of the relative magnitudes of various radiance components allowed us to define the range of conditions under which spectrally based depth retrieval is appropriate: the remotely sensed signal must be dominated by bottom‐reflected radiance. We developed a simple algorithm, called optimal band ratio analysis (OBRA), for identifying pairs of wavelengths for which this critical assumption is valid and which yield strong, linear relationships between an image‐derived quantity X and flow depth d. OBRA of simulated spectra indicated that water column optical properties were accounted for by a shorter‐wavelength numerator band sensitive to scattering by suspended sediment while depth information was provided by a longer‐wavelength denominator band subject to strong absorption by pure water. Field spectra suggested that bottom reflectance was fairly homogeneous, isolating the effect of depth, and that radiance measured above the water surface was primarily reflected from the bottom, not the water column. OBRA of these data, 28% of which were collected during a period of high turbidity, yielded strong X versus d relations (R² from 0·792 to 0·976), demonstrating that accurate depth retrieval is feasible under field conditions. Moreover, application of OBRA to hyperspectral image data resulted in spatially coherent, hydraulically reasonable bathymetric maps, though negative depth estimates occurred along channel margins where pixels were mixed. This study indicates that passive optical remote sensing could become a viable tool for measuring river bathymetry. Copyright © 2009 John Wiley & Sons, Ltd.     

Estimating the probability of river channel adjustment

River channels respond not only to natural external controls, and natural controls internal to individual drainage basins, but also to the influence of human activity. Although many site-specific instances of change have been documented, the complexity of the process interactions means that very little is known about the general nature of different styles of adjustment, or their relative sensitivity to drainage basin controls. Data obtained from the Thames Basin, southeast England, are used in a probabilistic approach to differentiate between four styles of river channel adjustment and a variety of drainage basin characteristics. Adopting a probabilistic approach quantifies the degree of confidence attributable to any prediction of river channel adjustment while acknowledging that certainties are difficult to obtain in studies of the natural environment. This approach could thus allow environmental planning decisions to be made with a quantified degree of uncertainty. Four multivariate logistic regression models are described which use a combination of continuous and categorical variables to associate drainage basin characteristics with four styles of river channel adjustment derived from a reconnaissance evaluation survey. In comparison, it is shown that laterally migrating river channels are the most common ‘natural’ channel type in the Thames Basin, and their probability of occurrence rises to 71 per cent in sand/gravel environments. In channels regulated by low weirs, deposition is the most likely channel activity where gradients are lower than 0·0040, whilst above this threshold the majority of channels are morphologically inactive. In urban channels, many of which are also lined by concrete, the likelihood of obtaining a stable channel is mostly in excess of 80 per cent. In channels straightened during this century, deposition is most likely in gradients below 0·0050, whereas erosional enlargement is most probable above this value. In channels which were initially channelized prior to this century, deposition gives way to stability at a threshold gradient of 0·0080.     

Adjustments in river channel geometry associated with hydraulic discontinuities across the fluvial–tidal transition of a regulated river

Major hydraulic discontinuities along lowland rivers may be caused by water impoundment behind weirs, by tributary floods, and by tides. An analysis of the geometry of 122 surveyed channel cross-sections located on an 18 km reach of the lower River Dee identifies up to three levels in the bank profile representing minima in the width:mean depth ratio, and distinct changes in the geometric properties of the channel to these three levels in a downstrem direction and within four stretches influenced to varying degrees by hydraulic discontinuities created by a weir and by tidal overtopping of the weir. Simple modelling combined with field observations suggest possible processes that may control the observed changes in channel morphology. © 1997 John Wiley & Sons, Ltd.     

The stream power river incision model: evidence,theory and beyond

The stream power incision model (SPIM) is a cornerstone of quantitative geomorphology. It states that river incision rate is the product of drainage area and channel slope raised to the power exponents m and n, respectively. It is widely used to predict patterns of deformation from channel long profile inversion or to model knickpoint migration and landscape evolution. Numerous studies have attempted to test its applicability with mixed results prompting the question of its validity. This paper synthesizes these results, highlights the SPIM deficiencies, and offers new insights into the role of incision thresholds and channel width. By reviewing quantitative data on incising rivers, I first propose six sets of field evidence that any long‐term incision model should be able to predict. This analysis highlights several inconsistencies of the standard SPIM. Next, I discuss the methods used to construct physics‐based long‐term incision laws. I demonstrate that all published incising river datasets away from knickpoints or knickzones are in a regime dominated by threshold effects requiring an explicit upscaling of flood stochasticity neglected in the standard SPIM and other incision models. Using threshold‐stochastic simulations with dynamic width, I document the existence of composite transient dynamics where knickpoint propagation locally obeys a linear SPIM (n=1) while other part of the river obey a non‐linear SPIM (n>1). The threshold‐stochastic SPIM resolves some inconsistencies of the standard SPIM and matches steady‐state field evidence when width is not sensitive to incision rate. However it fails to predict the scaling of slope with incision rate for cases where width decreases with incision rate. Recent proposed models of dynamic width cannot resolve these deficiencies. An explicit upscaling of sediment flux and threshold‐stochastic effects combined with dynamic width should take us beyond the SPIM which is shown here to have a narrow range of validity. Copyright © 2013 John Wiley & Sons, Ltd.     

Influence of river channel geometry in stream flow modelling and guidelines for field investigation

Fully physics‐based, process‐level, distributed fluid flow and reactive transport hydrological models are rarely used in practice until recent years. These models are useful tools to help understand the fundamental physical, chemical, and biological processes that take place in nature. In this study, sensitivity analyses based on a mountain area river basin modelling study are performed to investigate the effect of river channel geometric characteristics on downstream water flow. Numerical experiments show that reduction in the river channel geometric measurement interval may not significantly affect the downstream water stage simulation as long as measurement accuracy at special nodes is guaranteed. The special upstream nodes include but are not limited to 1) nodes located close to the observation station, 2) nodes near the borders of different land covers with considerable riverbed roughness changes, 3) nodes at entering points of tributaries causing discharge jump and 4) nodes with a narrow cross‐section width that may control the flow conditions. This information provides guidelines for field investigation to efficiently obtain necessary geometric data for physics‐based hydrological modelling. It is especially useful in alpine areas such as the Tibetan Plateau where field investigation capability is limited under severe topography and climate condition. Copyright © 2013 John Wiley & Sons, Ltd.     

Variable self‐similar sinuosity properties within simulated river networks

River networks have been shown to obey power scaling laws and to follow self‐organization principles. Their self‐similar (fractal) properties open a path to relate small scale and large scale hydrological processes, such as erosion, deposition or geological movements. However, the existence of a self‐similar dimension has only been checked using either the whole channel network or, on the contrary, a single channel link. No study has explicitly addressed the possible spatial variation of the self‐similar properties between these two extreme geomorphologic objects. Here, a new method based on self‐similarity maps (SSM) is proposed to spatially explore the stream length self‐similar dimension D_l within a river network. The mapping principle consists in computing local self‐similar dimensions deduced from a fit of stream length estimations using increasing divider sizes. A local uncertainty related to the fit quality is also computed and localized on every stream. To assess the efficiency of the approach, contrasted river networks are simulated using optimal channel networks (OCN), where each network is characterized by an exponent γ conditioning its overall topology. By building SSM of these networks, it is shown that deviations from uniform self‐similarity across space occur. Depending on the type of network (γ parameter), these deviations are or are not related to Strahler's order structure. Finally, it is found numerically that the structural averaged stream length self‐similar dimension D_l is closely related to the more functional γ parameter. Results form a bridge between the studies on river sinuosity (single channel) and growth of channel networks (watershed). As for every method providing spatial information where they were lacking before, the SSM may soon help to accurately interpret natural networks and help to simulate more realistic channel networks. Copyright © 2011 John Wiley & Sons, Ltd.     

Suitability of LiDAR point density and derived landform curvature maps for channel network extraction

This study uses landform curvature as an approach for channel network extraction. We considered a study area located in the eastern Italian Alps where a high‐quality set of LiDAR data was available and where channel heads and related channel network were mapped in the field. In the analysis, we derived 1‐m DTMs from different ground LiDAR point densities, and we used different smoothing factors for the landscape curvature calculation in order to test the suitability of the LiDAR point density and the derived curvature maps for the recognition of channel network. This methodology is based on threshold values of the curvature calculated as multiples (1–3 times) of the standard deviation of the curvature. Our analyses suggested that (i) the window size for curvature calculations has to be a function of the size of the features to be detected, (ii) a coarse ground LiDAR point density could be as useful as a finer one for the recognition of main channel network features and (iii) rougher curvature maps are not optimal as they do not explore a sufficient range at which features occur, while smoother curvature maps overcome this problem and are more appropriate for the extraction of surveyed channels. Copyright © 2010 John Wiley & Sons, Ltd.     

Geostatistical analysis of ground‐survey elevation data to elucidate spatial and temporal river channel change

A digital elevation model (DEM) of a fluvial environment represented landform surface variability well and provided a medium for monitoring morphological change over time. Elevation was measured above an arbitrary datum using a ground‐based three‐dimensional tacheometric survey in two reaches of the River Nent, UK, in July 1998, October 1998 (after flood conditions) and June 1999. A detailed geostatistical analysis of the elevation data was used to model the spatial variation of elevation and to produce DEMs in each reach and for each survey period. Maps of the difference in elevation were produced and volumetric change was calculated for each reach and each survey period. The parameters of variogram models were used to describe the morphological character of each reach and to elucidate the linkages between process and the form of channel change operating at different spatial and temporal scales. The analysis of channel change on the River Nent shows the potential of geostatistics for investigating the magnitude and frequency of geomorphic work in other rivers. A flood modified the channel features, but low magnitude and high frequency flows rationalized the morphology. In spite of relatively small amounts of net flux the channel features changed as a consequence of the reworking of existing material. The blocking of chute entrances and redirection of the channel had a considerable effect on the behaviour of the channel. Such small changes suggested that the distributary system was sensitive to variation in sediment regime. Plots of the kriging variances against sampling intervals were used to quantify the temporal variation in sampling redundancy (ranging between ?11 per cent and +93 per cent). These curves illustrated the importance of bespoke sampling designs to reduce sampling effort by incorporating anisotropic variation in space and geomorphic information on flow regime. Variation in the nugget parameter of the variogram models was interpreted as sampling inaccuracy caused by variability in particle size and is believed to be important for future work on surface roughness. Copyright © 2003 John Wiley & Sons, Ltd.     

Response of river channel patterns to the spatially varying suspended sediment concentrations

River channel pattern transformation is dealt with in a broad background of suspended sediment concentration, varying from low, medium, high to hyperconcentration. Based on data from about 100 alluvial rivers in China, suspended sediment transport rate has been plotted against mean annual water discharge, showing that all points can be divided into four belts by three straight lines, as stable braided pattern, meandering pattern with ordinary sediment concentrations, wandering braided pattern, and meandering pattern with hyperconcentration of sediment. This picture of channel pattern transformation can be well explained by the law of the water flow's energy expenditure varying with its sediment concentration. The energy expenditure increases with sediment concentration, reaching a maximum, then declines. Rivers falling in different ranges of sediment concentrations adjust their own energy expenditure in different manners, leading to occurrence of different channel patterns. Project supported by the National Natural Science Foundation of China (Grant No. 49671011).     

The effect of tide on the hydrology and morphology of a freshwater river

How does river hydrology and morphology change due to tidal influence? We contend that this is a question of particular consequence to many earth surface disciplines, but one that has not been adequately addressed. Previous studies have relied on gradients in channel morphology and stratigraphy to infer energy regime of channels. However, in tidal rivers geomorphology influences the energy regime while the energy regime influences morphology; thus, geomorphic and stratigraphic patterns do not fully resolve the mechanisms which lead to change. We addressed this problem by comparing measurements of hydraulic energy and channel morphology along a tidal gradient to predictions of these characteristics in the absence of tides, and attributed the differences to tidal processes. Measurements of discharge, channel area, and energy dissipation (in kJ day^–1) were made over a 24·8 hour period at four sites spanning the non‐tidal to tidal freshwater Newport River, NC. We then predicted those characteristics under non‐tidal conditions using hydraulic geometry relationships and literature values from coastal plain rivers. Discharge was enhanced more than 10‐fold by tide, and this tidal effect increased from upstream to downstream along the tidal gradient. Cross‐sectional area increased three‐fold due to tide. Energy dissipation measured in the upper tidal river was four‐fold lower than predicted to occur in the absence of tide because tides decreased average velocity and discharge. Energy dissipation measured downstream was similar to that predicted to occur without tides, although there was large uncertainty in predicted values downstream. While this limited dataset does not permit us to make broad generalizations for definitive models, it does provide a proof‐of‐concept for a new approach to addressing a critical problem at the interface of fluvial and coastal morphology. Copyright © 2013 John Wiley & Sons, Ltd.     

Application of boat‐based laser scanning for river survey

The boat‐based, mobile mapping system (BoMMS) with a laser scanner allows the derivation of detailed riverine topographical data for fluvial applications. Combined with data acquisition from static terrestrial LiDAR (light detection and range) or mobile terrestrial LiDAR on the ground, boat‐based laser scanning enables a totally new field mapping approach for fluvial studies. The BoMMS approach is an extremely rapid methodology for surveying riverine topography, taking only 85 min to survey a reach approximately 6 km in length. The BoMMS approach also allowed an effective survey angle for deep river banks, which is difficult to achieve with aerial or static terrestrial LiDAR. Further, this paper demonstrates the three‐dimensional mapping of a point‐bar and its detailed morphology. Compared with the BoMMS surface, approximately, 80% and 96% of the terrestrial LiDAR points showed a height deviation of less than 2 cm and 5 cm, respectively, with an overall standard deviation of ± 2·7 cm. This level of accuracy and rapidity of data capture enables the mapping of post‐flood deposition directly after a flood event without an extensive time lag. Additionally, the improved object characterisation may allow for better 3D mapping of the point bar and other riverrine features. However, the shadow effect of the BoMMS survey in point bar mapping should be removed by additional LiDAR data to acquire entire riverine topography. The approach demonstrated allowed a large reach to be surveyed compared with static terrestrial LiDAR and increased the spatial limit of survey towards aerial LiDAR, but it maintains the same or even better temporal resolution as static terrestrial LiDAR. Copyright © 2009 John Wiley & Sons, Ltd.     

Comparison of hydraulic geometry between sand‐ and gravel‐bed rivers in relation to channel pattern discrimination

A comparison has been made between the hydraulic geometry of sand‐ and gravel‐bed rivers, based on data from alluvial rivers around the world. The results indicate a signi?cant difference in hydraulic geometry among sand‐ and gravel‐bed rivers with different channel patterns. On this basis, some diagrams for discrimination of meandering and braided channel patterns have been established. The relationships between channel width and water discharge, between channel depth and water discharge, between width–depth ratio and water discharge and between channel slope and water discharge can all be used for channel pattern discrimination. The relationship between channel width and channel depth can also be used for channel pattern discrimination. However, the accuracy of these relationships for channel pattern discrimination varies, and the depth–discharge relationship is a better discriminator of pattern type than the classic slope–discharge function. The cause for this difference has been explained qualitatively. To predict the development of channel patterns under different natural conditions, the pattern discriminator should be searched on the basis of independent or at least semi‐independent variables. The relationship between stream power and bed material grain size can be used to discriminate channel patterns, which shows a better result than the discriminator using the slope–discharge relationship. Copyright © 2004 John Wiley & Sons, Ltd.     

Effect of cross‐section interpolated bathymetry on 2D hydrodynamic model results in a large river

Two‐dimensional (2D) hydrodynamic models have been increasingly used to quantify aquatic habitat and stream processes, such as sediment transport, streambed morphological evolution, and inundation extents. Because river topography has a strong influence on predicted hydraulic conditions, 2D models require accurate and detailed bathymetric data of the stream channel and surrounding floodplains. Besides collection of mass points to construct high‐resolution three‐dimensional surfaces, bathymetries may be interpolated from cross‐sections. However, limited information is available on the effects of cross‐section spacing and the derived interpolated bathymetry on 2D model results in large river systems. Here, we investigated the effects of cross‐section spacing on flow properties simulated with 2D modeling at low, medium and high discharges in two morphologically different reaches, a simple (almost featureless with low sinuosity) and a complex (presenting pools, riffles, runs, contractions and expansions) reach of the Snake River (Idaho, USA), the tenth largest river in the United States in terms of drainage area. We compared the results from 2D models developed with complete channel bathymetry acquired with multibeam sonar data and photogrammetry, with 2D model results that were developed using interpolated topography from uniformly distributed transects. Results indicate that cross‐sections spaced equal to or greater than 2 times the average channel width (W*) smooths the bathymetry and suppresses flow structures. Conversely, models generated with cross‐sections spaced at 0.5 and 1 W* have stream flow properties, sediment mobility and spatial habitat distribution similar to those of the complete bathymetry. Furthermore, differences in flow properties between interpolated and complete topography models generally increase with discharge and with channel complexity. Copyright © 2013 John Wiley & Sons, Ltd.     

Physical explanations of variations in river meander migration rates from model comparison

In meandering rivers, the local channel migration rate increases with increasing bend sharpness until it reaches a maximum at a certain critical value of the bend sharpness. Beyond this critical value, the migration rate decreases if bend sharpness increases. Similarly, reach‐averaged migration rates attain a maximum at a certain river sinuosity. This work investigates the physics of these phenomena by comparing the results of two physics‐based models of different complexity, in which the migration rates are proportional to the near‐bank flow velocity excess. In the computational tests the river was allowed to meander progressively, starting from an almost straight planimetry. Both models reproduced the observed peak in the curve describing the local migration rate as a function of the ratio radius of curvature‐channel width (R/B), with a rising limb at lower R/B values and a falling limb at higher R/B values. The rising limb can be explained by the decrease in relative lag distance between near‐bank flow velocity and forcing curvature as R/B increases. The falling limb results from the decrease in local channel curvature and near‐bank flow velocity excess. Since the models do not include flow separation, the results indicate that this phenomenon is not needed to explain the decrease of channel migration rates in sharp bends. The models reproduced also the peak in the curve describing the reach‐averaged migration rates as a function of river sinuosity The increase and then decrease of reach‐averaged migration rates as sinuosity increases appears to be mainly caused by the variation of the reach‐averaged value of the ratio R/B. Copyright © 2009 John Wiley & Sons, Ltd.     

Geometric and structural river channel complexity and the prediction of urban inundation

Recent research modelling floodplain inundation processes has concentrated on issues surrounding the level of physical, topographical, and numerical solver complexity needed to represent floodplain flows adequately. However, during flooding episodes the channel typically still conveys the bulk of the flow. Despite this, the effect of channel physical processes and topographic complexity on model results has been largely unexplored. To address this, the impact of channel cross‐section geometry, channel long‐profile variability and the representation of hydraulic structures on floodplain inundation are explored using a coupled dynamic 1D‐2D hydraulic model (ESTRY‐TUFLOW) of the Carlisle floods of January 2005. These simulations are compared with those from a simplified 1D‐2D model, LISFLOOD‐FP. In this case, the simpler model is sufficient to simulate the far‐field peak flood elevations. However, comparison of channel dynamics suggests that the full shallow water approximation used by ESTRY‐TUFLOW gives a more robust performance when models calibrated on maximum floodplain water elevations are used to predict channel water levels. Examination of the response of ESTRY‐TUFLOW to variations in channel geometric complexity shows that downstream variations in the channel long profile are more important than cross‐section variability for obtaining a dataset‐independent calibration. The results show, in general, that as model physical complexity is increased, calibrated parameters become less ‘effective’, and as a consequence, the values of performance measures reduce less rapidly away from the optimum value. This means that often more physically complex models are less likely to yield different optimum parameter values when calibrated on different datasets resulting in a more robust numerical model. Lastly, the inclusion of bridge structures can simulate substantial local backwatering effects, but the variability in observed water and wrack marks is such that it is not possible to discern the effect of the bridges at this site in the post‐event observational dataset. Copyright © 2011 John Wiley & Sons, Ltd.