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The assessment of river channels widely focusses on using channel form to identify channel character but fails to capture the more nuanced variations in morphodynamics without the analysis of process. This paper presents a method using an index of channel behaviour, the throughput ratio (ζ), which is calculated from morphologic change and sediment transport, and explores the viability of inferring process from channel form to act as an indicator of channel behaviour. Two experiments using the same initial width, slope, discharge, and grain size were used to demonstrate the effectiveness of this method in representing different morphodynamics. In one experiment the channel was allowed to laterally deform, whilst the other had inerodible elements placed at its boundaries. As a result the experiment with mobile banks widened and reduced sediment transport to zero, whereas the fixed-bank experiment – unable to decrease its shear stress – continued to output material. In both, the rate of morphologic change tended to zero despite their marked differences in sediment transport over time. The differences in evolution are due to the differences in process available to each channel despite an initial similarity in bed mobility and their gross similarity of a meandering planform. The throughput ratio allows new representations of the temporal and spatial patterns of the morphodynamics, providing additional measures with which to analyse the processes acting in river channels.

Channel processes under high-magnitude flow events are of central interest to river science and management as they may produce large volumes of sediment transport and geomorphic work. However, bedload transport processes under these conditions are poorly understood due to data collection limitations and the prevalence of physical models that restrict feedbacks surrounding morphologic adjustment. The extension of mechanistic bedload transport equations to gravel-bed rivers has emphasised the importance of variance in both entraining (shear stress) and resisting (grain size) forces, especially at low excess shear stresses. Using a fixed-bank laboratory model, we tested the hypothesis that bedload transport in rivers collapses to a more simple function (i.e. with mean shear stress and median grain size) under high excess shear stress conditions. Bedload transport was well explained by the mean shear stress (1D approach) calculated using the depth–slope product. Numerically modelling shear stress to account for the variance in shear stress (2D) did not substantially improve the correlation. Critical dimensionless shear stress values were back-calculated and were higher for the 2D approach compared to the 1D. This result suggests that 2D critical values account for the relatively greater influence of high shear stresses, whereas the 1D approach assumes that the mean shear stress is sufficient to mobilise the median grain size. While the 2D approach may have a stronger conceptual basis, the 1D approach performs unreasonably well under high excess shear stress conditions. Further work is required to substantiate these findings in laterally adjustable channels.

Channel processes under high-magnitude flow events are of central interest to river science and management as they may produce large volumes of sediment transport and geomorphic work. However, bedload transport processes under these conditions are poorly understood due to data collection limitations and the prevalence of physical models that restrict feedbacks surrounding morphologic adjustment. The extension of mechanistic bedload transport equations to gravel-bed rivers has emphasised the importance of variance in both entraining (shear stress) and resisting (grain size) forces, especially at low excess shear stresses. Using a fixed-bank laboratory model, we tested the hypothesis that bedload transport in rivers collapses to a more simple function (i.e. with mean shear stress and median grain size) under high excess shear stress conditions. Bedload transport was well explained by the mean shear stress (1D approach) calculated using the depth–slope product. Numerically modelling shear stress to account for the variance in shear stress (2D) did not substantially improve the correlation. Critical dimensionless shear stress values were back-calculated and were higher for the 2D approach compared to the 1D. This result suggests that 2D critical values account for the relatively greater influence of high shear stresses, whereas the 1D approach assumes that the mean shear stress is sufficient to mobilise the median grain size. While the 2D approach may have a stronger conceptual basis, the 1D approach performs unreasonably well under high excess shear stress conditions. Further work is required to substantiate these findings in laterally adjustable channels.

It is understood that the interaction between sediment supply and discharge drives first-order behaviour of alluvial deposits. The influence of the grain size distribution over the mobility and resultant evolution is, however, unclear. Four experiments were conducted in a scaled physical model for two grain size distributions, analogous to a one-dimensional self-formed alluvial fan. We demonstrate the unsuitability of the median grain size as a predictor of deposit behaviour at flows when the material is not equally mobile. The results instead suggest, during conditions of unequal mobility, that the largest grains control the transport efficiency of the overall sediment mixture, and thus also the morphodynamics of the deposit and its tendency to store or evacuate material. Deposits appear to show a dependence upon the rate of material supply more strongly when the likelihood of its motion is less equally distributed (i.e. under partial transport conditions). If the coarse fraction (e.g. greater than 84th percentile) is instead mobile due to increased discharge or because of their relative size, transport rates will increase and the behaviour of the mixtures converge to a common state, with morphology influenced by the material's mobility.

Most studies of gravel bed rivers present at least one bed surface grain size distribution, but there is almost never any information provided about the uncertainty in the percentile estimates. We present a simple method for estimating the grain size confidence intervals about sample percentiles derived from standard Wolman or pebble count samples of bed surface texture. The width of a grain size confidence interval depends on the confidence level selected by the user (e.g., 95 %), the number of stones sampled to generate the cumulative frequency distribution, and the shape of the frequency distribution itself. For a 95 % confidence level, the computed confidence interval would include the true grain size parameter in 95 out of 100 trials, on average. The method presented here uses binomial theory to calculate a percentile confidence interval for each percentile of interest, then maps that confidence interval onto the cumulative frequency distribution of the sample in order to calculate the more useful grain size confidence interval. The validity of this approach is confirmed by comparing the predictions using binomial theory with estimates of the grain size confidence interval based on repeated sampling from a known population. We also developed a two-sample test of the equality of a given grain size percentile (e.g., D50), which can be used to compare different sites, sampling methods, or operators. The test can be applied with either individual or binned grain size data. These analyses are implemented in the freely available GSDtools package, written in the R language. A solution using the normal approximation to the binomial distribution is implemented in a spreadsheet that accompanies this paper. Applying our approach to various samples of grain size distributions in the field, we find that the standard sample size of 100 observations is typically associated with uncertainty estimates ranging from about ±15 % to ±30 %, which may be unacceptably large for many applications. In comparison, a sample of 500 stones produces uncertainty estimates ranging from about ±9 % to ±18 %. In order to help workers develop appropriate sampling approaches that produce the desired level of precision, we present simple equations that approximate the proportional uncertainty associated with the 50th and 84th percentiles of the distribution as a function of sample size and sorting coefficient; the true uncertainty in any sample depends on the shape of the sample distribution and can only be accurately estimated once the sample has been collected.

Quantitative habitat suitability models (HSMs) are frequently used to inform the conservation and management of lotic organisms, often in the context of instream flow management. Correlative statistical models relating hydraulic variables to habitat preferences (habitat suitability curves based on use:availability ratios) are the most common form of HSM, but face significant criticism on the grounds that habitat preference may not reflect the fitness consequences of habitat use. Consequently, there has been a drive to develop mechanistic approaches that link habitat to direct correlates of fitness. Bioenergetic foraging models relating hydraulic conditions to energy balance are particularly well‐developed for drift‐feeding fishes (e.g. salmonids) and show promise as a more mechanistic approach to modelling suitability. However, these models are rarely validated empirically or quantitatively compared with correlative HSMs. We addressed these gaps by comparing the ability of a bioenergetics‐based HSM and two correlative HSMs (a traditional suitability index and a resource selection function) to predict density and growth of stream salmonids (juvenile steelhead, Oncorhynchus mykiss, and coastal cutthroat trout, Oncorhynchus clarki). Suitability estimates differed between the approaches, with both correlative models predicting higher suitability relative to the bioenergetic model at shallow depths and low to intermediate velocities, but lower suitability as depth increased. The bioenergetic model explained over 90% of variation in trout growth, compared to c. 50% for the correlative model. The bioenergetic model was also better at predicting fish density; however, the improvement was less striking and a high proportion of variation remained unexplained by either method. Differences in suitability estimates between approaches probably reflect biotic interactions (e.g. territorial displacement or predation risk) that decouple realised habitat use from energetics‐based estimates of habitat quality. Results highlight fundamental differences between correlative HSMs, based on observed habitat use, and mechanistic HSMs, based on the physiology and behaviour of the focal taxa. They also suggest that mechanistic bioenergetics‐based models provide more rigorous estimates of habitat suitability for drift‐feeding stream fishes. The bioenergetics approach is readily accessible to instream flow practitioners because model predictions are expressed in terms of traditional habitat suitability curves.

Avulsion is a key process in building alluvial fans, but it is also a formidable natural hazard. Based on laboratory experiments monitored with novel high-frequency photogrammetry, we present a new model for avulsion on widely graded gravel fans. Previous experimental studies of alluvial fans have suggested that avulsion occurs in a periodic autogenic cycle, that is thought to be mediated by the gradient of the fan and fan-channel. However, these studies measured gradients at low spatial or temporal resolutions, which capture temporally or spatially averaged topographic evolution. Here, we present high-resolution (1 mm), high-frequency (1-minute) topographic data and orthophotos from an alluvial fan experiment. Avulsions in the experiment were rapid and, in contrast to some previous experimental studies, avulsion occurrence was aperiodic. Moreover, we found little evidence of the back-filling observed at coarser temporal and spatial resolutions. Our observations suggest that avulsion is disproportionately affected by sediment accumulation in the channel, particularly around larger, less mobile grains. Such in-channel deposition can cause channel shifting that interrupts the autogenic avulsion cycle, so that avulsions are aperiodic and their timing is more difficult to predict.

On steep alluvial fans, debris floods happen rarely but are often catastrophic. Debris floods and their associated hazards are well documented, but the time between flood events has generally been ...

It has been observed that the relation between sediment storage and sediment transport rate in gravel-bed rivers exhibits counter-clockwise hysteresis, or aggradation-degradation cycles. Previous work has attributed these cycles to external changes to the sediment supply rate. We present a set of nine flume experiments that test the hypothesis that aggradation-degradation cycles can occur even under steady sediment supply conditions when the sediment transport rate temporarily nears the sediment supply rate. The experiments are designed to examine the transport-storage relations under a range of conditions with different initial bed condition, sediment supply rate, discharge, and supply material texture. The sediment transport efficiency of the experimental channel was strongly influenced by the existing bed morphology inherited from historical flows. The discharge and grain size distribution of the supply material played a secondary role, with higher discharge conditions and finer sediment feed material producing increased transport efficiencies. The transport-storage relations revealed that the transport rate of the channel changed with the volume of sediment stored and was, therefore, mediated by the channel morphology. Aggradation-degradation cycles were observed even under steady sediment supply and discharge conditions and were mediated by morphologic adjustments within the channel that temporarily led the transport rate to be near equal to the sediment supply rate. In other words, the probability of hysteresis in the transport-storage relation increases when the channel is near a transport equilibrium. The findings demonstrate the complexity associated with developing a unique relation between sediment transport and storage in gravel-bed rivers, and highlights the importance of considering the morphologic evolution and historical bed conditions.

While the stabilizing function of large grains in step-pool streams has long been recognized, the role they play in gravel-bed streams is less clear. Most researchers have ignored the role of large grains in gravel-bed streams, and have assumed that the median bed surface size controls the erodibility of alluvial boundaries. The experiments presented herein challenge this convention. Two experiments were conducted that demonstrate the significant morphodynamic implications of a slight change to the coarse tail of the bed material. The two distributions had the same range of particle sizes, and nearly identical bulk d50 values (1.6 mm); however the d90 of experiment GSD1 was slightly finer (3.7 mm) than that for experiment GSD2 (3.9 mm). Transport rates during GSD1 were nearly four times greater than during GSD2 (even though the dimensionless shear stress was slightly lower), and the channel developed a sinuous pattern with well-developed riffles, pools and bars. During GSD2 the initial rectangular channel remained virtually unchanged for the duration of the experiment. The relative stability of GSD2 seems to be associated with a slightly larger proportion of stable (large) grains on the bed surface: at the beginning of GSD1, 3.5% of the bed was immobile, while almost twice as much of it (6.1%) was immobile at the beginning of GSD2. The results demonstrate that the largest grains (not the median size) exert first-order control on channel stability. Copyright © 2017 John Wiley & Sons, Ltd.

It is understood that the interaction between sediment supply and discharge drives first-order behaviour of deposits. The influence of the grain size distribution shape over the mobility and resultant evolution is, however, unclear. Four experiments were conducted in a scaled physical model for two grain size distributions, analogous to a one-dimensional self-formed alluvial fan. We demonstrate the unsuitability of the median grain size as a predictor of deposit behaviour at flows when the material is not equally mobile. The results instead suggest, during conditions of unequal mobility, that largest grains control the transport efficiency of the overall sediment mixture, and thus also the morphodynamics of the deposit and its tendency to store or evacuate material. Deposits appear to show a dependence upon the rate of material supply more strongly when the likelihood of its motion is less equally distributed (i.e., under partial transport conditions). If the coarse fraction (e.g., greater than 84th percentile) is instead mobile due to increased discharge or because of their relative size, transport rates will increase and the behaviour of the mixtures converge to a common state, with morphology influenced by the material's mobility.

Most studies of gravel bed rivers present at least one bed surface grain size distribution, but there is almost never any information provided about the uncertainty of the percentile estimates. We present a simple method for estimating the confidence intervals about the grain size percentiles derived from standard Wolman or pebble count samples of bed surface texture. Our approach uses binomial probability theory to generate confidence intervals for all grain sizes in the distribution. We find that the standard sample size of 100 observations is associated with errors ranging from about ±15 % to ±30 %, which may be unacceptably large for many applications. In comparison, a sample of 500 stones produces an uncertainty ranging from about ±9 % to ±18 %. In order to help workers develop appropriate sampling approaches that produce the desired level of precision, we present simple equations that approximate the proportional uncertainty associated with the median size and the 84th percentile of the distribution as a function of the sample size and the standard deviation of the distribution, assuming that the underlying distribution is log-normal. However, the true uncertainty of any sample can only be accurately estimated once the sample has been collected, so these simple equations complement – but do not replace – the basic uncertainty analysis using binomial probability theory.

We illustrate an approach to quantify patterns in hydraulic habitat composition and local heterogeneity applicable at low cost over very large river extents, with selectable reach window scales. Ongoing developments in remote sensing and geographical information science massively improve efficiencies in analyzing earth surface features. With the development of new satellite sensors and drone platforms and with the lowered cost of high resolution multispectral imagery, fluvial geomorphology is experiencing a revolution in mapping streams at high resolution. Exploiting the power of aerial or satellite imagery is particularly useful in a riverscape research framework (Fausch et al., 2002), where high resolution sampling of fluvial features and very large coverage extents are needed. This study presents a satellite remote sensing method that requires very limited field calibration data to estimate over various scales ranging from 1 m to many tens or river kilometers (i) spatial composition metrics for key hydraulic mesohabitat types and (ii) reach-scale wetted habitat heterogeneity indices such as the hydromorphological index of diversity (HMID). When the purpose is hydraulic habitat characterization applied over long river networks, the proposed method (although less accurate) is much less computationally expensive and less data demanding than two dimensional computational fluid dynamics (CFD). Here, we illustrate the tools based on a Worldview 2 satellite image of the Kiamika River, near Mont Laurier, Quebec, Canada, specifically over a 17-km river reach below the Kiamika dam. In the first step, a high resolution water depth (D) map is produced from a spectral band ratio (calculated from the multispectral image), calibrated with limited field measurements. Next, based only on known river discharge and estimated cross section depths at time of image capture, empirical-based pseudo-2D hydraulic rules are used to rapidly generate a two-dimensional map of flow velocity (V) over the 17-km Kiamika reach. The joint distribution of D and V variables over wetted zones then is used to reveal structural patterns in hydraulic habitat availability at patch, reach, and segment scales. Here we analyze 156 bivariate (D, V) density function plots estimated over moving reach windows along the satellite scene extent to extract 14 physical habitat metrics (such as river width, mean and modal depths and velocity, variances and covariance in D and V over 1-m pixels, HMID, entropy). A principal component analysis on the set of metrics is then used to cluster river reaches in regard to similarity in their hydraulic habitat composition and heterogeneity. Applications of this approach can include (i) specific fish habitat detection at riverscape scales (e.g., large areas of riffle spawning beds, deeper pools) for regional management, (ii) studying how river habitat heterogeneity is correlated to fish distribution and (iii) guidance for site location for restoration of key habitats or for post regulation monitoring of representative reaches of various types.

Large wood has historically been removed from streams, resulting in the depletion of in-stream wood in waterways worldwide. As wood increases morphological and hydraulic complexity, the addition of large wood is commonly employed as a means to rehabilitate in-stream habitat. At present, however, the scientific understanding of wood mobilization and transport is incomplete. This paper presents results from a series of four flume experiments in which wood was added to a reach to investigate the piece and reach characteristics that determine wood stability and transport, as well as the time scale required for newly recruited wood to self-organize into stable jams. Our results show that wood transitions from a randomly distributed newly recruited state to a self-organized, or jam-stabilized state, over the course of a single bankfull flow event. Statistical analyses of piece mobility during this transitional period indicate that piece irregularities, especially rootwads, dictate the stability of individual wood pieces; rootwad presence or absence accounts for up to 80% of the variance explained by linear regression models for transport distance. Furthermore, small pieces containing rootwads are especially stable. Large ramped pieces provide nuclei for the formation of persistent wood jams, and the frequency of these pieces in the reach impacts the travel distance of mobile wood. This research shows that the simulation of realistic wood dynamics is possible using a simplified physical model, and also has management implications, as it suggests that randomly added wood may organize into persistent, stable jams, and characterizes the time scale for this transition.

Large wood governs channel morphology, as well as the availability of in-stream habitat, in many forested streams. In this paper, we use a stochastic, physically based model to simulate wood recruitment and in-stream geomorphic processes, in order to explore the influence of disturbance history on the availability of aquatic habitat. Specifically, we consider the effects of fire on a range of stream sizes by varying the rate of tree toppling over time in a simulated forest characterized by a tree height of 30 m. We also consider the effects of forest harvesting with various riparian buffer sizes, by limiting the lateral extent of the riparian stand. Our results show that pulsed inputs of wood increase the availability and variability of physical habitat in the postfire period; reach-averaged pool area and deposit area double in small streams, while side channels increase by over 50% in intermediate-sized channels. By contrast, forest harvesting reduces the availability of habitat within the reach, though the effects diminish with increasing buffer size or stream width; in laterally stable streams the effects are minimal so long as buffer width is large enough for key pieces to be recruited to the reach. This research emphasizes the importance of natural disturbance in creating and maintaining habitat heterogeneity and shows that scenario-based numerical modeling provides a useful tool for assessing the historical range of variability associated with natural disturbance, as well as changes in habitat relevant to fish. It can be also used to inform forest harvesting and management.

The effects of large floods on river morphology are variable and poorly understood. In this study, we apply multi-temporal datasets collected with small unmanned aircraft systems (UASs) to analyze three-dimensional morphodynamic changes associated with an extreme flood event that occurred from 19 to 23 June 2013 on the Elbow River, Alberta. We documented reach-scale spatial patterns of erosion and deposition using high-resolution (4–5 cm/pixel) orthoimagery and digital elevation models (DEMs) produced from photogrammetry. Significant bank erosion and channel widening occurred, with an average elevation change of −0.24 m. The channel pattern was reorganized and overall elevation variation increased as the channel adjusted to full mobilization of most of the bed surface sediments. To test the extent to which geomorphic changes can be predicted from initial conditions, we compared shear stresses from a two-dimensional hydrodynamic model of peak discharge to critical shear stresses for bed surface sediment sizes. We found no relation between modeled normalized shear stresses and patterns of scour and fill, confirming the complex nature of sediment mobilization and flux in high-magnitude events. However, comparing modeled peak flows through the pre- and post-flood topography showed that the flood resulted in an adjustment that contributes to overall stability, with lower percentages of bed area below thresholds for full mobility in the post-flood geomorphic configuration. Overall, this work highlights the potential of UAS-based remote sensing for measuring three-dimensional changes in fluvial settings and provides a detailed analysis of potential relationships between flood forces and geomorphic change. Copyright © 2015 John Wiley & Sons, Ltd.

Experiments using a 1∶30 scale physical model show that channel degradation on alluvial fans is dominated by lateral channel migration rather than vertical incision. The results are used to...