Evaluating river morphology change with a geomorphic form variation approach

Geomorphic river design strives for natural resilience by encouraging geomorphic form complexity and morphological processes linked to greater habitat diversity. Increasing availability of high-resolution topographic data and spatial feature mapping methods provide advantages for morphological analysis and river restoration planning. We propose and evaluate an approach to quantifying topographic variability of geomorphic form and pixel-level surface roughness resulting from channel planform geometry differences using spatially continuous variety computation applied to component metrics including flow direction, aspect and planform curvature. We define this as the geomorphic form variation (GFV) approach and found it scalable, repeatable and a multi-stage analytical metric for quantifying physical aspects of river-bed topographic variability. GFV may complement process-based morphological feature mapping applications, hydraulic assessment indices and spatial habitat heterogeneity metrics commonly used for ecological quality evaluation and river restoration. The GFV was tested on controlled synthetic channels derived from River Builder software and quasi-controlled sinuous planform flume experiment channels. Component variety metrics respond independently to specific geometric surface changes and are sensitive to multi-scaled morphology change, including coarser-grained sediment distributions of pixel-level surface roughness. GFV showed systematic patterns of change related to the effects of channel geometry, vertical bed feature (pool-bar) frequency and amplitude, and bar size, shape and orientation. Hotspot analysis found that bar margins were major components of topographic complexity, whereas grain-scale variety class maps further supported the multi-stage analytical capability and scalability of the GFV approach. The GFV can provide an overall variety value that may support river restoration decision-making and planning, particularly when geomorphic complexity enhancement is a design objective. Analysing metric variety values with statistically significant hotspot cluster maps and complementary process-based software and mapping applications allows variety correspondence to systematic feature changes to be assessed, providing an analytical approach for river morphology change comparison, channel design and geomorphic process restoration.     

Bedform effect on the reorganization of surface and subsurface grain size distribution in gravel bedded channels

Quantification of river bedform variability and complexity is important for sediment transport modeling as well as for characterization of river morphology. Alluvial bedforms are shown to exhibit highly nonlinear dynamics across a range of scales, affect local bed roughness, and vary with local hydraulic, hydrologic, and geomorphic properties. This paper examines sediment sorting on the crest and trough of gravel bedforms and relates it to bed elevation statistics. The data analysed here are the spatial and temporal series of bed elevation, grain size distribution of surface and subsurface bed materials, and sediment transport rates from flume experiments. We describe surface topography through bedform variability in height and wavelength and multiscale analysis of bed elevations as a function of discharge. We further relate bedform migration to preferential distribution of coarse and fine sediments on the troughs and crests, respectively, measuring directly surface and subsurface grain size distributions, and indirectly the small scale roughness variations as estimated from high resolution topographic scans.     

Wavelet Characteristics of Hydrological and Dissolved Oxygen Time Series in a Lowland River

In this study, we investigated the temporal variability of dissolved oxygen and water temperature in conjunction with water level fluctuations and river discharge in the Narew lowland river reach. For this purpose, high resolution hydrologic and water quality time series have been used. Spectral analyses of time series using continuous wavelet transform scheme have been applied in order to identify characteristic scales, its duration, and localisation in time. The results of wavelet analysis have shown a great number of periodicities in time series at the inter-annual time scale when compared to the classical Fourier analysis. Additionally, wavelet coherence revealed the complex nature of the relationship between dissolved oxygen and hydrological variables dependent on the scale and localisation in time. Hence, the results presented in this paper may provide an alternative representation to a frequency analysis of time series.     

Flood‐driven topographic changes in a gravel‐cobble river over segment,reach, and morphological unit scales

Regulated rivers generally incise below dams that cut off sediment supply, but how that happens and what the consequences are at different spatial scales is poorly understood. Modern topographic mapping at meter‐scale resolution now enables investigation of the details of spatial processes. In this study, spatial segregation was applied to a meter‐scale raster map of topographic change from 1999 to 2008 on the gravel‐cobble, regulated lower Yuba River in California to answer specific scientific questions about how a decadal hydrograph that included a flood peak of 22 times bankfull discharge affected the river at segment, reach, and morphological unit scales. The results show that the river preferentially eroded sediment from floodplains compared to the channel, and this not only promoted valley‐wide sediment evacuation, but also facilitated the renewal and differentiation of morphological units, especially in the channel. At the reach scale, area of fill and mean net rate of elevational change were directly correlated with better connectivity between the channel and floodplain, while the mean rate of scour in scour areas was influenced by the ratio of slope to bankfull Froude number, a ratio indicative of lateral migration versus vertical downcutting. Hierarchical segregation of topographic change rasters proved useful for understanding multi‐scalar geomorphic dynamics. Copyright © 2016 John Wiley & Sons, Ltd.     

Hierarchically nested river landform sequences. Part 1: Theory

Past river classifications use incommensurate typologies at each spatial scale and do not capture the pivotal role of topographic variability at each scale in driving the morphodynamics responsible for evolving hierarchically nested fluvial landforms. This study developed a new way to create geomorphic classifications using metrics diagnostic of individual processes the same way at every spatial scale and spanning a wide range of scales. We tested the approach on flow convergence routing, a geomorphically and ecologically important process with different morphodynamic states of erosion, routing, and deposition depending on the structure of nondimensional topographic variability. Five nondimensional landform types with unique functionality represent this process at any flow; they are nozzle, wide bar, normal channel, constricted pool, and oversized. These landforms are then nested within themselves by considering their longitudinal sequencing at key flows representing geomorphically important stages. A data analysis framework was developed to answer questions about the stage‐dependent spatial structure of topographic variability. Nesting permutations constrain and reveal how flow convergence routing morphodynamics functions in any river the framework is applied to. The methodology may also be used with other physical and biological datasets to evaluate the extent to which the patterning in that data is influenced by flow convergence routing. Copyright © 2018 John Wiley & Sons, Ltd.     

What should these rivers look like? Historical range of variability and human impacts in the Colorado Front Range,USA

Historical range of variability (HRV) describes the range of temporal and spatial variations in river variables such as flow regime or channel planform prior to intensive human alteration of the ecosystem. In mountainous river networks, HRV is most usefully applied to spatially differentiated geomorphic process domains with distinctive form and process. Using the Colorado Front Range as an example, three examples of how knowledge of HRV can assist river management and restoration are discussed. The examples involve instream wood load and channel morphology, beaver colonies and valley‐bottom form and process, and flow thresholds in regulated rivers. The question of what a river should look like – that is, what range of process and form the river included prior to intensive human alteration – can be addressed by (i) placing the river within a process domain, (ii) establishing correlations between form parameters that can be remotely sensed and reach‐scale process and form, so that the spatial extent, connectivity, and rarity of process domains within a river network or a region can be quickly assessed, (iii) inferring characteristics of the river prior to intensive alteration by documenting characteristics of the least altered reference rivers and by using proxy indicators of pre‐alteration conditions, and (iv) establishing process thresholds that must be exceeded to maintain form (e.g. flow thresholds to mobilize bed sediment). Once this context has been established, resource managers can better evaluate the options for restoring altered riverine form and function. Copyright © 2011 John Wiley & Sons, Ltd.     

Bridging the gap between turbulence and larger scales of flow motions in rivers

Although flow turbulence in rivers is of critical importance to earth scientists, ecologists and engineers, its relations with larger flow scales are not well understood, thus leaving a fundamental gap in our knowledge. From an analysis of a long time series of the streamwise and vertical flow velocity fluctuations measured in a gravel‐bed river, we show that the signature of the fundamental turbulent flow structures (e.g. ejections and sweeps) is embedded within increasingly larger flow scales in a self‐similar manner. The imbrication of turbulent structures into large flow pulsations of flow acceleration and deceleration covers more than two‐orders of magnitude from a few seconds to nearly 10 minutes. This property is explained by the clustering of turbulent events creating an emergent pattern at larger scales. The size of the larger flow pulsations scales with the spacing of the pools and riffles in the river. This implies a mutual adjustment between turbulence generation mechanisms and long pulsations of flow acceleration and deceleration controlled by the bed morphology. These results bridge a gap in our understanding of flows in rivers and offer a new perspective on the interactions between the turbulent flow with larger scales of flow motion that are critical for sediment transport, habitat selection and fish behaviour. Copyright © 2011 John Wiley & Sons, Ltd.     

Regional hydromorphological characterization with continuous and automated remote sensing analysis based on VHR imagery and low‐resolution LiDAR data

Recent developments in remote sensing (RS) technologies lead the way in characterizing river morphology at regional scales and inferring potential channel responses to human pressures. In this paper, a unique regional database of continuous hydromorphological variables (HyMo DB) based on areal and topographic data has been generated from RS analysis. Key riverscape units with specific geomorphic meaning have been automatically mapped for 1700 km² of river floodplains from simultaneous very‐high‐resolution (VHR) near‐infrared aerial imagery and low‐resolution LiDAR‐derived products. A multi‐level, geographical object‐based architecture (GEOBIA) was employed to integrate both spectral and topographic information and generate a regional classifier able to automatically map heterogeneous fluvial patterns in different geographical and topographical contexts of the Piedmont Region (Italy). This HyMo‐generated DB offers a unique set of tools for hydromorphologists and can be exploited for different purposes. For the first time, topographic information can be exploited regionally per riverscape unit class, allowing for quantitative analysis of their regional spatial and statistical variability. In this manner, river types can be automatically characterized and classified using objective and repeatable hydromorphological variables. We discuss the potential of quantifying functional links between riverscape units and their driving processes, a valuable source of information to start assessing and highlighting the entity of potential channel adjustments at the regional scale to human pressures. The HyMo DB can also be integrated with historical, field‐based information to better comprehend current fluvial changes at a local scale. In view of future RS acquisitions, the present approach will result in a suitable procedure for quantitative, objective and continuous monitoring of river evolutions over large scales. This type of hydromorphological characterization will allow regional trends and patterns to be highlighted through time and river management strategies to thus be implemented at both regional and local scales. Copyright © 2016 John Wiley & Sons, Ltd.     

The use of multivariate statistics to elucidate patterns of floodplain sedimentation at different spatial scales

Floodplains are depositional features of riverine landscapes that display complex sedimentation patterns that are amenable to multi‐scale approaches. We examined sedimentation in the Lower Balonne floodplain, Queensland, Australia, at three different spatial scales: the channel (10³ km), floodplain process zone (10 km) and geomorphic unit (10² m) scales, and compared scale‐related patterns evident from stratigraphy with those evident from quantitative multivariate analysis. Three stratigraphic sequences were found in the Lower Balonne floodplain: generally fining upward, episodic fining upward, and mud‐dominated. Stratigraphical analysis revealed the detailed character of sedimentary sequences embedded within the scale patterns derived from multivariate analysis. Multivariate statistical analyses of a range of textural and geochemical data revealed different patterns of floodplain sedimentation at each scale. At the channel scale, sediment texture and geochemistry were more heterogeneous in the Culgoa River than in Briarie Creek. At the floodplain process zone scale clear patterns of sediment texture and geochemistry were observed along the upper, mid and lower floodplain process zones of Briarie Creek, but not along the Culgoa River. At the geomorphic unit scale, clear patterns of sediment texture and geochemistry were observed among the bank, buried channel and flat floodplain units of the Culgoa River, but were not as clear in Briarie Creek. Recognition of rivers as hierarchically organized systems is an emerging paradigm in river science. Our study supports this paradigm by demonstrating that different sedimentation patterns occur at different scales to reveal a hierarchically organized floodplain environment. Copyright © 2006 John Wiley & Sons, Ltd.     

A field‐based investigation to examine underwater soundscapes of five common river habitats

Aquatic river habitat types have been characterized and classified for over five decades based on hydrogeomorphic and ecological variables. However, few studies considered the generation of underwater sound as a unique property of aquatic habitats, and therefore as a potential information source for freshwater organisms. In this study, five common habitat types along 12 rivers in Switzerland (six replicates per habitat type) were acoustically compared. Acoustic signals were recorded by submerging two parallel hydrophones and were analysed by calculating the energetic mean as well as the temporal variance of ten octave bands (31·5 Hz–16 kHz). Concurrently, each habitat type was characterized by hydraulic and geomorphic variables, respectively. The average relative roughness, velocity‐to‐depth ratio, and Froude number explained most of the variance of the acoustic signals created in different habitat types. The average relative roughness predominantly affected middle frequencies (63 Hz–1 kHz), while streambed sediment transport increased high‐frequency sound pressure levels (2–16 kHz) as well as the temporal variability of the recorded signal. Each aquatic habitat type exhibited a distinct acoustic signature or soundscape. These soundscapes may be a crucial information source for many freshwater organisms about their riverine environment. Copyright © 2010 John Wiley & Sons, Ltd.     

Mapping hydraulic biotopes using terrestrial laser scan data of water surface properties

For more than a decade, habitat mapping using biotopes (in‐channel hydraulically‐defined habitats) has underpinned aquatic conservation in the UK through (a) providing baseline information on system complexity and (b) allowing environmental and ecological change to be monitored and evaluated. The traditional method used is the subjective river habitat or corridor survey. This has recently been revised to include the floodplain via GeoRHS, but issues still exist concerning development of a national database due to the labour intensive nature of the data collection, subjectivity issues between samplers, temporal changes, the fuzzy nature of perceived habitats and habitat boundaries. This paper takes an innovative approach to biotope definition using high resolution spatial data to define water surface roughness for two representative reaches of the River South Tyne, Cumbria, and the River Rede, Northumberland, UK. Data was collected using a terrestrial laser scanner (TLS) and hydraulic variability simply expressed through assigning a local standard deviation value to a set of adjacent water surface values. Statistical linkage of these data with biotope locations defined visually in the field allowed complete mapping of the surveyed reach defining habitat and biotope areas to the fine scale resolution of the TLS data. Despite issues of data loss due to absorption and transmission through the water, the reflected signal generated an extremely detailed and objective map of the water surface roughness, which may be compared with known biotope locations as defined by visual identification in the field. The TLS accuracy achieved in the present study is comparable with those obtained using hyperspectral imagery: with 84% of the pool/glide/marginal deadwater amalgamated biotope, 88% of riffles, 57% of runs and 50% of the amalgamated cascade/rapid biotope successfully plotted. It is clear from this exercise that biotope distribution is more complex than previously mapped using subjective techniques, and based upon the water surface roughness delimiters presented in this study, the amalgamation of pools with glides and marginal deadwaters, riffles with unbroken standing waves, and cascades with rapids, is proposed. Copyright © 2010 John Wiley & Sons, Ltd     

Influence of river channel morphology and bank characteristics on water surface boundary delineation using high‐resolution passive remote sensing and template matching

Accurate mapping of water surface boundaries in rivers is an important step for monitoring water stages, estimating discharge, flood extent, and geomorphic response to changing hydrologic conditions, and assessing riverine habitat. Nonetheless, it is a challenging task in spatially and spectrally heterogeneous river environments, commonly characterized by high spatiotemporal variations in morphology, bed material, and bank cover. In this study, we investigate the influence of channel morphology and bank characteristics on the delineation of water surface boundaries in rivers using high spatial resolution passive remote sensing and a template‐matching (object‐based) algorithm, and compare its efficacy with that of Support Vector Machine (SVM) (pixel‐based) algorithm. We perform a detailed quantitative evaluation of boundary‐delineation accuracy using spatially explicit error maps in tandem with the spatial maps of geomorphic and bank classes. Results show that template matching is more successful than SVM in delineating water surface boundaries in river sections with spatially challenging geomorphic landforms (e.g. sediment bar structures, partially submerged sediment deposits) and shallow water conditions. However, overall delineation accuracy by SVM is higher than that of template matching (without iterative hierarchical learning). Vegetation and water indices, especially when combined with texture information, improve the accuracy of template matching, for example, in river sections with overhanging trees and shadows – the two most problematic conditions in water surface boundary delineation. By identifying the influence of channel morphology and bank characteristics on water surface boundary mapping, this study helps determine river sections with higher uncertainty in delineation. In turn, the most suitable methods and data sets can be selectively utilized to improve geomorphic/hydraulic characterization. The methodology developed here can also be applied to similar studies on other geomorphic landforms including floodplains, wetlands, lakes, and coastlines. Copyright © 2014 John Wiley & Sons, Ltd.     

Basin‐scale methods for predicting salmonid spawning habitat via grain size and riffle spacing,tested in a California coastal drainage

Basin‐scale predictive geomorphic models for river characteristics, particularly grain size, can aid in salmonid habitat identification. However, these basin‐scale methods are largely untested with actual habitat usage data. Here, we develop and test an approach for predicting grain size distributions from high resolution LiDAR (Light Detection and Ranging)‐derived topographic data for a 77 km² watershed along the central California Coast. This approach improves on previous efforts in that it predicts the full grain size distribution and incorporates an empirically calibrated shear stress partitioning factor. The predicted grain size distributions are used to calculate the fraction of the bed area movable by spawning fish. We then compare the ‘movable fraction’ with 7 years of observed spawning data. We find that predicted movable fraction explains the paucity of spawning in the upper reaches of the study drainage, but does not explain variation along the mainstem. In search of another morphologic characteristic that may help explain the variation within the mainstem, we measure riffle density, a proxy for physical habitat complexity. We find that field surveys of riffle density explain 64% of the variation in spawning in these mainstem reaches, suggesting that within reaches of appropriate sized gravel, spawning density is related to riffle density. Because riffle density varies systematically with channel width, predicting riffle spacing is straightforward with LiDAR data. Taken together, these findings demonstrate the efficacy of basin‐scale spawning habitat predictions made using high‐resolution digital elevation models. Copyright © 2016 John Wiley & Sons, Ltd.     

Snowpack variability across various spatio‐temporal resolutions

High‐resolution snow depth (SD) maps (1 × 1 m) obtained from terrestrial laser scanner measurements in a small catchment (0.55 km²) in the Pyrenees were used to assess small‐scale variability of the snowpack at the catchment and sub‐grid scales. The coefficients of variation are compared for various plot resolutions (5 × 5, 25 × 25, 49 × 49, and 99 × 99 m) and eight different days in two snow seasons (2011–2012 and 2012–2013). We also studied the relation between snow variability at the small scale and SD, topographic variables, small‐scale variability in topographic variables. The results showed that there was marked variability in SD, and it increased with increasing scales. Days of seasonal maximum snow accumulation showed the least small‐scale variability, but this increased sharply with the onset of melting. The coefficient of variation (CV) in snowpack depth showed statistically significant consistency amongst the various spatial resolutions studied, although it declined progressively with increasing difference between the grid sizes being compared. SD best explained the spatial distribution of sub‐grid variability. Topographic variables including slope, wind sheltering, sub‐grid variability in elevation, and potential incoming solar radiation were also significantly correlated with the CV of the snowpack, with the greatest correlation occurring at the 99 × 99 m resolution. At this resolution, stepwise multiple regression models explained more than 70% of the variance, whereas at the 25 × 25 m resolution they explained slightly more than 50%. The results highlight the importance of considering small‐scale variability of the SD for comprehensively representing the distribution of snowpack from available punctual information, and the potential for using SD and other predictors to design optimized surveys for acquiring distributed SD data. Copyright © 2014 John Wiley & Sons, Ltd.     

Application of globally available,coarse-resolution digital elevation models for delineating valley bottom segments of varying length across a catchment

The worldwide availability of digital elevation models (DEMs) has enabled rapid (semi-)automated mapping of earth surface landforms. In this paper, we first present an approach for delineating valley bottom extent across a large catchment using only publicly available, coarse-resolution DEM input. We assess the sensitivity of our results to variable DEM resolution and find that coarse-resolution datasets (90 m resolution) provide superior results. We also find that LiDAR-derived DEMs produce more realistic results than satellite-derived DEMs across the full range of topographic settings tested. Satellite-derived DEMs perform more effectively in moderate topographic settings, but fail to capture the subtleties of valley bottom extent in mild gradient, low-lying topography and in narrow headwater reaches. Second, we present a semi-automated technique within ArcGIS for delineating valley bottom segments using DEM-derived network scale metrics of valley bottom width and slope. We use an unsupervised machine-learning technique based on the k-means clustering algorithm to solve a conundrum in GIS-based geomorphic analysis of rivers: the delineation of valley bottom segments of variable length. The delineation of valley bottom segments provides a coarse-scale entry point into automated geomorphic analysis and characterization of river systems. © 2020 John Wiley & Sons, Ltd.     

Impact of flow variability on the morphology of a low-energy meandering river

Few studies have precisely documented the response of stream channels to short-term flow variability. This paper examines the impact of sequential flows of various magnitudes on the morphology of a low-energy river in northeastern Illinois, U.S.A. Between June 1986 and November 1988 channel cross-sections were surveyed on a semiannual basis at 26 locations along a 7.2 km stretch of the Des Plaines River. During this period an estimated 100-year flood, several bankfull flows, and an extreme low flow associated with a severe drought occurred. The response of the river channel to each of these events was relatively minor. Mean changes for the reach were generally less than 3 per cent for mean depth and less than 1 per cent for width. Statistical analysis indicates that net changes in width and depth over the entire period were not significantly different from zero. This lack of geomorphic response is attributable to low stream power, low hydrologic variability, fine bed materials, and cohesive banks along this stretch of river. Although dramatic changes in channel morphology did not occur, subtleties in geomorphic response were observed that reflect the temporal ordering of hydrologic events.     

Experimental field assessment of suspended sediment pathways for characterizing hydraulic habitat

The distribution of particulate matter within river channels, including sediments, nutrients and pollutants, is fundamental to the survival of aquatic organisms. However, the interactions between flow and sediment transport at the patch scale of river systems represents an under‐researched component of physical habitat studies, particularly those concerning the characterization of ‘physical biotopes’ (riffles, runs, pools, glides). This paper describes a field methodology for exploring the transfer of particulate matter at small scales within river channels, which may be used to aid hydraulic habitat characterization. The field protocol combines field measurement of high frequency flow properties, to characterize hydraulic habitat units, and deployment of spatial arrays of turbidity probes, to detect the passage of artificially‐induced sediment plumes through different biotope units. Sediment plumes recorded by the probes are analysed quantitatively in the manner of the flood hydrograph, and qualitative inferences are made on the dominant mixing processes operating within different parts of the channel. Relationships between the nature of spatio‐temporal hydraulic variations within glide, riffle and pool biotopes, and the character and mixing behaviour of sediment plumes within these habitat units are identified. Results from these preliminary experiments suggest that investigating and characterizing the transfer and storage of sediments, nutrients and pollutants within and between different biotopes is a viable avenue for further research, with potential to contribute to improved physical habitat characterization for river management and habitat restoration. The experiments are also an illustration of the value of neglected synergies between process geomorphology, ecology and river hydraulics. Copyright © 2010 John Wiley & Sons, Ltd.     

Geomorphic process from topographic form: automating the interpretation of repeat survey data in river valleys

The ability to quantify the processes driving geomorphic change in river valley margins is vital to geomorphologists seeking to understand the relative role of transport mechanisms (e.g. fluvial, aeolian, and hillslope processes) in landscape dynamics. High‐resolution, repeat topographic data are becoming readily available to geomorphologists. By contrasting digital elevation models derived from repeat surveys, the transport processes driving topographic changes can be inferred, a method termed ‘mechanistic segregation.’ Unfortunately, mechanistic segregation largely relies on subjective and time consuming manual classification, which has implications both for its reproducibility and the practical scale of its application. Here we present a novel computational workflow for the mechanistic segregation of geomorphic transport processes in geospatial datasets. We apply the workflow to seven sites along the Colorado River in the Grand Canyon, where geomorphic transport is driven by a diverse suite of mechanisms. The workflow performs well when compared to field observations, with an overall predictive accuracy of 84% across 113 validation points. The approach most accurately predicts changes due to fluvial processes (100% accuracy) and aeolian processes (96%), with reduced accuracy in predictions of alluvial and colluvial processes (64% and 73%, respectively). Our workflow is designed to be applicable to a diversity of river systems and will likely provide a rapid and objective understanding of the processes driving geomorphic change at the reach and network scales. We anticipate that such an understanding will allow insight into the response of geomorphic transport processes to external forcings, such as shifts in climate, land use, or river regulation, with implications for process‐based river management and restoration. Copyright © 2017 John Wiley & Sons, Ltd.     

Stream flow characterization and feature detection using a discrete wavelet transform

An exploration of the wavelet transform as applied to daily river discharge records demonstrates its strong potential for quantifying stream flow variability. Both periodic and non-periodic features are detected equally, and their locations in time preserved. Wavelet scalograms often reveal structures that are obscure in raw discharge data. Integration of transform magnitude vectors over time yields wavelet spectra that reflect the characteristic time-scales of a river's flow, which in turn are controlled by the hydroclimatic regime. For example, snowmelt rivers in Colorado possess maximum wavelet spectral energy at time-scales on the order of 4 months owing to sustained high summer flows; Hawaiian streams display high energies at time-scales of a few days, reflecting the domination of brief rainstorm events. Wavelet spectral analyses of daily discharge records for 91 rivers in the US and on tropical islands indicate that this is a simple and robust way to characterize stream flow variability. Wavelet spectral shape is controlled by the distribution of event time-scales, which in turn reflects the timing, variability and often the mechanism of water delivery to the river. Five hydroclimatic regions, listed here in order of decreasing seasonality and increasing pulsatory nature, are described from the wavelet spectral analysis: (a) western snowmelt, (b) north-eastern snowmelt, (c) mid-central humid, (d) south-western arid and (e) ‘rainstorm island’. Spectral shape is qualitatively diagnostic for three of these regions. While more work is needed to establish the use of wavelets for hydrograph analysis, our results suggest that river flows may be effectively classified into distinct hydroclimatic categories using this approach. © 1998 John Wiley & Sons, Ltd.     

Dissecting the effect of rainfall variability on the statistical structure of peak flows

This study examines the role of rainfall variability on the spatial scaling structure of peak flows using the Whitewater River basin in Kansas as an illustration. Specifically, we investigate the effect of rainfall on the scatter, the scale break and the power law (peak flows vs. upstream areas) regression exponent. We illustrate why considering individual hydrographs at the outlet of a basin can lead to misleading interpretations of the effects of rainfall variability. We begin with the simple scenario of a basin receiving spatially uniform rainfall of varying intensities and durations and subsequently investigate the role of storm advection velocity, storm variability characterized by variance, spatial correlation and intermittency. Finally, we use a realistic space–time rainfall field obtained from a popular rainfall model that combines the aforementioned features. For each of these scenarios, we employ a recent formulation of flow velocity for a network of channels, assume idealized conditions of runoff generation and flow dynamics and calculate peak flow scaling exponents, which are then compared to the scaling exponent of the width function maxima. Our results show that the peak flow scaling exponent is always larger than the width function scaling exponent. The simulation scenarios are used to identify the smaller scale basins, whose response is dominated by the rainfall variability and the larger scale basins, which are driven by rainfall volume, river network aggregation and flow dynamics. The rainfall variability has a greater impact on peak flows at smaller scales. The effect of rainfall variability is reduced for larger scale basins as the river network aggregates and smoothes out the storm variability. The results obtained from simple scenarios are used to make rigorous interpretations of the peak flow scaling structure that is obtained from rainfall generated with the space–time rainfall model and realistic rainfall fields derived from NEXRAD radar data.