Geology topics

Carl J. Legleiter

Publications and source records attributed to Carl J. Legleiter.

66 records · Page 4Linked to original sources

USGS2017

A framework for modeling connections between hydraulics, water surface roughness, and surface reflectance in open channel flows

This paper introduces a framework for examining connections between the flow field, the texture of the air-water interface, and the reflectance of the water surface and thus evaluating the potential to infer hydraulic information from remotely sensed observations of surface reflectance. We used a spatial correlation model describing water surface topography to illustrate the application of our framework. Nondimensional relations between model parameters and flow intensity were established based on a prior flume study. Expressing the model in the spatial frequency domain allowed us to use an efficient Fourier transform-based algorithm for simulating water surfaces. Realizations for both flume and field settings had water surface slope distributions positively correlated with velocity and water surface roughness. However, most surface facets were gently sloped and thus unlikely to yield strong specular reflections; the model exaggerated the extent of water surface features, leading to underestimation of facet slopes. A ray tracing algorithm indicated that reflectance was greatest when solar and view zenith angles were equal and the sensor scanned toward the Sun to capture specular reflections of the solar beam. Reflected energy was concentrated in a small portion of the sky, but rougher water surfaces reflected rays into a broader range of directions. Our framework facilitates flight planning to avoid surface-reflected radiance while mapping other river attributes, or to maximize this component to exploit relationships between hydraulics and surface reflectance. This initial analysis also highlighted the need for improved models of water surface topography in natural rivers.

Journal of Geophysical Research F: Earth Surface↗

USGS2017

Effects of lateral confinement in natural and leveed reaches of a gravel-bed river: Snake River, Wyoming, USA

This study examined the effects of natural and anthropogenic changes in confining margin width by applying remote sensing techniques – fusing LiDAR topography with image-derived bathymetry – over a large spatial extent: 58 km of the Snake River, Wyoming, USA. Fused digital elevation models from 2007 and 2012 were differenced to quantify changes in the volume of stored sediment, develop morphological sediment budgets, and infer spatial gradients in bed material transport. Our study spanned two similar reaches that were subject to different controls on confining margin width: natural terraces versus artificial levees. Channel planform in reaches with similar slope and confining margin width differed depending on whether the margins were natural or anthropogenic. The effects of tributaries also differed between the two reaches. Generally, the natural reach featured greater confining margin widths and was depositional, whereas artificial lateral constriction in the leveed reach produced a sediment budget that was closer to balanced. Although our remote sensing methods provided topographic data over a large area, net volumetric changes were not statistically significant due to the uncertainty associated with bed elevation estimates. We therefore focused on along-channel spatial differences in bed material transport rather than absolute volumes of sediment. To complement indirect estimates of sediment transport derived by morphological sediment budgeting, we collected field data on bed mobility through a tracer study. Surface and subsurface grain size measurements were combined with bed mobility observations to calculate armoring and dimensionless sediment transport ratios, which indicated that sediment supply exceeded transport capacity in the natural reach and vice versa in the leveed reach. We hypothesize that constriction by levees induced an initial phase of incision and bed armoring. Because levees prevented bank erosion, the channel excavated sediment by migrating rapidly across the restricted braidplain and eroding bars and islands.

Wyoming↗

USGS2017

Remote measurement of river discharge using thermal particle image velocimetry (PIV) and various sources of bathymetric information

Although river discharge is a fundamental hydrologic quantity, conventional methods of streamgaging are impractical, expensive, and potentially dangerous in remote locations. This study evaluated the potential for measuring discharge via various forms of remote sensing, primarily thermal imaging of flow velocities but also spectrally-based depth retrieval from passive optical image data. We acquired thermal image time series from bridges spanning five streams in Alaska and observed strong agreement between velocities measured in situ and those inferred by Particle Image Velocimetry (PIV), which quantified advection of thermal features by the flow. The resulting surface velocities were converted to depth-averaged velocities by applying site-specific, calibrated velocity indices. Field spectra from three clear-flowing streams provided strong relationships between depth and reflectance, suggesting that, under favorable conditions, spectrally-based bathymetric mapping could complement thermal PIV in a hybrid approach to remote sensing of river discharge; this strategy would not be applicable to larger, more turbid rivers, however. A more flexible and efficient alternative might involve inferring depth from thermal data based on relationships between depth and integral length scales of turbulent fluctuations in temperature, captured as variations in image brightness. We observed moderately strong correlations for a site-aggregated data set that reduced station-to-station variability but encompassed a broad range of depths. Discharges calculated using thermal PIV-derived velocities were within 15% of in situ measurements when combined with depths measured directly in the field or estimated from field spectra and within 40% when the depth information also was derived from thermal images. The results of this initial, proof-of-concept investigation suggest that remote sensing techniques could facilitate measurement of river discharge.

Journal of Hydrology↗

USGS2017

Using remotely sensed data to estimate river characteristics including water-surface velocity and discharge

This paper describes a project combining field studies and analyses directed at providing an assessment of the accuracy of remotely sensed methods for determining river characteristics such as velocity and discharge. In particular, we describe a remote sensing method for surface velocities using mid-wave thermal camera videography combined with image analysis. One of the critical problems in this work is determining a method for relating remotely measured water-surface velocities to vertically averaged velocities through a velocity index. We explore three similarity profiles that allow a relationship between surface and vertically averaged velocity to be found either using empirical results or simple roughness-to-depth ratios. To test the approaches we compare them in a situation where vertical structure is known over most of the flow depth through ADCP measurements. By determining best-fit profiles through the ADCP profiles, average values of the velocity index are found for the cross-sections where measurement were made. By comparing these to the predicted velocity indices from the three similarity profiles, we find that, although the differences between the various similarity profiles are substantial, they are smaller than differences associated with local nonuniformity and nonhydrostatic flow. Nevertheless, the velocity indices are accurate to about +/-5%, meaning that remotely sensed vertically averaged velocities can be computed to well within the current accuracy standard for such values when used for river gaging.

Conference Paper↗

USGS2017

Remote measurement of surface-water velocity using infrared videography and PIV: a proof-of-concept for Alaskan rivers

Thermal cameras with high sensitivity to medium and long wavelengths can resolve features at the surface of flowing water arising from turbulent mixing. Images acquired by these cameras can be processed with particle image velocimetry (PIV) to compute surface velocities based on the displacement of thermal features as they advect with the flow. We conducted a series of field measurements to test this methodology for remote sensing of surface velocities in rivers. We positioned an infrared video camera at multiple stations across bridges that spanned five rivers in Alaska. Simultaneous non-contact measurements of surface velocity were collected with a radar gun. In situ velocity profiles were collected with Acoustic Doppler Current Profilers (ADCP). Infrared image time series were collected at a frequency of 10Hz for a one-minute duration at a number of stations spaced across each bridge. Commercial PIV software used a cross-correlation algorithm to calculate pixel displacements between successive frames, which were then scaled to produce surface velocities. A blanking distance below the ADCP prevents a direct measurement of the surface velocity. However, we estimated surface velocity from the ADCP measurements using a program that normalizes each ADCP transect and combines those normalized transects to compute a mean measurement profile. The program can fit a power law to the profile and in so doing provides a velocity index, the ratio between the depth-averaged and surface velocity. For the rivers in this study, the velocity index ranged from 0.82 – 0.92. Average radar and extrapolated ADCP surface velocities were in good agreement with average infrared PIV calculations.

Conference Paper↗

USGS2016

Removing sun glint from optical remote sensing images of shallow rivers

Sun glint is the specular reflection of light from the water surface, which often causes unusually bright pixel values that can dominate fluvial remote sensing imagery and obscure the water-leaving radiance signal of interest for mapping bathymetry, bottom type, or water column optical characteristics. Although sun glint is ubiquitous in fluvial remote sensing imagery, river-specific methods for removing sun glint are not yet available. We show that existing sun glint-removal methods developed for multispectral images of marine shallow water environments over-correct shallow portions of fluvial remote sensing imagery resulting in regions of unreliable data along channel margins. We build on existing marine glint-removal methods to develop a river-specific technique that removes sun glint from shallow areas of the channel without overcorrection by accounting for non-negligible water-leaving near-infrared radiance. This new sun glint-removal method can improve the accuracy of spectrally-based depth retrieval in cases where sun glint dominates the at-sensor radiance. For an example image of the gravel-bed Snake River, Wyoming, USA, observed-vs.-predicted R 2 values for depth retrieval improved from 0.66 to 0.76 following sun glint removal. The methodology presented here is straightforward to implement and could be incorporated into image processing workflows for multispectral images that include a near-infrared band.

Earth Surface Processes and Landforms↗

USGS2016

Characterizing supraglacial meltwater channel hydraulics on the Greenland Ice Sheet from in situ observations

Supraglacial rivers on the Greenland ice sheet (GrIS) transport large volumes of surface meltwater toward the ocean, yet have received relatively little direct research. This study presents field observations of channel width, depth, velocity, and water surface slope for nine supraglacial channels on the southwestern GrIS collected between 23 July and 20 August, 2012. Field sites are located up to 74 km inland and span 494-1485 m elevation, and contain measured discharges larger than any previous in situ study: from 0.006 to 23.12 m 3 /s in channels 0.20 to 20.62 m wide. All channels were deeply incised with near vertical banks, and hydraulic geometry results indicate that supraglacial channels primarily accommodate greater discharges by increasing velocity. Smaller streams had steeper water surface slopes (0.74-8.83%) than typical in terrestrial settings, yielding correspondingly high velocities (0.40-2.60 m/s) and Froude numbers (0.45-3.11) with supercritical flow observed in 54% of measurements. Derived Manning's n values were larger and more variable than anticipated from channels of uniform substrate, ranging from 0.009 to 0.154 with a mean value of 0.035 +/- 0.027 despite the absence of sediment, debris, or other roughness elements. Ubiquitous micro-depressions in shallow sections of the channel bed may explain some of these roughness values. However, we find that other, unobserved sources of flow resistance likely contributed to these elevated n values: future work should explicitly consider additional sources of flow resistance beyond bed roughness in supraglacial channels. We conclude that hydraulic modelling for these channels must allow for both sub- and supercritical flow, and most importantly must refrain from assuming that all ice-substrate channels exhibit similar hydraulic behavior, especially for Froude numbers and Manning's n. Finally, this study highlights that further theoretical and empirical work on supraglacial channel hydraulics is necessary before broad scale understanding of ice sheet hydrology can be achieved. This article is protected by copyright. All rights reserved.

Earth Surface Processes and Landforms↗

USGS2016

Inferring river bathymetry via Image-to-Depth Quantile Transformation (IDQT)

Conventional, regression-based methods of inferring depth from passive optical image data undermine the advantages of remote sensing for characterizing river systems. This study introduces and evaluates a more flexible framework, Image-to-Depth Quantile Transformation (IDQT), that involves linking the frequency distribution of pixel values to that of depth. In addition, a new image processing workflow involving deep water correction and Minimum Noise Fraction (MNF) transformation can reduce a hyperspectral data set to a single variable related to depth and thus suitable for input to IDQT. Applied to a gravel bed river, IDQT avoided negative depth estimates along channel margins and underpredictions of pool depth. Depth retrieval accuracy (R25 0.79) and precision (0.27 m) were comparable to an established band ratio-based method, although a small shallow bias (0.04 m) was observed. Several ways of specifying distributions of pixel values and depths were evaluated but had negligible impact on the resulting depth estimates, implying that IDQT was robust to these implementation details. In essence, IDQT uses frequency distributions of pixel values and depths to achieve an aspatial calibration; the image itself provides information on the spatial distribution of depths. The approach thus reduces sensitivity to misalignment between field and image data sets and allows greater flexibility in the timing of field data collection relative to image acquisition, a significant advantage in dynamic channels. IDQT also creates new possibilities for depth retrieval in the absence of field data if a model could be used to predict the distribution of depths within a reach.

Water Resources Research↗

USGS2016

Spectrally based mapping of riverbed composition

Remote sensing methods provide an efficient means of characterizing fluvial systems. This study evaluated the potential to map riverbed composition based on in situ and/or remote measurements of reflectance. Field spectra and substrate photos from the Snake River, Wyoming, USA, were used to identify different sediment facies and degrees of algal development and to quantify their optical characteristics. We hypothesized that accounting for the effects of depth and water column attenuation to isolate the reflectance of the streambed would enhance distinctions among bottom types and facilitate substrate classification. A bottom reflectance retrieval algorithm adapted from coastal research yielded realistic spectra for the 450 to 700 nm range; but bottom reflectance-based substrate classifications, generated using a random forest technique, were no more accurate than classifications derived from above-water field spectra. Additional hypothesis testing indicated that a combination of reflectance magnitude (brightness) and indices of spectral shape provided the most accurate riverbed classifications. Convolving field spectra to the response functions of a multispectral satellite and a hyperspectral imaging system did not reduce classification accuracies, implying that high spectral resolution was not essential. Supervised classifications of algal density produced from hyperspectral data and an inferred bottom reflectance image were not highly accurate, but unsupervised classification of the bottom reflectance image revealed distinct spectrally based clusters, suggesting that such an image could provide additional river information. We attribute the failure of bottom reflectance retrieval to yield more reliable substrate maps to a latent correlation between depth and bottom type. Accounting for the effects of depth might have eliminated a key distinction among substrates and thus reduced discriminatory power. Although further, more systematic study across a broader range of fluvial environments is needed to substantiate our initial results, this case study suggests that bed composition in shallow, clear-flowing rivers potentially could be mapped remotely.

Geomorphology↗

USGS2012

Mapping river bathymetry with a small footprint green LiDAR: Applications and challenges

Airborne bathymetric Light Detection And Ranging (LiDAR) systems designed for coastal and marine surveys are increasingly sought after for high-resolution mapping of fluvial systems. To evaluate the potential utility of bathymetric LiDAR for applications of this kind, we compared detailed surveys collected using wading and sonar techniques with measurements from the United States Geological Survey’s hybrid topographic⁄ bathymetric Experimental Advanced Airborne Research LiDAR (EAARL). These comparisons, based upon data collected from the Trinity and Klamath Rivers, California, and the Colorado River, Colorado, demonstrated that environmental conditions and postprocessing algorithms can influence the accuracy and utility of these surveys and must be given consideration. These factors can lead to mapping errors that can have a direct bearing on derivative analyses such as hydraulic modeling and habitat assessment. We discuss the water and substrate characteristics of the sites, compare the conventional and remotely sensed river-bed topographies, and investigate the laser waveforms reflected from submerged targets to provide an evaluation as to the suitability and accuracy of the EAARL system and associated processing algorithms for riverine mapping applications.

Journal of the American Water Resources Associatio↗

USGS2011

Evaluating the potential for remote bathymetric mapping of a turbid, sand-bed river: 1. Field spectroscopy and radiative transfer modeling

Remote sensing offers an efficient means of mapping bathymetry in river systems, but this approach has been applied primarily to clear-flowing, gravel bed streams. This study used field spectroscopy and radiative transfer modeling to assess the feasibility of spectrally based depth retrieval in a sand-bed river with a higher suspended sediment concentration (SSC) and greater water turbidity. Attenuation of light within the water column was characterized by measuring the amount of downwelling radiant energy at different depths and calculating a diffuse attenuation coefficient, K d . Attenuation was strongest in blue and near-infrared bands due to scattering by suspended sediment and absorption by water, respectively. Even for red wavelengths with the lowest values of K d , only a small fraction of the incident light propagated to the bed, restricting the range of depths amenable to remote sensing. Spectra recorded above the water surface were used to establish a strong, linear relationship ( R 2 = 0.949) between flow depth and a simple band ratio; even under moderately turbid conditions, depth remained the primary control on reflectance. Constraints on depth retrieval were examined via numerical modeling of radiative transfer within the atmosphere and water column. SSC and sensor radiometric resolution limited both the maximum detectable depth and the precision of image-derived depth estimates. Thus, although field spectra indicated that the bathymetry of turbid channels could be remotely mapped, model results implied that depth retrieval in sediment-laden rivers would be limited to shallow depths (on the order of 0.5 m) and subject to a significant degree of uncertainty.

Water Resources Research↗

USGS2011

Evaluating the potential for remote bathymetric mapping of a turbid, sand-bed river: 2. application to hyperspectral image data from the Platte River

This study examined the possibility of mapping depth from optical image data in turbid, sediment-laden channels. Analysis of hyperspectral images from the Platte River indicated that depth retrieval in these environments is feasible, but might not be highly accurate. Four methods of calibrating image-derived depth estimates were evaluated. The first involved extracting image spectra at survey point locations throughout the reach. These paired observations of depth and reflectance were subjected to optimal band ratio analysis (OBRA) to relate ( R 2 = 0.596) a spectrally based quantity to flow depth. Two other methods were based on OBRA of data from individual cross sections. A fourth strategy used ground-based reflectance measurements to derive an OBRA relation ( R 2 = 0.944) that was then applied to the image. Depth retrieval accuracy was assessed by visually inspecting cross sections and calculating various error metrics. Calibration via field spectroscopy resulted in a shallow bias but provided relative accuracies similar to image-based methods. Reach-aggregated OBRA was marginally superior to calibrations based on individual cross sections, and depth retrieval accuracy varied considerably along each reach. Errors were lower and observed versus predicted regression R 2 values higher for a relatively simple, deeper site than a shallower, braided reach; errors were 1/3 and 1/2 the mean depth for the two reaches. Bathymetric maps were coherent and hydraulically reasonable, however, and might be more reliable than implied by numerical metrics. As an example application, linear discriminant analysis was used to produce a series of depth threshold maps for characterizing shallow-water habitat for roosting cranes.

Platte River↗