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At least 19 recordsLinked to original sources
USGS2021

The optical river bathymetry toolkit

Spatially distributed information on water depth is essential for many applications in river research and management and, under certain circumstances, can be inferred from remotely sensed data. Although fluvial remote sensing has emerged as a rapidly developing subdiscipline of the riverine sciences, more widespread adoption of these techniques has been hindered by a lack of accessible software. The Optical River Bathymetry Toolkit (ORByT) fills this void by providing a standalone package for mapping water depth from passive optical image data. The ORByT interface enables end users to import images and field‐based depth measurements, create and refine water masks, and perform spectrally based depth retrieval via an Optimal Band Ratio Analysis algorithm. The resulting bathymetric map can be exported as an image file, point cloud, and/or cross section; a thorough accuracy assessment also is incorporated into the workflow. In addition, image‐derived depth estimates can be subtracted from water surface elevations to obtain bed elevations suitable for input to a hydrodynamic model. Potential users of ORByT must bear in mind the inherent limitations of passive optical remote sensing: reliable bathymetry can only be inferred in clear‐flowing, shallow streams; this approach is not appropriate for more turbid, deeper rivers.

River Research and Applications↗
USGS2009

Field evaluation of a two-dimensinal hydrodynamic model near boulders for habitat calculation

Two-dimensional hydrodynamic models are now widely used in aquatic habitat studies. To test the sensitivity of calculated habitat outcomes to limitations of such a model and of typical field data, bathymetry, depth and velocity data were collected for three discharges in the vicinity of two large boulders in the South Platte River (Colorado) and used in the River2D model. Simulated depth and velocity were compared with observed values at 204 locations and the differences in habitat numbers produced by observed and simulated conditions were calculated. The bulk of the differences between simulated and observed depth and velocity values were found to lie within the likely error of measurement. However, the effect of flow simulation outliers on potential habitat outcomes must be considered when using 2D models for habitat simulation. Furthermore, the shape of the habitat suitability relation can influence the effects of simulation errors. Habitat relations with steep slopes in the velocity ranges found in similar study areas are expected to be sensitive to the magnitude of error found here. Comparison of habitat values derived from simulated and observed depth and velocity revealed a small tendency to under-predict habitat values.

River Research and Applications↗
USGS2025

Hyperspectral imaging of river bathymetry using an ensemble of regression trees

Remote sensing has emerged as an effective tool for characterizing river systems, and machine learning (ML) techniques could make this approach even more powerful. To explore this possibility, we developed an ML-based workflow for hyperspectral imaging of river bathymetry using an ensemble of regression trees (HIRBERT). This approach involves using paired observations of depth and reflectance to select wavelength bands as predictors and then train a depth retrieval model; applying the model to the image yields a spatially continuous bathymetric map. We used data from five rivers with diverse morphologies and optical characteristics to assess whether HIRBERT can (1) provide more accurate depth estimates than a band ratio-based algorithm and (2) extend the range of depths detectable via remote sensing. Relative to single band combinations identified via optimal band ratio analysis (OBRA), regression tree ensembles improved depth retrieval performance, with observed versus predicted (OP) regression R 2 values increasing for all five sites. Similarly, HIRBERT provided more reliable depth estimates than OBRA over the full range of depths present along each river. These results suggest that by incorporating additional spectral information from multiple wavelength bands, ML could enhance bathymetric mapping across a range of river environments. In addition, we show how graphical tools can facilitate interpretation of ML-based depth retrieval models and yield insight regarding relationships between depth and reflectance. The HIRBERT workflow is packaged in free, standalone software developed to support applications in river research and management. Although ML can enhance remote sensing of river bathymetry, the limitations of this approach must also be acknowledged: Field measurements of water depth are required to train a depth retrieval model and the resulting model should only be applied to the image from which the training data were derived. The inherently image-specific nature of this approach implies that developing generalized regression tree ensembles that could be applied at larger scales would require additional research.

California, Idaho, Nebraska, Oregon, Wyoming↗
USGS2011

Effects of uncertain topographic input data on two-dimensional flow modeling in a gravel-bed river

Many applications in river research and management rely upon two-dimensional (2D) numerical models to characterize flow fields, assess habitat conditions, and evaluate channel stability. Predictions from such models are potentially highly uncertain due to the uncertainty associated with the topographic data provided as input. This study used a spatial stochastic simulation strategy to examine the effects of topographic uncertainty on flow modeling. Many, equally likely bed elevation realizations for a simple meander bend were generated and propagated through a typical 2D model to produce distributions of water-surface elevation, depth, velocity, and boundary shear stress at each node of the model's computational grid. Ensemble summary statistics were used to characterize the uncertainty associated with these predictions and to examine the spatial structure of this uncertainty in relation to channel morphology. Simulations conditioned to different data configurations indicated that model predictions became increasingly uncertain as the spacing between surveyed cross sections increased. Model sensitivity to topographic uncertainty was greater for base flow conditions than for a higher, subbankfull flow (75% of bankfull discharge). The degree of sensitivity also varied spatially throughout the bend, with the greatest uncertainty occurring over the point bar where the flow field was influenced by topographic steering effects. Uncertain topography can therefore introduce significant uncertainty to analyses of habitat suitability and bed mobility based on flow model output. In the presence of such uncertainty, the results of these studies are most appropriately represented in probabilistic terms using distributions of model predictions derived from a series of topographic realizations. Copyright 2011 by the American Geophysical Union.

Water Resources Research↗
USGS2021

Improving remotely sensed river bathymetry by image-averaging

Basic data on river bathymetry is critical for numerous applications in river research and management and is increasingly obtained via remote sensing, but the noisy, pixelated appearance of image‐derived depth maps can compromise subsequent analyses. We hypothesized that this noise originates from reflectance from an irregular water surface and introduced a framework for mitigating these effects by Inferring Bathymetry from Averaged River Images (IBARI). This workflow produces time‐averaged images from video frames stabilized to account for platform motion and/or computes a spatial average from an ensemble simulated by randomly shifting images relative to themselves. We used field observations of water depth and helicopter‐based videos from a clear‐flowing river to assess the potential of this approach to improve depth retrieval. Our results indicated that depths inferred from averaged images were more accurate and precise than those inferred from single frames; observed versus predicted regression R 2 increased from 0.80 to 0.88. In addition, IBARI significantly enhanced the texture of image‐derived depth maps, leading to smoother, more coherent representations of channel morphology. Depth retrieval improved with image sequence duration, but the number of images was more important than the length of time encompassed; shorter acquisitions at higher frame rates would economize data collection. We also demonstrated the potential to scale up the IBARI workflow by producing a mosaic of bathymetric maps derived from averaged images acquired at several hovering waypoints distributed along a 2.36 km reach. This approach is well‐suited to data collected from helicopters and small unmanned aircraft systems.

Water Resources Research↗
USGS2011

Effects of dams in river networks on fish assemblages in non-impoundment sections of rivers in Michigan and Wisconsin, USA

Regional assessment of cumulative impacts of dams on riverine fish assemblages provides resource managers essential information for dam operation, potential dam removal, river health assessment and overall ecosystem management. Such an assessment is challenging because characteristics of fish assemblages are not only affected by dams, but also influenced by natural variation and human-induced modification (in addition to dams) in thermal and flow regimes, physicochemical habitats and biological assemblages. This study evaluated the impacts of dams on river fish assemblages in the non-impoundment sections of rivers in the states of Michigan and Wisconsin using multiple fish assemblage indicators and multiple approaches to distinguish the influences of dams from those of other natural and human-induced factors. We found that environmental factors that influence fish assemblages in addition to dams should be incorporated when evaluating regional effects of dams on fish assemblages. Without considering such co-influential factors, the evaluation is inadequate and potentially misleading. The role of dams alone in determining fish assemblages at a regional spatial scale is relatively small (explained less than 20% of variance) compared with the other environmental factors, such as river size, flow and thermal regimes and land uses jointly. However, our results do demonstrate that downstream and upstream dams can substantially modify fish assemblages in the non-impoundment sections of rivers. After excluding river size and land-use influences, our results clearly demonstrate that dams have significant impacts on fish biotic-integrity and habitat-and-social-preference indicators. The influences of the upstream dams, downstream dams, distance to dams, and dam density differ among the fish indicators, which have different implications for maintaining river biotic integrity, protecting biodiversity and managing fisheries.

Wisconsin and Michigan↗
USGS2024

An enhanced and expanded Toolbox for River Velocimetry using Images from Aircraft (TRiVIA)

Detailed, accurate information on flow patterns in river channels can improve understanding of habitat conditions, geomorphic processes, and potential hazards to help inform water management. Data describing flow patterns in river channels can be obtained efficiently via image-based techniques that have become more widely used in recent years as the number of platforms for acquiring images has expanded and the number of algorithms for inferring velocities has grown. Image-based techniques have been incorporated into various software packages, including the Toolbox for River Velocimetry using Images from Aircraft (TRiVIA). TRiVIA is a freely available, standalone computer program that provides a comprehensive workflow for performing particle image velocimetry (PIV)-based analyses within a graphical interface. This paper summarizes major enhancements incorporated into the latest release of TRiVIA, version 2.1. For example, a new Tool for Input Parameter Selection (TIPS) provides guidance for specifying key inputs to the PIV algorithm by allowing users to explore relationships between flow velocity, pixel size, output vector spacing, and frame interval. Improved visualization capabilities include the ability to create streamlines and display PIV output on an interactive web map. The program now provides greater flexibility for importing field data in various formats and selecting which observations to use for accuracy assessment. The most substantial additions to TRiVIA 2.1 are the ability to integrate bathymetric information with image-derived velocity estimates to calculate river discharge and to use images acquired from moving aircraft to efficiently map long segments of large rivers to support habitat assessment, contaminant transport studies, and a range of other applications.

River Research and Applications↗
USGS2006

Ecological consequences of hydropower development in Central America: Impacts of small dams and water diversion on neotropical stream fish assemblages

Small dams for hydropower have caused widespread alteration of Central American rivers, yet much of recent development has gone undocumented by scientists and conservationists. We examined the ecological effects of a small hydropower plant (Dona Julia Hydroelectric Center) on two low-order streams (the Puerto Viejo River and Quebradon stream) draining a mountainous area of Costa Rica. Operation of the Dona Julia plant has dewatered these streams, reducing discharge to ~ 10% of average annual flow. This study compared fish assemblage composition and aquatic habitat upstream and downstream of diversion dams on two streams and along a ~ 4 km dewatered reach of the Puerto Viejo River in an attempt to evaluate current instream flow recommendations for regulated Costa Rican streams. Our results indicated that fish assemblages directly upstream and downstream of the dam on the third order Puerto Viejo River were dissimilar, suggesting that the small dam (< 15 in high) hindered movement of fishes. Along the ~ 4 km dewatered reach of the Puerto Viejo River, species count increased with downstream distance from the dam. However, estimated species richness and overall fish abundance were not significantly correlated with downstream distance from the dam. Our results suggested that effects of stream dewatering may be most pronounced for a subset of species with more complex reproductive requirements, classified as equilibrium-type species based on their life-history. In the absence of changes to current operations, we expect that fish assemblages in the Puerto Viejo River will be increasingly dominated by opportunistic-type, colonizing fish species. Operations of many other small hydropower plants in Costa Rica and other parts of Central America mirror those of Doha Julia; the methods and results of this study may be applicable to some of those projects.

River Research and Applications↗
USGS2009

Geomorphic applications of stream-gage information

In the United States, several thousand stream gages provide what typically is the only source of continuous, long-term streamflow and channel-geometry information for the locations being monitored. In this paper, the geomorphic content of stream-gage information, previous and potential applications of stream-gage information in fluvial geomorphic research and various possible limitations are described. Documented applications include studies of hydraulic geometry, channel bankfull characteristics, sediment transport and channel geomorphic response to various types of disturbance. Potential applications include studies to determine the geomorphic effectiveness of large floods and in-stream habitat change in response to disturbance. For certain applications, various spatial, temporal and data limitations may render the stream-gage information of limited use; however, such information often is of considerable value to enable or enhance geomorphic investigations.

River Research and Applications↗
USGS2004

Acute exposure to gas-supersaturated water does not affect reproductive success of female adult chinook salmon late in maturation

At times, total dissolved gas concentrations in the Columbia and Snake rivers have been elevated due to involuntary spill from high spring runoff and voluntary spill used as a method to pass juvenile salmonids over dams. The goal of this project was to determine if acute exposure to total dissolved gas supersaturation (TDGS) affects the reproductive performance of female chinook salmon late in their maturation. During this study, adult female spring chinook salmon were exposed to mean TDGS levels of 114.1 % to 125.5%. We ended exposures at first mortality, or at the appearance of impending death. Based on this criterion, exposures lasted from 10 to 68 h and were inversely related to TDGS. There was no effect of TDGS on pre-spawning mortality or fecundity when comparing treatment fish to experimental controls or the general hatchery population four to six weeks after exposures. Egg quality, based on egg weight and egg diameter, did not differ between treatment and control fish. Fertilization rate and survival to eyed-stage was high (>94%) for all groups. With the exception of Renibacterium salmoninarum (the causative agent of bacterial kidney disease; BKD), no viral or bacterial fish pathogens were isolated from experimental fish. The prevalence (about 45%) and severity of R. salmoninarum did not differ among the groups or the general hatchery population. We conclude that these acute exposures to moderate levels of gas-supersaturated water-perhaps similar to that experienced by immigrating adult salmon as they approach and pass a hydropower dam on the Columbia River-did not affect reproductive success of female chinook salmon late in their maturation. These results are most applicable to summer and fall chinook salmon, which migrate in the summer/fall and spawn shortly after reaching their natal streams. Published in 2004 by John Wiley and Sons, Ltd.

River Research and Applications↗
USGS2012

Predicting ecological flow regime at ungaged sites: A comparison of methods

Nineteen ecologically relevant streamflow characteristics were estimated using published rainfall–runoff and regional regression models for six sites with observed daily streamflow records in Kentucky. The regional regression model produced median estimates closer to the observed median for all but two characteristics. The variability of predictions from both models was generally less than the observed variability. The variability of the predictions from the rainfall–runoff model was greater than that from the regional regression model for all but three characteristics. Eight characteristics predicted by the rainfall–runoff model display positive or negative bias across all six sites; biases are not as pronounced for the regional regression model. Results suggest that a rainfall–runoff model calibrated on a single characteristic is less likely to perform well as a predictor of a range of other characteristics (flow regime) when compared with a regional regression model calibrated individually on multiple characteristics used to represent the flow regime. Poor model performance may misrepresent hydrologic conditions, potentially distorting the perceived risk of ecological degradation. Without prior selection of streamflow characteristics, targeted calibration, and error quantification, the widespread application of general hydrologic models to ecological flow studies is problematic. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.

Kentucky, Tennessee↗
USGS2025

Confluence of time and space: An innovation for quantifying dynamics of hydrologic floodplain connectivity with remote sensing and GIS

Hydrologic connectivity is a crucial determinant of aquatic ecosystem services, governing the exchange of nutrients, sediments, chemicals, and biota. Various indices and metrics exist for quantifying hydrologic connectivity across diverse environments and scales. However, existing methodologies often fail to adequately capture lateral connectivity between floodplain lakes and streams across vast, low-relief, multi-lake floodplain systems. This study introduces a novel approach for quantifying lateral hydrologic connectivity specifically tailored for floodplain lakes connecting to streams within the expansive floodplain of the Lower Mississippi River. This approach centers on the spatial and temporal intersection of lakes and streams, leveraging remote sensing and GIS data to estimate nine distinct metrics of hydrologic connectivity. To assess the reliability of the method, the study estimated connectivity metrics for 92 randomly selected floodplain lakes, comprising 53 lakes connected to large streams (Strahler order >7), 13 lakes connected to medium (order 4-6) streams, and 26 lakes connected to small (order 1-3) streams. As expected, there was significant variability in hydrologic connectivity across different stream size classes. The outlined approach contributes valuable insights into the hydrologic connectivity of floodplain lakes and offers a generalizable framework applicable to other floodplains. Its versatility makes it a practical tool for understanding connectivity requirements for biota and facilitating applications in conservation and water resources management. Thus, this work represents a meaningful step toward advancing our understanding of lateral hydrologic connectivity dynamics in complex aquatic ecosystems.

Arkansas, Illinois, Kentucky, Louisiana, Mississip↗
USGS2026

Software to support remote sensing of river discharge based on critical flow theory

Water resource management requires accurate observations of streamflow but standard field methods for measuring river discharge ( Q ) are costly and can be hazardous for equipment and personnel. Remote sensing has become a viable alternative, but many image-based techniques require field data for calibration and depth and velocity can seldom be mapped with a single sensor. A new approach based on critical flow theory, in contrast, allows both of these attributes to be inferred from readily available image data. This technique only pertains to sites with standing waves, called undular hydraulic jumps (UHJs), but a recent investigation demonstrated its potential to provide accurate discharge estimates. This paper introduces software designed to facilitate Inferring Q from UHJs Identified in River Images (InQUIRI). The package includes modules for retrieving data from image servers, making the measurements of wavelength and width required to calculate discharge, inferring a representative wavelength from a profile digitized along a wave train, combining multiple estimates to obtain an ensemble median discharge, and assessing accuracy via comparison to gage records from the U.S. Geological Survey. By making these steps easier to implement, InQUIRI enables users to apply the workflow to a variety of UHJ-containing images. Accumulating more case studies, some successful and others less so, would help constrain the range of applicability of the critical flow approach and foster development of refined guidelines for selecting and measuring waves. The software described herein could play an important role in promoting informed use of this new technique for non-contact streamflow measurement.

Arizona, Colorado, New Mexico, Utah↗
USGS2014

Use of dynamic occupancy models to assess the response of Darters (Teleostei: Percidae) to varying hydrothermal conditions in a southeastern United States tailwater

During the past 100 years, most large rivers in North America have been altered for flood control, hydropower, navigation or water supply development. Although these activities clearly provide important human services, their associated environmental disturbances can profoundly affect stream-dwelling organisms. We used dynamic multi-species occupancy models combined with a trait-based approach to estimate the influence of site-level and species-level characteristics on patch dynamic rates for 15 darter species native to the Elk River, a large, flow-regulated Tennessee River tributary in Tennessee and Alabama. Dynamic occupancy modelling results indicated that for every 2.5 °C increase in stream temperature, darters were 3.94 times more likely to colonize previously unoccupied stream reaches. Additionally, large-bodied darter species were 3.72 times more likely to colonize stream reaches compared with small-bodied species, but crevice-spawning darter species were 5.24 times less likely to colonize previously unoccupied stream reaches. In contrast, darters were 2.21 times less likely to become locally extinct for every 2.5 °C increase in stream temperature, but high stream discharge conditions elevated the risk of local extinction. Lastly, the presence of populations in neighbouring upstream study reaches contributed to a lower risk of extinction, whereas the presence of populations in neighbouring downstream study reaches contributed to higher rates of colonization. Our study demonstrates the application of a trait-based approach combined with a metapopulation framework to assess the patch dynamics of darters in a regulated river. Results from our study will provide a baseline for evaluating the ecological consequences of alternative dam operations.

River Research and Applications↗
USGS2013

Estimating thermal regimes of bull trout and assessing the potential effects of climate warming on critical habitats

Understanding the vulnerability of aquatic species and habitats under climate change is critical for conservation and management of freshwater systems. Climate warming is predicted to increase water temperatures in freshwater ecosystems worldwide, yet few studies have developed spatially explicit modelling tools for understanding the potential impacts. We parameterized a nonspatial model, a spatial flow-routed model, and a spatial hierarchical model to predict August stream temperatures (22-m resolution) throughout the Flathead River Basin, USA and Canada. Model comparisons showed that the spatial models performed significantly better than the nonspatial model, explaining the spatial autocorrelation found between sites. The spatial hierarchical model explained 82% of the variation in summer mean (August) stream temperatures and was used to estimate thermal regimes for threatened bull trout (Salvelinus confluentus) habitats, one of the most thermally sensitive coldwater species in western North America. The model estimated summer thermal regimes of spawning and rearing habitats at <13 C&deg; and foraging, migrating, and overwintering habitats at <14 C&deg;. To illustrate the useful application of such a model, we simulated climate warming scenarios to quantify potential loss of critical habitats under forecasted climatic conditions. As air and water temperatures continue to increase, our model simulations show that lower portions of the Flathead River Basin drainage (foraging, migrating, and overwintering habitat) may become thermally unsuitable and headwater streams (spawning and rearing) may become isolated because of increasing thermal fragmentation during summer. Model results can be used to focus conservation and management efforts on populations of concern, by identifying critical habitats and assessing thermal changes at a local scale.

River Research and Applications↗
USGS2026

IVyTools: Space-Time Image Velocimetry for streamflow

Accurate streamflow measurements are essential for hydrologic monitoring, flood forecasting, and water resource management. Traditional in situ methods, although reliable, are often impractical or unsafe during flood conditions or at inaccessible locations. Image velocimetry techniques offer a potential non-contact alternative, yet operational adoption has been hindered by the lack of standardized, open-source tools, particularly for Space–Time Image Velocimetry (STIV). This paper introduces IVyTools, an open-source software application for operational streamflow measurement using STIV. Developed by the US Geological Survey (USGS), IVyTools integrates standardized streamflow measurement protocols into a reproducible, quality-controlled workflow that includes video preprocessing, orthorectification, velocity estimation, and streamflow (discharge) computation. The software incorporates a dual-method uncertainty framework based on ISO 748:2007 and an adapted Interpolated Variance Estimator (IVE), enabling users to quantify and diagnose measurement uncertainty. Validation against an independently published benchmark dataset demonstrates that IVyTools achieves a mean absolute percentage error of 4.56% (MAE = 5.16 m 3 /s ) from field-measured reference discharges, with acceptable performance across diverse river conditions. This work supports the broader adoption of image-based streamflow measurement methods and provides a foundation for potential future automation and integration into real-time hydrologic networks.

River Research and Applications↗
USGS2016

Informing watershed connectivity barrier prioritization decisions: A synthesis

Water resources and transportation infrastructure such as dams and culverts provide countless socio-economic benefits; however, this infrastructure can also disconnect the movement of organisms, sediment, and water through river ecosystems. Trade-offs associated with these competing costs and benefits occur globally, with applications in barrier addition (e.g. dam and road construction), reengineering (e.g. culvert repair), and removal (e.g. dam removal and aging infrastructure). Barrier prioritization provides a unique opportunity to: (i) restore and reconnect potentially large habitat patches quickly and effectively and (ii) avoid impacts prior to occurrence in line with the mitigation hierarchy (i.e. avoid then minimize then mitigate). This paper synthesizes 46 watershed-scale barrier planning studies and presents a procedure to guide barrier prioritization associated with connectivity for aquatic organisms. We focus on practical issues informing prioritization studies such as available data sets, methods, techniques, and tools. We conclude with a discussion of emerging trends and issues in barrier prioritization and key opportunities for enhancing the body of knowledge.

River Research and Applications↗
USGS2006

Applicability of the flood-pulse concept in a temperate floodplain river ecosystem: Thermal and temporal components

Annual growth increments were calculated for blue catfish (Ictalurus furcatus) and flathead catfish (Pylodictis olivaris) from the lower Mississippi River (LMR) to assess hypothesized relationships between fish growth and floodplain inundation as predicted by the Flood-Pulse Concept. Variation in catfish growth increment was high for all age classes of both species, and growth increments were not consistently related to various measures of floodplain inundation. However, relationships became stronger, and usually direct, when water temperature was integrated with area and duration of floodplain inundation. Relationships were significant for four of six age classes for blue catfish, a species known to utilize floodplain habitats. Though similar in direction, relationships were weaker for flathead catfish, which is considered a more riverine species. Our results indicate the Flood-Pulse Concept applies more strongly to temperate floodplain-river ecosystems when thermal aspects of flood pulses are considered. We recommend that future management of the LMR should consider ways to 'recouple' the annual flood and thermal cycles. An adaptive management approach will allow further determination of important processes affecting fisheries production in the LMR. Copyright ?? John Wiley & Sons, Ltd.

River Research and Applications↗