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At least 487 records · Page 27Linked to original sources
USGS1957

Drainage areas of Iowa streams

The drainage area of a stream at a specified location ordinarily may be defined as that area, measured in a horizontal plane, which is enclosed by a topographic divide such that direct surface runoff from precipitation would drain by gravity into the river basin above the specified point. One of the most important factors in the hydrologic computation for the design of structures on or over watercourses is the drainage area upstream from the point under consideration. Other hydrologic studies such as low-flow, flood-frequency analyses, rainfall-runoff correlations, stream density, and area-distance make use of this factor as a basic premise for computation. In order that the drainage-area information of the interior streams of Iowa be of uniform accuracy and available to all users of these data, this report has been compiled, and the drainage areas of all streams in excess of 5 square mies are listed. For the larger streams, drainage areas have been determined at numerous intermediate points. As a result of this report much basic background material has been compiled that will he useful in future hydrologic studies of drainage basin characteristics. This publication is limited to the presentation of the drainage-area data for the interior streams of the State. The methods of application of these data to the study of streamflow characteristics, and the design of related structures are properly the function of the design engineer and are not discussed herein.

Iowa↗
USGS2023

Disparate data streams together yield novel survival estimates of Alaska-breeding Whimbrels

Survival estimates are critical components of avian ecology. In well-intentioned efforts to maximize the utility of one's research, survival estimates often derive from data that were not originally collected for survival assessments, and such post hoc analyses may include unintentional biases. We estimated the survival of Whimbrels captured and marked at two breeding sites in Alaska using divergent data streams that in isolation were subject to methodological biases. Although both capture sites were chosen to study the migration ecology of Alaska-breeding Whimbrels, maximizing the conservation value of the data we collected was obviously desirable. We used multi-year telemetry information to infer survival from one site (Colville River) and mark-resight techniques to estimate survival from a second site (Kanuti River). At the Colville River, we could not feasibly include a control group of birds to assess potential survival effects of externally mounted transmitters, while at Kanuti River we were unable to accurately account for potential emigration events because we used resightings alone. We integrated these datasets in a Bayesian hierarchical framework, an approach that permitted insights across sites that moderated methodological biases within sites. Using telemetry enabled us to detect permanent emigration events from breeding sites in two of ten birds; results that informed estimates for birds without tracking devices. These datasets yielded point estimates of true survival of Whimbrels from Colville River equipped with solar-powered satellite transmitters that were higher (0.83) than true survival estimates of Whimbrels from Kanuti River marked with leg flags alone (0.74) or equipped with surgically implanted satellite transmitters (0.50), but the 95% credible intervals on these estimates overlapped across groups. For species like Whimbrels that are difficult and costly to study, combining information from disparate data streams allowed us to derive novel demographic estimates, an approach with clear application to other similar studies.

Alaska↗
USGS1981

Lithology, reservoir properties, and burial history of portion of Gammon Shale (Cretaceous), southwestern North Dakota

In the northern Great Plains, large quantities of biogenic methane are contained at shallow depths in Cretaceous marine mudstones. The Gammon Shale and equivalents of the Milk River Formation in Canada, which comprise most sediments deposited offshore during the Eagle-Telegraph Creek regression, are typical of such gas-bearing rocks. At Little Missouri field, southwestern North Dakota, Gammon reservoirs consist of discontinuous lenses and laminae of siltstone, less than 10 mm thick, enclosed by silty clay shale. Large amounts of allogenic clay, including highly expansible mixed-layer illite-smectite cause great water sensitivity and high measured and calculated water-saturation values. Reconstructed burial depths, clay mineralogy, and organic matter maturation studies show that the Gammon has not undergone thermal conditions sufficient for oil or thermal gas generation. Scarce authigenic minerals such as pyrite, siderite, and calcite probably formed as a result of bacterial metabolism early in the burial history. The scarcity of authigenic silicates suggests that diagenesis has been inhibited during much of the burial history by the presence of free methane. Shale layers are practically impermeable whereas siltstone microlenses are porous (30 to 40%) and have permeabilities on the order of 3 to 30 md. Reservoir continuity between siltstone layers is poor and, overall, reservoir permeability is probably less than 0.4 md. Connecting passageways between siltstone lenses are 0.1 µm or less in diameter. Organic matter in the low-permeability reservoirs served as the source of biogenic methane, and capillary forces acted as the trapping mechanism for gas accumulation. At Little Missouri field, reservoirs and non-reservoirs cannot be distinguished on the basis of lithology, and much of the Gammon interval is potentially economic. Future research should be directed toward determining the physical basis of log response in the low-permeability reservoirs and toward the development or application of water-free recovery technology.

North Dakota↗
USGS2015

Application of the FluEgg model to predict transport of Asian carp eggs in the Saint Joseph River (Great Lakes tributary)

The Fluvial Egg Drift Simulator (FluEgg) is a three-dimensional Lagrangian model that simulates the movement and development of Asian carp eggs until hatching based on the physical characteristics of the flow field and the physical and biological characteristics of the eggs. This tool provides information concerning egg development and spawning habitat suitability including: egg plume location, egg vertical and travel time distribution, and egg-hatching risk. A case study of the simulation of Asian carp eggs in the Lower Saint Joseph River, a tributary of Lake Michigan, is presented. The river hydrodynamic input for FluEgg was generated in two ways — using hydroacoustic data and using HEC-RAS model data. The HEC-RAS model hydrodynamic input data were used to simulate 52 scenarios covering a broad range of flows and water temperatures with the eggs at risk of hatching ranging from 0 to 93% depending on river conditions. FluEgg simulations depict the highest percentage of eggs at risk of hatching occurs at the lowest discharge and at peak water temperatures. Analysis of these scenarios illustrates how the interactive relation among river length, hydrodynamics, and water temperature influence egg transport and hatching risk. An improved version of FluEgg, which more realistically simulates dispersion and egg development, is presented. Also presented is a graphical user interface that facilitates the use of FluEgg and provides a set of post-processing analysis tools to support management decision-making regarding the prevention and control of Asian carp reproduction in rivers with or without Asian carp populations.

Michigan↗
USGS2014

Characterizing riverbed sediment using high-frequency acoustics 2: scattering signatures of Colorado River bed sediment in Marble and Grand Canyons

In this, the second of a pair of papers on the statistical signatures of riverbed sediment in high-frequency acoustic backscatter, spatially explicit maps of the stochastic geometries (length- and amplitude-scales) of backscatter are related to patches of riverbed surfaces composed of known sediment types, as determined by geo-referenced underwater video observations. Statistics of backscatter magnitudes alone are found to be poor discriminators between sediment types. However, the variance of the power spectrum, and the intercept and slope from a power-law spectral form (termed the spectral strength and exponent, respectively) successfully discriminate between sediment types. A decision-tree approach was able to classify spatially heterogeneous patches of homogeneous sands, gravels (and sand-gravel mixtures), and cobbles/boulders with 95, 88, and 91% accuracy, respectively. Application to sites outside the calibration, and surveys made at calibration sites at different times, were plausible based on observations from underwater video. Analysis of decision trees built with different training data sets suggested that the spectral exponent was consistently the most important variable in the classification. In the absence of theory concerning how spatially variable sediment surfaces scatter high-frequency sound, the primary advantage of this data-driven approach to classify bed sediment over alternatives is that spectral methods have well understood properties and make no assumptions about the distributional form of the fluctuating component of backscatter over small spatial scales.

Arizona↗
USGS2003

A bibliography of Klamath Mountains geology, California and Oregon, listing authors from Aalto to Zucca for the years 1849 to Mid-2003

This bibliography of Klamath Mountains geology was begun, although not in a systematic or comprehensive way, when, in 1953, I was assigned the task of preparing a report on the geology and mineral resources of the drainage basins of the Trinity, Klamath, and Eel Rivers in northwestern California. During the following 40 or more years, I maintained an active interest in the Klamath Mountains region and continued to collect bibliographic references to the various reports and maps of Klamath geology that came to my attention. When I retired in 1989 and became a Geologist Emeritus with the Geological Survey, I had a large amount of bibliographic material in my files. Believing that a comprehensive bibliography of a region is a valuable research tool, I have expended substantial effort to make this bibliography of the Klamath Mountains as complete as is reasonably feasible. My aim was to include all published reports and maps that pertain primarily to the Klamath Mountains, as well as all pertinent doctoral and master's theses. In addition, I included reports in which the Klamath Mountains are of significance but not the primary focus; these latter kinds are mostly reports that correlate the Klamath terranes with those of other provinces, that compare the genesis of Klamath rocks with those elsewhere, or that include the Klamath Mountains in a continental framework. Reports describing the geology of the overlap sequences such as the Great Valley sequence, Hornbrook Formation, and Tertiary sediments and volcanics are included where those rocks lie within the limits of the Klamath Mountains province, but are only selectively included where the overlap sequences are mainly peripheral to the province. The alphabetical part of the bibliography consists of approximately 1700 entries. The list of primary references probably is virtually complete through 1994 and includes some 1995 references. The earliest reference is to James Dwight Dana in 1849. In order to restrict the size of the topical part of the bibliography to reasonable limits, each reference is listed under only one subject although many references may be applicable to two or more subjects. Titles in the topical section are abbreviated to conserve space and still retain identity. The bibliography was compiled from a variety of sources. Some of the references have not been checked against the original publications for accuracy. Caveat emptor! I would appreciate being informed of any errors or ommissions in order that a corrected and updated version of the bibliography may be prepared. I thank Nancy Blair for assistance in verifying some of the references, and thank Mary Donato and Robert Brown for helpful suggestions regarding the topical part of the bibliography. Since the first version of this bibliography was released in 1995, the total number of entries has increased from approximately 1700 to 1937, which indicates a continued high interest in the geology of the Klamath Mountains province. The total number of entries includes 73 Ph.D. theses and 123 Masters theses representing 26 universities.

Open-File Report↗
USGS2022

Remote sensing of visible dye concentrations during a tracer experiment on a large, turbid river

Understanding dispersion in rivers is critical for numerous applications, such as characterizing larval drift for endangered fish species and responding to spills of hazardous materials. Injecting a visible dye into the river can yield insight on dispersion processes, but conventional field instrumentation yields limited data on variations in dye concentration over time at a few, fixed points. Remote sensing can provide more detailed, spatially distributed information on the dye's motion, but this approach has only been tested in clear-flowing streams. The purpose of this study was to assess the potential of remote sensing to facilitate tracer studies in more turbid rivers. To pursue this objective, we injected Rhodamine WT dye into the Missouri River and collected field spectra from a boat, videos from a small unoccupied aircraft system (sUAS), and orthophotos from an airplane. Applying an optimal band ratio analysis (OBRA) algorithm to the field spectra revealed strong correlations ( R 2 = 0.936) between a spectrally based quantity and in situ concentration measurements. OBRA also performed well for broadband RGB (red, green, blue) images extracted from the sUAS-based videos; the resulting concentration maps were used to produce animations that captured movement of the dye pulse. Spectral mixture analysis of repeat orthophoto coverage yielded relative concentration estimates that provided a synoptic perspective on dispersion of the dye throughout the entire 13.8 km reach over the full 2.5-hr duration of the experiment. The results of this study demonstrate the potential to remotely sense tracer dye concentrations in large, highly turbid rivers.

Missouri↗
USGS2015

Hydrologic implications of GRACE satellite data in the Colorado River Basin

Use of GRACE (Gravity Recovery and Climate Experiment) satellites for assessing global water resources is rapidly expanding. Here we advance application of GRACE satellites by reconstructing long-term total water storage (TWS) changes from ground-based monitoring and modeling data. We applied the approach to the Colorado River Basin which has experienced multiyear intense droughts at decadal intervals. Estimated TWS declined by 94 km 3 during 1986–1990 and by 102 km 3 during 1998–2004, similar to the TWS depletion recorded by GRACE (47 km 3 ) during 2010–2013. Our analysis indicates that TWS depletion is dominated by reductions in surface reservoir and soil moisture storage in the upper Colorado basin with additional reductions in groundwater storage in the lower basin. Groundwater storage changes are controlled mostly by natural responses to wet and dry cycles and irrigation pumping outside of Colorado River delivery zones based on ground-based water level and gravity data. Water storage changes are controlled primarily by variable water inputs in response to wet and dry cycles rather than increasing water use. Surface reservoir storage buffers supply variability with current reservoir storage representing ∼2.5 years of available water use. This study can be used as a template showing how to extend short-term GRACE TWS records and using all available data on storage components of TWS to interpret GRACE data, especially within the context of droughts.

Water Resources Research↗
USGS2022

Using ensemble data assimilation to estimate transient hydrologic exchange flow under highly dynamic flow conditions

Quantifying dynamic hydrologic exchange flows (HEFs) within river corridors that experience high-frequency flow variations caused by dam regulations is important for understanding the biogeochemical processes at the river water and groundwater interfaces. Heat has been widely used as a tracer to infer steady-state flow velocities through analytical solutions of heat transport defined by the diurnal temperature signals. Under sub-daily dynamic flow conditions, however, such analytical solutions are not applicable due to the violation of their fundamental assumptions. In this study, we developed a data assimilation-based approach to estimate the sub-daily flux under highly dynamic flow conditions using multi-depth temperature observations at a 5-min resolution. If the hydraulic gradient is measured, Darcy's law was used to calculate the flux with permeability estimated from temperature responses below the riverbed. Otherwise, flux was estimated directly by assimilating multi-depth temperature data at 1- or 2-hr time intervals assuming one-dimensional flow and heat transport governing equation. By comparing estimated fluxes with model-generated synthetic truth, we demonstrated that both schemes have robust performance in estimating fluxes under highly dynamic flow conditions. This data assimilation-based flux estimation method was able to capture the vertical sub-daily fluxes using multi-depth high-resolution temperature data alone, even in the presence of multi-dimensional flow. This approach has been successfully applied to real field temperature data collected at the Hanford site, which experiences highly dynamic HEFs. Our study shows the promise of adopting distributed 1-D temperature monitoring to capture spatial and temporal exchange dynamics in river corridors at a watershed scale or beyond.

Washington↗
USGS2022

Does large dam removal restore downstream riparian vegetation diversity? Testing predictions on the Elwha River, Washington, USA

Large dams and their removal can profoundly affect riparian ecosystems by altering flow and sediment regimes, hydrochory, and landform dynamics, yet few studies have documented these effects on downstream plant communities. Ecological theory and empirical results suggest that by altering disturbance regimes, reducing hydrochory, and shifting communities to later successional stages, dams reduce downstream plant diversity. Dam removal could reverse these processes, but the release of large volumes of sediment could have unexpected, transient effects. Two large dams were removed on the Elwha River in Washington State, USA, from 2011-2014, representing an unprecedented opportunity to study large dam removal effects on riparian plant communities. Our research objectives were to determine: 1) whether the Elwha River dams were associated with lower downstream plant diversity and altered species composition across riparian landforms pre-dam removal, and 2) whether dam removal has begun to restore downstream diversity and composition. To address these objectives, we compared plant species richness and community composition in river segments above, below, and between the two dams. Plant communities were sampled twice before (2005 and 2010) and four times after (2013, 2014, 2016, and 2017) the start of dam removal, with 2013 and 2014 sampled while the upstream dam removal was ongoing. Prior to dam removal, native species richness was 41% lower below dams compared to the upstream segment; six years after dam removal began, it increased ~31% between the dams, while nonnative species richness and cover were not apparently affected by dams or their removal. Deposition caused by large volumes of released reservoir sediment had mixed effects on native species richness (increased on floodplains, decreased elsewhere) in the lowest river segment. Plant community composition was also different downstream from dams compared to the upstream reference, and has changed in downstream floodplains and bars since dam removal. Long-term, we expect that diversity will continue to increase in downstream river segments. Our results provide evidence that 1) large dams reduce downstream native plant diversity, 2) dam removal may restore it, and 3) given the natural dynamics of riparian vegetation, long-term, multi-year before-and-after-monitoring is essential for understanding dam removal effects.

Washington↗
USGS2026

Evaluating approximations of river channel shape using a national cross section database

Many hydrologic applications require basic information on the size and shape of river channels, but measuring cross section (XS) geometry in the field or via remote sensing can be costly and often provides only partial coverage. Given these challenges, we capitalized upon an existing data set of 46,971 XS from gaging stations to evaluate various approximations of channel shape. After screening and pre-processing these data, we fit four model types to each XS, including a new approach that involves Stacking PDFs (probability density functions) to Approximate River Channel Shapes (SPARCS). This framework produced depth estimates that closely matched field measurements, with typical cross-sectional area errors <1 % and a median R 2 of 0.77 for comparison of observed and predicted depths. SPARCS model parameters can be interpreted in terms of channel characteristics: mean depth, asymmetry, bar convexity, and flatness of the bed. The model performed well for the XS included in the database, which was biased toward straight, uniform channels conducive to operational streamflow measurement. Neither model parameters nor accuracy were dependent on discharge. We also assessed the potential of SPARCS to fill in measurement gaps and found that although the model can help, the accuracy of inferred depths decreased as the observable fraction of the channel decreased. An important limitation of SPARCS is that mid-channel bars or multi-threaded morphologies cannot be produced. Graphical tools can help visualize how model parameters affect simulated river forms. SPARCS could facilitate satellite-based discharge estimation by providing prior information on channel shape.

Water Resources Research↗
USGS2014

Decadal surface water quality trends under variable climate, land use, and hydrogeochemical setting in Iowa, USA

Understanding how nitrogen fluxes respond to changes in agriculture and climate is important for improving water quality. In the midwestern United States, expansion of corn cropping for ethanol production led to increasing N application rates in the 2000s during a period of extreme variability of annual precipitation. To examine the effects of these changes, surface water quality was analyzed in 10 major Iowa Rivers. Several decades of concentration and flow data were analyzed with a statistical method that provides internally consistent estimates of the concentration history and reveals flow-normalized trends that are independent of year-to-year streamflow variations. Flow-normalized concentrations of nitrate+nitrite-N decreased from 2000 to 2012 in all basins. To evaluate effects of annual discharge and N loading on these trends, multiple conceptual models were developed and calibrated to flow-weighted annual concentrations. The recent declining concentration trends can be attributed to both very high and very low discharge in the 2000s and to the long (e.g., 8 year) subsurface residence times in some basins. Dilution of N and depletion of stored N occurs in years with high discharge. Reduced N transport and increased N storage occurs in low-discharge years. Central Iowa basins showed the greatest reduction in flow-normalized concentrations, likely because of smaller storage volumes and shorter residence times. Effects of land-use changes on the water quality of major Iowa Rivers may not be noticeable for years or decades in peripheral basins of Iowa, and may be obscured in the central basins where extreme flows strongly affect annual concentration trends.

Iowa↗
USGS2019

River water-quality concentration and flux estimation can be improved by accounting for serial correlation through an autoregressive model

Accurate quantification of riverine water‐quality concentration and flux is challenging because monitoring programs typically collect concentration data at lower frequencies than discharge data. Statistical methods are often used to estimate concentration and flux on days without observations. One recently developed approach is the Weighted Regressions on Time, Discharge, and Season (WRTDS), which has been shown to provide among the most accurate estimates compared to other common methods. The main objective of this work was to improve WRTDS estimation by accounting for the autocorrelation structure of model residuals using the first‐order autoregressive model (AR1). This modified approach, called WRTDS‐Kalman Filter (WRTDS‐K), was compared with WRTDS for six constituents including nitrate‐plus‐nitrite (NO x ), total phosphorus, total Kjeldahl nitrogen, soluble reactive phosphorus, suspended sediment, and chloride. Near‐daily concentration records at nine sites were used to generate subsets through Monte Carlo sampling for five different sampling scenarios. Results show that WRTDS‐K provided generally better daily estimates of concentration and flux than WRTDS under these sampling scenarios for all constituents, especially NO x . The degree of improvement is strongly affected by the underlying sampling scenario, with WRTDS‐K gaining more advantage when more samples are available, and hence more residuals can be exploited. The performance of WRTDS‐K depends on the AR1 coefficient (ρ) and that relationship varies with constituents and sampling scenarios. These results provided recommendations on the optimal ρ for each constituent and sampling scenario. Overall, WRTDS‐K has the potential for broad applications to monitoring records elsewhere, as demonstrated by a pilot application to Chesapeake Bay tributaries.

Ohio↗
USGS2016

Selenium: Mercury molar ratios in freshwater fish in the Columbia River Basin: Potential applications for specific fish consumption advisories

Fish provide a valuable source of beneficial nutrients and are an excellent source of low fat protein. However, fish are also the primary source of methylmercury exposure in humans. Selenium often co-occurs with mercury and there is some evidence that selenium can protect against mercury toxicity yet States issue fish consumption advisories based solely on the risks that methylmercury pose to human health. Recently, it has been suggested the selenium: mercury molar ratio be considered in risk management. In order for agencies to utilize the ratio to set consumption guidelines, it is important to evaluate the variability in selenium and mercury in different fish species. We examined 10 different freshwater fish species found within the Columbia River Basin in order to determine the inter- and intra-specific variability in the selenium: mercury molar ratios and the selenium health benefit values. We found significant variation in selenium: mercury molar ratios. The mean molar ratios for each species were all above 1:1, ranging from 3.42:1 in Walleye to 27.2:1 in Chinook salmon. There was a positive correlation between both mercury and selenium with length for each fish species apart from yellow perch and rainbow trout. All species had health benefit values greater than 2. We observed considerable variability in selenium: mercury molar ratios within fish species collected in the Columbia River Basin. Although incorporating selenium: mercury molar ratios into fish consumption holds the potential for refining advisories and assessing the risk of methylmercury exposure, the current understanding of how these ratios apply is insufficient, and further understanding of drivers of variability in the ratios is needed.

Biological Trace Element Research↗
USGS2017

Estimating discharge and nonpoint source nitrate loading to streams from three end‐member pathways using high‐frequency water quality data

The myriad hydrologic and biogeochemical processes taking place in watersheds occurring across space and time are integrated and reflected in the quantity and quality of water in streams and rivers. Collection of high‐frequency water quality data with sensors in surface waters provides new opportunities to disentangle these processes and quantify sources and transport of water and solutes in the coupled groundwater‐surface water system. A new approach for separating the streamflow hydrograph into three components was developed and coupled with high‐frequency nitrate data to estimate time‐variable nitrate loads from chemically dilute quick flow, chemically concentrated quick flow, and slowflow groundwater end‐member pathways for periods of up to 2 years in a groundwater‐dominated and a quick‐flow‐dominated stream in central Wisconsin, using only streamflow and in‐stream water quality data. The dilute and concentrated quick flow end‐members were distinguished using high‐frequency specific conductance data. Results indicate that dilute quick flow contributed less than 5% of the nitrate load at both sites, whereas 89 ± 8% of the nitrate load at the groundwater‐dominated stream was from slowflow groundwater, and 84 ± 25% of the nitrate load at the quick‐flow‐dominated stream was from concentrated quick flow. Concentrated quick flow nitrate concentrations varied seasonally at both sites, with peak concentrations in the winter that were 2–3 times greater than minimum concentrations during the growing season. Application of this approach provides an opportunity to assess stream vulnerability to nonpoint source nitrate loading and expected stream responses to current or changing conditions and practices in watersheds.

Water Resources Research↗
USGS1996

Reactive solute transport in streams: 2. Simulation of a pH modification experiment

We present an application of an equilibrium-based solute transport model to a p H-modification experiment conducted on the Snake River, an acidic, metal-rich stream located in the Rocky Mountains of Colorado. During the experiment, instream p H decreased from 4.2 to 3.2, causing a marked increase in dissolved iron concentrations. Model application requires specification of several parameters that are estimated using tracer techniques, mass balance calculations, and geochemical data. Two basic questions are addressed through model application: (1) What are the processes responsible for the observed increase in dissolved iron concentrations? (2) Can the identified processes be represented within the equilibrium-based transport model? Simulation results indicate that the increase in iron was due to the dissolution of hydrous iron oxides and the photoreduction of ferric iron. Dissolution from the streambed is represented by considering a trace compartment consisting of freshly precipitated hydrous iron oxide and an abundant compartment consisting of aged precipitates that are less soluble. Spatial variability in the solubility of hydrous iron oxide is attributed to heterogeneity in the streambed sediments, temperature effects, and/or variability in the effects of photoreduction. Solubility products estimated via simulation fall within a narrow range ( pK sp from 40.2 to 40.8) relative to the 6 order of magnitude variation reported for laboratory experiments ( pK sp from 37.3 to 43.3). Results also support the use of an equilibrium-based transport model as the predominate features of the iron and p H profiles are reproduced. The model provides a valuable tool for quantifying the nature and extent of p H-dependent processes within the context of hydrologic transport.

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↗
USGS2024

Self-potential tomography preconditioned by particle swarm optimization— Application to monitoring hyporheic exchange in a bedrock river

A self-potential (SP) data-inversion algorithm was developed and tested on an analytical model of electrical-potential profile data attributed to single and multiple polarized electrical sources. The developed algorithm was then validated by an application to SP-monitoring field data measured on the floodplain of East Fork Poplar Creek, Oak Ridge, Tennessee, to image electrical sources in areas conducive to preferential flow into the flood plain from the bedrock-lined riverbed. The algorithm combined stochastic source-localization by particle-swarm-optimization (PSO) of electrical sources characterized by simplified geometries with source tomography by regularized weighted least-squares minimization of a quadratic objective function. Prior information was incorporated by preconditioning the tomography algorithm by PSO results. Variable percentages of random noise were added to analytical-model data to evaluate the algorithm performance. Results indicated that true parameters of single-source models were inverted and approximated with small residual error, whereas inversion of analytical-model data representing multiple electrical sources accurately approximated the locations of the sources but miscalculated some parameters because of the non-uniqueness of the inverse-model solution. Source tomography applied to analytical model data during testing produced a spatially continuous parameter field that identified the locations of point-scale synthetic dipole sources of electrical current flow with varying degrees of accuracy depending on the prior information incorporated into the tomography. When applied to SP-monitoring field data, the algorithm imaged electrical sources within a known fault that intersects the bedrock riverbed and flood plain of East Fork Poplar Creek and depicted dynamic electrical conditions attributed to hyporheic exchange.

Tennessee↗