This report describes the techniques and methods for computing the mean-channel velocity and discharge using the entropy-based probability concept (probability concept). The method is an alternative to or augments standard streamgaging methods adopted by the U.S. Geological Survey (USGS). Although sensor technology for measuring the mean velocity and discharge has advanced, standard streamgaging and computational methods have remained relatively unchanged since the USGS established its first streamgage at the Rio Grande at Embudo, New Mexico in 1889.
Standard streamgaging methods rely on integrating velocities and depths measured at multiple verticals at a channel cross section (standard cross section) to compute a discharge. The probability concept computes discharge at a single vertical (y-axis) using the ratio of the mean-channel velocity (mean velocity) and maximum velocity, the measured maximum velocity, and the area as a function of stage at the standard cross section. Proper siting and operation and maintenance are required. If siting is conducted appropriately, the probability concept parameters and the y-axis stationing will be similar for different streamflow conditions. The timing of operation and maintenance visits should be based on hydrologic and meteorologic occurrences and seasonality and should capture low, medium, high, and opportunistic streamflow conditions.
Advantages of the probability concept are the capacity to (1) compute discharge time series immediately after streamgage siting, (2) compute discharge for complex streamflow conditions that cannot be quantified by stage-discharge methods, (3) augment time-series data where gaps exist, and (4) integrate with surface velocity sensors such as Doppler velocity radars and cameras, which are not subject to damage caused by ice, debris, and flood flows. Potential sources of bias in discharge derived from the probability concept include (1) rain, (2) wind, and (3) geomorphologic and hydraulic instabilities. Recommendations to address these biases are provided.
This report guides users through the steps to parameterize the probability concept, process field data, and compute the mean velocity and discharge using the probability concept.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/tm3A26","usgsCitation":"Fulton, J.W., Engel, F.L., Eggleston, J.R., and Chiu, C.-L., 2025, Computing discharge using the entropy-based probability concept: U.S. Geological Survey Techniques and Methods book 3, chap. A26, 66 p., https://doi.org/10.3133/tm3A26.","productDescription":"Report: viii, 66 p.; Appendix","onlineOnly":"Y","ipdsId":"IP-138301","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":496208,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/03/a26/tm3a26.pdf","text":"Report","size":"6.77 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T and M 2-A26"},{"id":496210,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/03/a26/Appendix_3_Wind_Bias.csv","text":"Appendix 3","size":"8.0 KB","linkFileType":{"id":7,"text":"csv"},"description":"T and M 2-A26 Appendix 3","linkHelpText":"Correction for Wind Bias"},{"id":496207,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/03/a26/coverthb.jpg"}],"contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, CO 80225
This report describes the steps and the theory to compute the speed and flow of water in streams using the probability concept.
","publicationDate":"2025-09-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Fulton, John W, 0000-0002-5335-0720","orcid":"https://orcid.org/0000-0002-5335-0720","contributorId":213630,"corporation":false,"usgs":true,"family":"Fulton","given":"John","middleInitial":"W,","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949518,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engel, Frank L. 0000-0002-4253-2625","orcid":"https://orcid.org/0000-0002-4253-2625","contributorId":218208,"corporation":false,"usgs":true,"family":"Engel","given":"Frank","middleInitial":"L.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949519,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eggleston, Jack R. 0000-0001-6633-3041","orcid":"https://orcid.org/0000-0001-6633-3041","contributorId":204628,"corporation":false,"usgs":true,"family":"Eggleston","given":"Jack R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":949520,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chiu, Chao-Lin","contributorId":361821,"corporation":false,"usgs":false,"family":"Chiu","given":"Chao-Lin","affiliations":[{"id":86362,"text":"Emeritus - University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":949521,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70265885,"text":"70265885 - 2025 - RIce-Net: Integrating ground-based cameras and machine learning for automated river ice detection","interactions":[],"lastModifiedDate":"2025-04-18T15:01:11.611637","indexId":"70265885","displayToPublicDate":"2025-04-15T09:45:42","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21202,"text":"Environmental Engineering & Software","active":true,"publicationSubtype":{"id":10}},"title":"RIce-Net: Integrating ground-based cameras and machine learning for automated river ice detection","docAbstract":"River ice plays a critical role in controlling streamflow in cold regions. The U.S. Geological Survey (USGS) qualifies affected water-level measurements and inferred streamflow by ice conditions at a date later than the day of the actual measurements. This study introduces a novel computer vision-based framework, River Ice-Network (RIce-Net), that uses the USGS nationwide network of ground-based cameras whose images are published through the National Imagery Management System (NIMS). RIce-Net consists of a binary classifier to identify ice-affected images that are segmented to calculate the fraction of ice coverage, which is used to automatically generate a near real-time ice flag. RIce-Net was trained using images from selected NIMS stations collected in 2023 and tested using images collected in 2024. Also, the framework’s scalability and transferability were tested over another station that was not included in the training process. RIce-Net ice flags are well-aligned with those reported by USGS.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2025.106454","usgsCitation":"Ayyad, M., Temini, M., Abdelkader, M., Henein, M., Engel, F.L., Lotspeich, R.R., and Eggleston, J., 2025, RIce-Net: Integrating ground-based cameras and machine learning for automated river ice detection: Environmental Engineering & Software, v. 190, 106454, 12 p., https://doi.org/10.1016/j.envsoft.2025.106454.","productDescription":"106454, 12 p.","ipdsId":"IP-170559","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":488461,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2025.106454","text":"Publisher Index 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Russell 0000-0002-5572-9064 rlotspei@usgs.gov","orcid":"https://orcid.org/0000-0002-5572-9064","contributorId":3388,"corporation":false,"usgs":true,"family":"Lotspeich","given":"R.","email":"rlotspei@usgs.gov","middleInitial":"Russell","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":false,"id":933816,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Eggleston, Jack R. 0000-0001-6633-3041","orcid":"https://orcid.org/0000-0001-6633-3041","contributorId":204628,"corporation":false,"usgs":true,"family":"Eggleston","given":"Jack R.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933817,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70257623,"text":"70257623 - 2024 - A two-dimensional, reach-scale implementation of space-time image velocimetry (STIV) and comparison to particle image velocimetry (PIV)","interactions":[],"lastModifiedDate":"2024-08-21T11:58:57.627306","indexId":"70257623","displayToPublicDate":"2024-05-14T06:54:21","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"A two-dimensional, reach-scale implementation of space-time image velocimetry (STIV) and comparison to particle image velocimetry (PIV)","docAbstract":"Image-based algorithms have become a powerful tool for estimating flow velocities in rivers. In this study, we generalize the space-time image velocimetry (STIV) framework for reach-scale application rather than along a cross section. The new algorithm provides information on both the magnitude and orientation of velocity vectors, and we refer to the algorithm as two-dimensional STIV, or 2D-STIV. The workflow involves setting up a grid, using centreline tangent vectors as initial estimates of flow direction, and then extracting space-time images (STIs) along search lines radiating from each grid node. The autocorrelation function is used to infer the inclination of streak lines present in STIs, which represents the advection of water surface features. Information on flow direction is obtained by evaluating various candidate search lines and identifying that which yields the highest velocity. This search can be performed exhaustively or via optimization. We applied the new 2D-STIV algorithm to three test cases, one simulated data set and two natural channels, and compared image-derived velocities to modelled or measured values. We also applied two established particle image velocimetry (PIV) algorithms to the same data sets. 2D-STIV performed as well as the two PIV algorithms for simulated images. For a natural river with distinct water surface features, 2D-STIV was effective for much of the channel but also led to a more patchy, irregular velocity field than the two PIV algorithms. For a site lacking obvious surface features, exhaustive 2D-STIV led to velocity estimates uncorrelated with field data while the optimization-based version produced erratic flow directions. 2D-STIV also required greater image sequence durations, higher frame rates, and generally longer computational run times. Overall, ensemble PIV was the most reliable algorithm.
Understanding the density-dependent processes that drive population demography in a changing world is critical in ecology, yet measuring performance–density relationships in long-lived mammalian species demands long-term data, limiting scientists' ability to observe such mechanisms. We tested performance–density relationships for an opportunistic omnivore, grizzly bears (Ursus arctos, Linnaeus, 1758) in the Greater Yellowstone Ecosystem, with estimates of body composition (lean body mass and percent body fat) serving as indicators of individual performance over two decades (2000–2020) during which time pronounced environmental changes have occurred. Several high-calorie foods for grizzly bears have mostly declined in recent decades (e.g., whitebark pine [Pinus albicaulis, Engelm, 1863]), while increasing human impacts from recreation, development, and long-term shifts in temperatures and precipitation are altering the ecosystem. We hypothesized that individual lean body mass declines as population density increases (H1), and that this effect would be more pronounced among growing individuals (H2). We also hypothesized that omnivory helps grizzly bears buffer energy intake from changing foods, with body fat levels being independent from population density and environmental changes (H3). Our analyses showed that individual lean body mass was negatively related to population density, particularly among growing-age females, supporting H1 and partially H2. In contrast, population density or sex had little effect on body fat levels and rate of accumulation, indicating that sufficient food resources were available on the landscape to accommodate successful use of shifting food sources, supporting H3. Our results offer important insights into ecological feedback mechanisms driving individual performances within a population undergoing demographic and ecosystem-level changes. However, synergistic effects of continued climate change and increased human impacts could lead to more extreme changes in food availability and affect observed population resilience mechanisms. Our findings underscore the importance of long-term studies in protected areas when investigating complex ecological relationships in an increasingly anthropogenic world.
The U.S. Geological Survey Community for Data Integration annually supports small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 14 projects supported in fiscal year 2019 and outlines their goals, activities, and accomplishments. Proposals in 2019 were encouraged to address the optional disciplinary theme of biosurveillance of emerging invasive species and health threats.
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U.S. Geological Survey
P.O. Box 25046, Mail Stop 302
Denver, CO 80225
Monitoring discharge in the Chicago Sanitary and Ship Canal is critical for the accounting done by the U.S. Army Corps of Engineers of the diversion of water from Lake Michigan to the Mississippi River Basin by the State of Illinois. The primary streamgage used for this discharge monitoring, the Chicago Sanitary and Ship Canal near Lemont, Illinois (U.S. Geological Survey station 05536890), is operated by the U.S. Geological Survey as an index-velocity station and at the time of this study (water years 2006–16) had two continuous velocity meters (an acoustic Doppler velocity meter and an acoustic velocity meter) and a water-level sensor, among other instruments. Discharge is computed at the streamgage using an index-velocity rating developed by linear regression of the velocity meter values fitted to discharges intermittently measured with an acoustic Doppler current profiler. In this study, the uncertainties of the velocity meters and stage sensors were estimated using a type B (judgment-based) approach, and measured discharge uncertainties were taken from those provided by a common acoustic Doppler current profiler data processing software tool, QRev. The velocity meter uncertainties, expressed as standard deviations, were estimated to be about 2.5 percent of velocity except near zero, where they exceeded that fraction, whereas for the acoustic Doppler current profiler uncertainties, when converted to mean channel velocity, 2.5 percent of velocity was determined to be a lower bound. The estimated velocity meter and measured discharge uncertainties were compared to index-velocity ratings developed from regression analyses of two types: (1) those that allow specification of measurement uncertainties and (2) ordinary least squares (OLS) regression, which does not. Based on the linearity of the index-velocity rating and the approximate agreement of the distributions of the fitting and prediction velocities, the assumptions required for unbiased prediction by OLS regression were determined to be approximately satisfied. From the regression residuals, it was determined that the estimated measurement uncertainties are too small, too similar between acoustic velocity meter and acoustic Doppler velocity meter velocities, and possibly too strongly dependent on velocity. Large, non-Gaussian OLS regression residuals also were observed. The uncertainty of annual mean discharge computed using the different regressions also was considered and was determined to be strongly dependent on the assumed measurement uncertainty. Because the assumptions required for OLS regression to give unbiased and variance-maintaining predictions were determined to be approximately satisfied, the results of discharge computation using the index-velocity rating based on OLS regression were deemed to be reliable. These results indicate about 0.8-percent uncertainty in the computed discharge as measured by the coefficient of variation at the annual time scale when using the acoustic Doppler velocity meter and 1.2-percent uncertainty with the acoustic velocity meter. It may be possible to improve the accuracy of the computed discharge and its uncertainty by further examining the measurement uncertainties and addressing differences in the distributions of the velocities used in fitting the index-velocity ratings and those used in prediction. Although the index-velocity ratings and computed discharges presented in this study are similar to those used in computing the published discharge at the study streamgage, the values presented in this report are not intended to replace the published discharge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221007","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Chicago District","usgsCitation":"Over, T.M., Muste, M., Duncker, J.J., Tsai, H., Jackson, P.R., Johnson, K.K., Engel, F.L., and Prater, C.D., 2022, Uncertainty analysis of index-velocity meters and discharge computations at the Chicago Sanitary and Ship Canal near Lemont, Illinois, water years 2006–16: U.S. Geological Survey Open-File Report 2022–1007, 35 p., https://doi.org/10.3133/ofr20221007.","productDescription":"Report: viii, 35 p.; Appendix; Data Release; Dataset","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-125889","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501754,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112755.htm","linkFileType":{"id":5,"text":"html"}},{"id":397713,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7X63K41","text":"USGS data release","linkHelpText":"Discharge measurements at U.S. Geological Survey streamgage 05536890 Chicago Sanitary and Ship Canal near Lemont, Illinois, 2005–2013"},{"id":397709,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2022/1007/ofr20221007_appendix2.pdf","text":"Appendix 2","size":"7.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1007 appendix 2","linkHelpText":"—Slides"},{"id":397714,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":397708,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1007/ofr20221007.pdf","text":"Report","size":"13.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1007"},{"id":397712,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1007/images"},{"id":397711,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1007/ofr20221007.XML"},{"id":397707,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1007/coverthb.jpg"}],"country":"United States","state":"Illinois","city":"Lemont","otherGeospatial":"Chicago Sanitary and Ship Canal","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.06846618652344,\n 41.66573093599398\n ],\n [\n -88.04718017578125,\n 41.64469659784919\n ],\n [\n -87.86796569824217,\n 41.699063978799174\n ],\n [\n -87.75672912597656,\n 41.789744876718984\n ],\n [\n -87.7979278564453,\n 41.83068856472101\n ],\n [\n -87.92701721191406,\n 41.75645886225854\n ],\n [\n -88.06709289550781,\n 41.6908605241911\n ],\n [\n -88.06846618652344,\n 41.66573093599398\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin Ave.
Urbana, IL 61801
In 2018, the U.S. Geological Survey (USGS), in cooperation with the Bandera County River Authority and Groundwater District and the Texas Water Development Board, studied floods through the period of record to create a library of flood-inundation maps for the Medina River at Bandera, Texas. Digital flood-inundation maps for a 23-mile reach of the Medina River at and near Bandera, from the confluence with Winans Creek to English Crossing Road, were developed. The flood-inundation maps depict estimates of the areal extent and depth of flooding corresponding to a range of different gage heights (gage height is commonly referred to as “stage,” or the water-surface elevation at a streamflow-gaging station) at USGS streamflow-gaging station 08178880 Medina River at Bandera, Tex. (hereinafter referred to as the “Bandera station”). Water-surface profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The stage-discharge (streamflow) relation effective in 2018 was used to calibrate the model, and stages from four recent flood events were used to independently validate the model. The calibrated hydraulic model was then used to compute 29 water-surface profiles for stages at 1-foot (ft) increments referenced to the station datum and ranging from 10 ft (near bankfull) to 38 ft, which exceeds the major flood stage of the National Weather Service Advanced Hydrologic Prediction Service of 24 ft. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging data having a 0.4-ft vertical accuracy and 1.6-ft horizontal resolution) to delineate the area flooded for stages ranging from 10 to 38 ft.
The digital flood-inundation maps are delivered through the USGS Flood Inundation Mapper application that presents map libraries and provides detailed information on flood-inundation extents and stages for modeled sites. The flood-inundation maps developed in this study, in conjunction with the real-time stage data from the Bandera station, are intended to help guide the public in taking individual safety precautions and provide emergency management personnel with a tool to efficiently manage emergency flood operations and post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195067","collaboration":"Prepared in cooperation with the Bandera County River Authority and Groundwater District and the Texas Water Development Board","usgsCitation":"Choi, N., and Engel, F.L., 2019, Flood-inundation maps for a 23-mile reach of the Medina River at Bandera, Texas, 2018: U.S. Geological Survey Scientific Investigations Report 2019–5067, 15 p., https://doi.org/10.3133/sir20195067.","productDescription":"Report: viii, 15 p.; Fact Sheet: 2 p.; Data Release","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-104084","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":366755,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/fs20193043","text":"FS 2019–3043","size":"895 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019–3043","linkHelpText":" Flood Warning Toolset for the Medina River in Bandera County, Texas"},{"id":366756,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WYD6LS","text":"USGS data release ","linkHelpText":"Geospatial and survey data for flood-inundation maps in a 23-mile reach of the Medina River at Bandera, Texas, 2018"},{"id":366666,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5067/coverthb.jpg"},{"id":366667,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5067/sir20195067.pdf","text":"Report","size":"3.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5067"}],"contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754–4501
Floods are the most common natural disaster in the United States. The Medina River in Bandera County, Texas, is in the Edwards Plateau, where high-intensity rain rates and steep terrain frequently contribute to severe flash flooding capable of causing loss of life and property. For example, the July 5, 2002, flood claimed a total of 12 lives in the central Texas area. The estimated peak discharge during this flood at U.S. Geological Survey (USGS) streamflow-gaging station 08178880 Medina River at Bandera, Tex., was 159,000 cubic feet per second (corresponding to a stage or gage height of 38.91 feet), causing significant flooding in Bandera near Mud Creek and farther downstream.
In 2018, the USGS, in cooperation with the Bandera County River Authority and Groundwater District and the Texas Water Development Board, developed a flood early-warning toolset to enhance the communication of flood risk and provide emergency management with additional information to improve flood response and mitigation. This toolset consists of a continuous streamflow-gage monitoring network, a well-calibrated hydraulic model of the Medina River, and a flood-inundation mapper application for the study area. A library of flood-inundation maps tied to the National Weather Service river stage forecast capability is included with the toolset.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193043","usgsCitation":"Engel, F.L., and Choi, N., 2019, Flood warning toolset for the Medina River in Bandera County, Texas: U.S. Geological Survey Fact Sheet 2019–3043, 2 p., https://doi.org/10.3133/fs20193043. ","productDescription":"Report: 2 p.; Companion Files","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-110193","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":366754,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/sir20195067","text":"SIR 2019–5067","size":"3.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5067","linkHelpText":" Flood-Inundation Maps for a 23-Mile Reach of the Medina River at Bandera, Texas, 2018"},{"id":366753,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3043/fs20193043.pdf","text":"Report","size":"895 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019–3043"},{"id":366752,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3043/coverthb.jpg"}],"country":"United States","state":"Texas","county":"Bandera County ","otherGeospatial":"Medina River","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-98.9253,29.7842],[-98.7869,29.7168],[-98.8056,29.6968],[-98.9213,29.5665],[-98.9245,29.562],[-98.9282,29.5593],[-98.9318,29.5588],[-98.9429,29.5585],[-98.9513,29.5581],[-98.9607,29.5578],[-98.9633,29.5578],[-98.9676,29.5546],[-98.9712,29.5533],[-98.9765,29.5547],[-98.978,29.5556],[-98.9811,29.5589],[-98.9832,29.5625],[-98.9837,29.5671],[-98.9836,29.5717],[-98.9819,29.5804],[-98.9818,29.5909],[-98.9801,29.5983],[-98.9779,29.606],[-98.9789,29.6102],[-98.9794,29.6129],[-98.982,29.6148],[-98.9909,29.6185],[-99.0103,29.6187],[-99.4132,29.6253],[-99.6033,29.6257],[-99.6031,29.9068],[-99.2839,29.905],[-99.1766,29.8946],[-98.9253,29.7842]]]},\"properties\":{\"name\":\"Bandera\",\"state\":\"TX\"}}]}","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754–4501
The Brandon Road Lock and Dam on the Des Plaines River near Joliet, Illinois, has been identified for potential implementation of aquatic nuisance species (ANS) control measures. To provide additional information concerning the flow hydraulics and mixing characteristics of the lock and downstream approach channel, the U.S. Geological Survey performed a detailed study of the site between December 2014 and October 2015, which included the collection and analysis of bathymetric, hydrodynamic, and dye tracer data. Synthesis of these data allowed a characterization of the site for future use in feasibility studies of potential ANS control technologies. The results of this study show a highly dynamic system driven primarily by lock operations but influenced by channel characteristics, industrial withdrawals, and meteorological forcing. Lock operation produces rapidly varying flows in the downstream approach channel, including transient oscillations that produce bidirectional flows. When the lock is not in operation, flows in the approach channel are primarily driven by leakage and wind forcing. Uniform concentrations of dissolved constituents in the lock chamber can be achieved by injection of the constituent into the existing lock filling and emptying system; however, valve and gate leakage can inhibit the mixing at the downstream end of the lock and substantially affects the ability to maintain a treated lock chamber at a uniform target concentration at tailwater level. Proper understanding of these hydraulic factors should be accounted for if the lock is to be used to deliver any dissolved constituent or operated in a way to prevent upstream passage of floating ANS. Moreover, extremely variable flow conditions including bidirectional flows and upstream return flows must be considered when implementing any ANS control technologies in the approach channel.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185094","collaboration":"Prepared in cooperation with the Great Lakes Restoration Initiative","usgsCitation":"Engel, F.L., Jackson, P.R., and Murphy, E.A., 2018, Flow hydraulics and mixing characteristics in and downstream from Brandon Road Lock, Joliet, Illinois: U.S. Geological Survey Scientific Investigations Report 2018–5094, 32 p., https://doi.org/10.3133/sir20185094.","productDescription":"Report: vii, 32 p.; 8 Data Releases","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-091674","costCenters":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":437814,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7K935SH","text":"USGS data release","linkHelpText":"Multibeam bathymetry and sediment depth data at select locations on the Des Plaines River near Joliet, Illinois, February 1314, 2017"},{"id":437813,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7S180NN","text":"USGS data release","linkHelpText":"Miscellaneous flow discharge measurements collected downstream of Brandon Road Lock and Dam"},{"id":437812,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F73F4MRV","text":"USGS data release","linkHelpText":"Bathymetric survey of the Brandon Road Dam Spillway, Joliet, Illinois"},{"id":437811,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74747Z7","text":"USGS data release","linkHelpText":"Rhodamine WT dye concentrations measured at fixed locations in the Des Plaines River near Brandon Road Lock and Dam near Rockdale, Illinois (October 20-21,2015)"},{"id":437810,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70G3H8C","text":"USGS data release","linkHelpText":"Spatial distribution of Rhodamine WT dye concentration measured in the Des Plaines River near Brandon Road Lock and Dam near Rockdale, Illinois (October 20-21, 2015)"},{"id":437809,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77W69B7","text":"USGS data release","linkHelpText":"Rhodamine WT dye concentration profiles measured at fixed stations in the Brandon Road Lock chamber near Rockdale, Illinois (October 20, 2015)"},{"id":437808,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VQ30S2","text":"USGS data release","linkHelpText":"Water surface elevation in the Brandon Road Lock chamber near Rockdale, Illinois (October 19-21, 2015)"},{"id":355952,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F70G3H8C","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Spatial distribution of Rhodamine WT dye concentration measured in the Des Plaines River near Brandon Road Lock and Dam near Rockdale, Illinois (October 20–21, 2015) "},{"id":355948,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P26X39","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Acoustic Doppler current profiler velocity and discharge measurements collected in and near the lock chamber of Brandon Road Lock and Dam, Joliet, Illinois, USA in December 2014 "},{"id":355949,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F73F4MRV","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Bathymetric survey of the Brandon Road Dam Spillway, Joliet, Illinois"},{"id":355950,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F77W69B7","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Rhodamine WT dye concentration profiles measured at fixed stations in the Brandon Road Lock chamber near Rockdale, Illinois (October 20, 2015)"},{"id":355953,"rank":10,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7VQ30S2","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water surface elevation in the Brandon Road Lock chamber near Rockdale, Illinois (October 19–21, 2015)"},{"id":355944,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5094/coverthb.jpg"},{"id":355945,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5094/sir20185094.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5094"},{"id":355946,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7K935SH ","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Multibeam bathymetry and sediment depth data at select locations on the Des Plaines River near Joliet, Illinois, February 13–14, 2017"},{"id":355947,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7S180NN","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Miscellaneous flow discharge measurements collected downstream of Brandon Road Lock and Dam"},{"id":355951,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F74747Z7","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Rhodamine WT dye concentrations measured at fixed locations in the Des Plaines River near Brandon Road Lock and Dam near Rockdale, Illinois (October 20–21, 2015)"}],"country":"United States","state":"Illinois","city":"Joliet","otherGeospatial":"Brandon Road Lock","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.3333,\n 41.37474755643594\n ],\n [\n -88.03276062011719,\n 41.37474755643594\n ],\n [\n -88.03276062011719,\n 41.6333\n ],\n [\n -88.3333,\n 41.6333\n ],\n [\n -88.3333,\n 41.37474755643594\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 N. Goodwin Ave.
Urbana, Illinois 61801
In 2016, the U.S. Fish and Wildlife Service, U.S. Geological Survey, and U.S. Army Corps of Engineers undertook a field study in the Chicago Sanitary and Ship Canal near Romeoville, Illinois to determine the influence of tow transit on the efficacy of the Electric Dispersal Barrier System (EDBS) in preventing the passage of juvenile fish (total length < 100 millimeters (mm)). Dual-frequency identification sonar data showed that large schools of juvenile fish (mean school size of 120 fish; n = 19) moved upstream and crossed the electric field of an array in the EDBS concurrent with downstream-bound (downbound) loaded tows in 89.5% of trials. Smaller schools of juvenile fish (mean school size of 98 fish; n = 15) moved downstream and crossed the electric field of an array in the EDBS concurrent with upstream-bound (upbound) loaded tows in 73.3% of trials. Observed fish passages through the EDBS were always opposite to the direction of tow movement, and not associated with propeller wash. These schools were not observed to breach the EDBS in the absence of a tow and showed no signs of incapacitation in the barrier during tow passage. Loaded tows transiting the EDBS create a return current of water flowing between the tow and the canal wall that typically travels opposite the direction of tow movement, and cause a decrease in the voltage gradient of the barrier of up to 88%. Return currents and decreases in voltage gradients induced by tow passage likely contributed to the observed fish passage through the EDBS. The efficacy of the EDBS in preventing the passage of small, wild fish is compromised while tows are moving across the barrier system. In particular, downbound tows moving through the EDBS create a pathway for the upstream movement of small fish, and therefore may increase the risk of transfer of invasive fishes from the Mississippi River Basin to the Great Lakes Basin.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2017.08.013","usgsCitation":"Davis, J.J., LeRoy, J., Shanks, M.R., Jackson, P.R., Engel, F.L., Murphy, E.A., Baxter, C.L., McInerney, M.K., and Barkowski, N.A., 2017, Effects of tow transit on the efficacy of the Chicago Sanitary and Ship Canal Electric Dispersal Barrier System: Journal of Great Lakes Research, v. 43, no. 6, p. 1119-1131, https://doi.org/10.1016/j.jglr.2017.08.013.","productDescription":"13 p.","startPage":"1119","endPage":"1131","ipdsId":"IP-086419","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":469530,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2017.08.013","text":"Publisher Index Page"},{"id":345662,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","city":"Romeoville","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.06166410446166,\n 41.64078396644512\n ],\n [\n -88.05765151977539,\n 41.64078396644512\n ],\n [\n -88.05765151977539,\n 41.648192108560146\n ],\n [\n -88.06166410446166,\n 41.648192108560146\n ],\n [\n -88.06166410446166,\n 41.64078396644512\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59b8f219e4b08b1644e0aeaf","contributors":{"authors":[{"text":"Davis, Jeremiah J.","contributorId":150963,"corporation":false,"usgs":false,"family":"Davis","given":"Jeremiah","email":"","middleInitial":"J.","affiliations":[{"id":13587,"text":"Bowling Green State University","active":true,"usgs":false}],"preferred":false,"id":710181,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LeRoy, Jessica Z. jleroy@usgs.gov","contributorId":174538,"corporation":false,"usgs":true,"family":"LeRoy","given":"Jessica Z.","email":"jleroy@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":710178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shanks, Matthew R.","contributorId":196367,"corporation":false,"usgs":false,"family":"Shanks","given":"Matthew","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":710182,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, Patrick Ryan","contributorId":34043,"corporation":false,"usgs":true,"family":"Jackson","given":"Patrick","email":"","middleInitial":"Ryan","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":710179,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Engel, Frank L. 0000-0002-4253-2625 fengel@usgs.gov","orcid":"https://orcid.org/0000-0002-4253-2625","contributorId":5463,"corporation":false,"usgs":true,"family":"Engel","given":"Frank","email":"fengel@usgs.gov","middleInitial":"L.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710180,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Murphy, Elizabeth A. 0000-0002-8939-7678 emurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-8939-7678","contributorId":196368,"corporation":false,"usgs":true,"family":"Murphy","given":"Elizabeth","email":"emurphy@usgs.gov","middleInitial":"A.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":710183,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Baxter, Carey L.","contributorId":196369,"corporation":false,"usgs":false,"family":"Baxter","given":"Carey","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":710184,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McInerney, Michael K.","contributorId":196370,"corporation":false,"usgs":false,"family":"McInerney","given":"Michael","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":710185,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Barkowski, Nicholas A.","contributorId":196371,"corporation":false,"usgs":false,"family":"Barkowski","given":"Nicholas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":710186,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70176364,"text":"70176364 - 2016 - Entrainment, retention, and transport of freely swimming fish in junction gaps between commercial barges operating on the Illinois Waterway","interactions":[],"lastModifiedDate":"2016-09-09T15:33:29","indexId":"70176364","displayToPublicDate":"2016-09-09T16:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Entrainment, retention, and transport of freely swimming fish in junction gaps between commercial barges operating on the Illinois Waterway","docAbstract":"Large Electric Dispersal Barriers were constructed in the Chicago Sanitary and Ship Canal (CSSC) to prevent the transfer of invasive fish species between the Mississippi River Basin and the Great Lakes Basin while simultaneously allowing the passage of commercial barge traffic. We investigated the potential for entrainment, retention, and transport of freely swimming fish within large gaps (> 50 m3) created at junction points between barges. Modified mark and capture trials were employed to assess fish entrainment, retention, and transport by barge tows. A multi-beam sonar system enabled estimation of fish abundance within barge junction gaps. Barges were also instrumented with acoustic Doppler velocity meters to map the velocity distribution in the water surrounding the barge and in the gap formed at the junction of two barges. Results indicate that the water inside the gap can move upstream with a barge tow at speeds near the barge tow travel speed. Water within 1 m to the side of the barge junction gaps was observed to move upstream with the barge tow. Observed transverse and vertical water velocities suggest pathways by which fish may potentially be entrained into barge junction gaps. Results of mark and capture trials provide direct evidence that small fish can become entrained by barges, retained within junction gaps, and transported over distances of at least 15.5 km. Fish entrained within the barge junction gap were retained in that space as the barge tow transited through locks and the Electric Dispersal Barriers, which would be expected to impede fish movement upstream.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2016.05.005","usgsCitation":"Davis, J.J., Jackson, P.R., Engel, F.L., LeRoy, J., Neeley, R.N., Finney, S.T., and Murphy, E.A., 2016, Entrainment, retention, and transport of freely swimming fish in junction gaps between commercial barges operating on the Illinois Waterway: Journal of Great Lakes Research, v. 42, no. 4, p. 837-848, https://doi.org/10.1016/j.jglr.2016.05.005.","productDescription":"12 p.","startPage":"837","endPage":"848","ipdsId":"IP-071305","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":328467,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","otherGeospatial":"Illinois Waterway","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.15498352050781,\n 41.492120839687786\n ],\n [\n -88.15498352050781,\n 41.66419207101119\n ],\n [\n -87.97096252441406,\n 41.66419207101119\n ],\n [\n -87.97096252441406,\n 41.492120839687786\n ],\n [\n -88.15498352050781,\n 41.492120839687786\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57d3cf23e4b0571647d15f4b","contributors":{"authors":[{"text":"Davis, Jeremiah J.","contributorId":150963,"corporation":false,"usgs":false,"family":"Davis","given":"Jeremiah","email":"","middleInitial":"J.","affiliations":[{"id":13587,"text":"Bowling Green State University","active":true,"usgs":false}],"preferred":false,"id":648528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jackson, P. Ryan 0000-0002-3154-6108 pjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-3154-6108","contributorId":173931,"corporation":false,"usgs":true,"family":"Jackson","given":"P.","email":"pjackson@usgs.gov","middleInitial":"Ryan","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":648527,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Engel, Frank L. 0000-0002-4253-2625 fengel@usgs.gov","orcid":"https://orcid.org/0000-0002-4253-2625","contributorId":5463,"corporation":false,"usgs":true,"family":"Engel","given":"Frank","email":"fengel@usgs.gov","middleInitial":"L.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":648529,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LeRoy, Jessica Z. jleroy@usgs.gov","contributorId":174538,"corporation":false,"usgs":true,"family":"LeRoy","given":"Jessica Z.","email":"jleroy@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":648530,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Neeley, Rebecca N.","contributorId":174535,"corporation":false,"usgs":false,"family":"Neeley","given":"Rebecca","email":"","middleInitial":"N.","affiliations":[{"id":5128,"text":"U.S. Fish and Wildlife Service, University of Montana, Missoula, MT 59812","active":true,"usgs":false}],"preferred":false,"id":648531,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Finney, Samuel T.","contributorId":174536,"corporation":false,"usgs":false,"family":"Finney","given":"Samuel","email":"","middleInitial":"T.","affiliations":[{"id":5128,"text":"U.S. Fish and Wildlife Service, University of Montana, Missoula, MT 59812","active":true,"usgs":false}],"preferred":false,"id":648532,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Murphy, Elizabeth A. emurphy@usgs.gov","contributorId":174537,"corporation":false,"usgs":true,"family":"Murphy","given":"Elizabeth","email":"emurphy@usgs.gov","middleInitial":"A.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":648533,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70170932,"text":"70170932 - 2016 - Three-dimensional flow structure and patterns of bed shear stress in an evolving compound meander bend","interactions":[],"lastModifiedDate":"2016-07-07T10:04:44","indexId":"70170932","displayToPublicDate":"2016-05-11T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Three-dimensional flow structure and patterns of bed shear stress in an evolving compound meander bend","docAbstract":"Compound meander bends with multiple lobes of maximum curvature are common in actively evolving lowland rivers. Interaction among spatial patterns of mean flow, turbulence, bed morphology, bank failures and channel migration in compound bends is poorly understood. In this paper, acoustic Doppler current profiler (ADCP) measurements of the three-dimensional (3D) flow velocities in a compound bend are examined to evaluate the influence of channel curvature and hydrologic variability on the structure of flow within the bend. Flow structure at various flow stages is related to changes in bed morphology over the study timeframe. Increases in local curvature within the upstream lobe of the bend reduce outer bank velocities at morphologically significant flows, creating a region that protects the bank from high momentum flow and high bed shear stresses. The dimensionless radius of curvature in the upstream lobe is one-third less than that of the downstream lobe, with average bank erosion rates less than half of the erosion rates for the downstream lobe. Higher bank erosion rates within the downstream lobe correspond to the shift in a core of high velocity and bed shear stresses toward the outer bank as flow moves through the two lobes. These erosion patterns provide a mechanism for continued migration of the downstream lobe in the near future. Bed material size distributions within the bend correspond to spatial patterns of bed shear stress magnitudes, indicating that bed material sorting within the bend is governed by bed shear stress. Results suggest that patterns of flow, sediment entrainment, and planform evolution in compound meander bends are more complex than in simple meander bends. Moreover, interactions among local influences on the flow, such as woody debris, local topographic steering, and locally high curvature, tend to cause compound bends to evolve toward increasing planform complexity over time rather than stable configurations.
","language":"English","publisher":"John Wiley & Sons","doi":"10.1002/esp.3895","usgsCitation":"Engel, F.L., and Rhoads, B.L., 2016, Three-dimensional flow structure and patterns of bed shear stress in an evolving compound meander bend: Earth Surface Processes and Landforms, v. 41, no. 9, p. 1211-1226, https://doi.org/10.1002/esp.3895.","productDescription":"16 p.","startPage":"1211","endPage":"1226","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059802","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":321116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"9","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-15","publicationStatus":"PW","scienceBaseUri":"5734499ee4b0dae0d5dd691b","contributors":{"authors":[{"text":"Engel, Frank L. 0000-0002-4253-2625 fengel@usgs.gov","orcid":"https://orcid.org/0000-0002-4253-2625","contributorId":5463,"corporation":false,"usgs":true,"family":"Engel","given":"Frank","email":"fengel@usgs.gov","middleInitial":"L.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629142,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rhoads, Bruce L.","contributorId":20248,"corporation":false,"usgs":true,"family":"Rhoads","given":"Bruce","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":629143,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70124986,"text":"sir20145176 - 2014 - Evaluation of a mass-balance approach to determine consumptive water use in northeastern Illinois","interactions":[],"lastModifiedDate":"2014-12-02T08:59:49","indexId":"sir20145176","displayToPublicDate":"2014-12-02T09:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5176","title":"Evaluation of a mass-balance approach to determine consumptive water use in northeastern Illinois","docAbstract":"A principal component of evaluating and managing water use is consumptive use. This is the portion of water withdrawn for a particular use, such as residential, which is evaporated, transpired, incorporated into products or crops, consumed by humans or livestock, or otherwise removed from the immediate water environment. The amount of consumptive use may be estimated by a water (mass)-balance approach; however, because of the difficulty of obtaining necessary data, its application typically is restricted to the facility scale. The general governing mass-balance equation is: Consumptive use = Water supplied - Return flows.
\nThis study explored a mass-balance field-based computation of consumptive use in a residential setting at the scale of a sanitary sewer service area (sewershed). In addition, the feasibility (cost and difficulty) and relative uncertainties (accuracies) associated with applying the approach at this scale were evaluated. The study was conducted during 2011–13 within a 3.5-square mile (mi2) sewershed confined to a predominantly residential area of Elk Grove Village, Illinois. Following background evaluation of the geohydrologic setting, sewershed infrastructure, and possible components of supplied and returned water, the identified primary components were
\n1. public water deliveries by the Elk Grove Village Department of Public Works,
\n2. self-served groundwater withdrawals in an included unincorporated neighborhood with public sanitary sewer service,
\n3. return flows to the sanitary sewer system, and
\n4. direct return of water discharged from swimming pools to Salt Creek. Water volumes principally were reported for deliveries, measured for sanitary sewer returns by using an acoustic Doppler current-velocity meter, and estimated for domestic withdrawals and swimming pool discharges to storm sewers. All water volumes required some degree of estimation. Observation wells were installed adjacent to sewer pipelines (lines) to determine the depth of the water table relative to that of the sewer lines and to collect water samples for detection of optical brighteners, as they are routinely discharged as clotheswashing waste to sanitary sewers. These data provided qualitative information on gains (inflow and infiltration) and losses (exfiltration) of sewer flow by pipe leakage, which might otherwise not be considered in the sewer flow return measurements. Hydrographs of sewer flow also were evaluated to identify and estimate storm-associated inputs to sewer flow.
\nThe volume of sanitary sewer return flow (778 million gallons per year [Mgal/yr]) was determined to substantially exceed the volume of supplied water (566 Mgal/yr), thus, for this study setting, voiding the utility of the applied mass-balance approach for estimating consumptive water use. Mass-balance components, including sanitary sewer flow and supplied-water use, were estimated within reasonable limits of uncertainty. Evidence of a water table that is typically shallower than the area’s sewer lines, yet is sometimes depressed near more deeply buried sewer lines, suggests groundwater infiltration into the sewers contributes to the excess volume of return flow. Technical obstacles and project resources precluded accurate quantification of infiltration volumes and other gains and losses to sanitary sewer flow. As estimated from various simplified methods, a minimum of 26 percent of return flow measured in the sanitary sewer represented groundwater infiltration and stormwater inflow; separately, about 2 percent of return flow was estimated as inflow. On the basis of the alternative winter base-rate method, consumptive use in the sewershed was estimated as 13 percent, which compares favorably with that used by the State of Illinois for Lake Michigan allocation accounting (10 percent) and other States and Canadian Provinces in the Great Lakes region (generally 10-15 percent).
\nThe study also provided other findings considered useful to studies of water use and to performance evaluation of sanitary sewer infrastructure. In urban residential settings, the comparatively small volumes of nonpublic sources of water (self-supplied) and direct (nonsanitary) return flow potentially can be ignored in the estimation of consumptive use. An acoustic Doppler current-velocity meter can be used in sanitary sewers to accurately measure discharge and reasonably estimate storm-associated inflows. Hourly to daily patterns of water use can be readily identified and quantified in the return flow record for the sanitary sewers. Relative volumes of infiltration gains (and exfiltration losses) can be substantial, even in sewer systems of communities making significant investments in system upgrades to limit sewer line leakage. Monitoring of optical brighteners in groundwater (and potentially in sanitary sewer flow) can provide a useful means of identifying probable leakage from (and to) sewer lines. Accurate quantification of gains and losses to sanitary sewer flow at the sewershed scale will require additional research effort and technical advances.
\nUnder ideal conditions, accurate quantification of consumptive use at the sewershed scale by the described mass-balance approach might be possible. Under most prevailing conditions, quantification likely would be more costly and time consuming than that of the present study, given the freely contributed technical support of the host community and relatively appropriate conditions of the study area. Essentials to quantification of consumptive use are a fully cooperative community, storm and sanitary sewers that are separate, and newer sewer infrastructure and (or) a robust program for limiting infiltration, exfiltration, and inflow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145176","collaboration":"U.S. Army Corps of Engineers- Chicago District","usgsCitation":"Mills, P., Duncker, J.J., Over, T.M., Marian Domanski, Marian Domanski, and Engel, F.L., 2014, Evaluation of a mass-balance approach to determine consumptive water use in northeastern Illinois: U.S. Geological Survey Scientific Investigations Report 2014-5176, viii, 90 p., https://doi.org/10.3133/sir20145176.","productDescription":"viii, 90 p.","numberOfPages":"102","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-045730","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":296338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145176.jpg"},{"id":296317,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5176/"},{"id":296337,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5176/pdf/sir2014-5176.pdf"}],"country":"United States","state":"Illinois","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"547ed4a3e4b09357f05f8a21","contributors":{"authors":[{"text":"Mills, P.C. pcmills@usgs.gov","contributorId":3810,"corporation":false,"usgs":true,"family":"Mills","given":"P.C.","email":"pcmills@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":525967,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duncker, James J. 0000-0001-5464-7991 jduncker@usgs.gov","orcid":"https://orcid.org/0000-0001-5464-7991","contributorId":4316,"corporation":false,"usgs":true,"family":"Duncker","given":"James","email":"jduncker@usgs.gov","middleInitial":"J.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":526058,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Over, Thomas M. 0000-0001-8280-4368 tmover@usgs.gov","orcid":"https://orcid.org/0000-0001-8280-4368","contributorId":1819,"corporation":false,"usgs":true,"family":"Over","given":"Thomas","email":"tmover@usgs.gov","middleInitial":"M.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":525968,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marian Domanski","contributorId":128046,"corporation":true,"usgs":false,"organization":"Marian Domanski","id":535671,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marian Domanski","contributorId":127611,"corporation":false,"usgs":false,"family":"Marian Domanski","affiliations":[{"id":7078,"text":"USGS IL WSC","active":true,"usgs":false}],"preferred":false,"id":525969,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Engel, Frank L. 0000-0002-4253-2625 fengel@usgs.gov","orcid":"https://orcid.org/0000-0002-4253-2625","contributorId":5463,"corporation":false,"usgs":true,"family":"Engel","given":"Frank","email":"fengel@usgs.gov","middleInitial":"L.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":526059,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70058009,"text":"70058009 - 2013 - Integrated carbon budget models for the Everglades terrestrial-coastal-oceanic gradient: Current status and needs for inter-site comparisons","interactions":[],"lastModifiedDate":"2013-12-03T16:05:03","indexId":"70058009","displayToPublicDate":"2013-12-03T15:54:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2929,"text":"Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Integrated carbon budget models for the Everglades terrestrial-coastal-oceanic gradient: Current status and needs for inter-site comparisons","docAbstract":"Recent studies suggest that coastal ecosystems can bury significantly \nmore C than tropical forests, indicating that continued coastal development and \nexposure to sea level rise and storms will have global biogeochemical consequences. \nThe Florida Coastal Everglades Long Term Ecological Research (FCE LTER) site \nprovides an excellent subtropical system for examining carbon (C) balance because \nof its exposure to historical changes in freshwater distribution and sea level rise and \nits history of significant long-term carbon-cycling studies. FCE LTER scientists used \nnet ecosystem C balance and net ecosystem exchange data to estimate C budgets \nfor riverine mangrove, freshwater marsh, and seagrass meadows, providing insights \ninto the magnitude of C accumulation and lateral aquatic C transport. Rates of net \nC production in the riverine mangrove forest exceeded those reported for many \ntropical systems, including terrestrial forests, but there are considerable uncertainties \naround those estimates due to the high potential for gain and loss of C through \naquatic fluxes. C production was approximately balanced between gain and loss in \nEverglades marshes; however, the contribution of periphyton increases uncertainty \nin these estimates. Moreover, while the approaches used for these initial estimates \nwere informative, a resolved approach for addressing areas of uncertainty is critically \nneeded for coastal wetland ecosystems. 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