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At least 1,801 records · Page 100Linked to original sources
USGS2010

Water resources of Monroe County, New York, water years 2003-08: Streamflow, constituent loads, and trends in water quality

This report, the sixth in a series published since 1994, presents analyses of hydrologic data in Monroe County for the period October 2002 through September 2008. Streamflows and water quality were monitored at nine sites by the Monroe County Department of Health and the U.S. Geological Survey. Streamflow yields (flow per unit area) were highest in Northrup Creek, which had sustained flows from year-round inflow from the village of Spencerport wastewater-treatment plant and seasonal releases from the New York State Erie (Barge) Canal. Genesee River streamflow yields also were high, at least in part, as a result of higher rainfall and lower evapotranspiration rates in the upper part of the Genesee River Basin than in the other study basins. The lowest streamflow yields were measured in Honeoye Creek, which reflected a decrease in flows due to the withdrawals from Hemlock and Canadice Lakes for the city of Rochester water supply. Water samples collected at nine monitoring sites were analyzed for nutrients, chloride, sulfate, and total suspended solids. The loads of constituents, which were computed from the concentration data and the daily flows recorded at each of the monitoring sites, are estimates of the mass of the constituents that was transported in the streamflow. Annual yields (loads per unit area) also were computed to assess differences in constituent transport among the study basins. All urban sites - Allen Creek and the two downstream sites on Irondequoit Creek - had seasonally high concentrations and annual yields of chloride. Chloride loads are attributed to the application of road-deicing salts to the county's roadways and are related to population and road densities. The less-urbanized sites in the study - Genesee River, Honeoye Creek, and Oatka Creek - had relatively low concentrations and yields of chloride. The highest concentrations and yields of sulfate were measured in Black Creek, Oatka Creek, and Irondequoit Creek at Railroad Mills and are attributable to dissolution of sulfate from gypsum (calcium sulfate) deposits in Silurian shale bedrock that crops out upstream from these monitoring sites. Northrup Creek had the highest concentrations of phosphorus, orthophosphate, and nitrogen, and high yields of nitrate plus nitrite nitrogen and ammonia plus organic nitrogen. These results are attributed to discharges from the Spencerport wastewater-treatment plant (which ceased operation in June 2008), diversions from the New York State Erie (Barge) Canal, and manure and fertilizers applied to agricultural fields. Concentrations and yields of nitrate plus nitrite nitrogen also were high in Oatka Creek and Black Creek; basins with substantial agricultural land uses. Allen Creek had the second highest yield of ammonia plus organic nitrogen. Honeoye Creek, which drains a relatively undeveloped basin, had the lowest yields of nitrogen constituents. The second highest median concentrations and highest sample concentrations of phosphorus and orthophosphate, as well as the highest phosphorus yields, were measured in the Genesee River. A comparison of the yields computed for the two downstream sites on Irondequoit Creek - above Blossom Road and at Empire Boulevard - permitted an assessment of the mitigative effects of the Ellison Park wetland on constituent loads, which would otherwise be transported to Irondequoit Bay. These effects also include those provided by a flow-control structure (installed mid-way through the wetland during February 1997), which was designed to increase the dispersal and short-term detention of stormflows in the wetland. The wetland decreased yields of particulate constituents - phosphorus and ammonia plus organic nitrogen - but had little effect on the yields of dissolved constituents - chloride, sulfate, and nitrate plus nitrite nitrogen. Trends in flow-adjusted concentrations were identified at all sites for most of the nutrient constituents that were evaluated. All of the linear time tren

Scientific Investigations Report↗
USGS2022

A Central Asia hydrologic monitoring dataset for food and water security applications in Afghanistan

From the Hindu Kush mountains to the Registan Desert, Afghanistan is a diverse landscape where droughts, floods, conflict, and economic market accessibility pose challenges for agricultural livelihoods and food security. The ability to remotely monitor environmental conditions is critical to support decision making for humanitarian assistance. The Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) global and Central Asia data streams provide information on hydrologic states for routine integrated food security analysis. While developed for a specific project, these data are publicly available and useful for other applications that require hydrologic estimates of the water and energy balance. These two data streams are unique because of their suitability for routine monitoring, as well as for being a historical record for computing relative indicators of water availability. The global stream is available at ∼ 1-month latency, and monthly average outputs are on a 10 km grid from 1982–present. The second data stream, Central Asia (21–56 ∘ N, 30–100 ∘ E), at ∼ 1 d latency, provides daily average outputs on a 1 km grid from 2000–present. This paper describes the configuration of the two FLDAS data streams, background on the software modeling framework, selected meteorological inputs and parameters, and results from previous evaluation studies. We also provide additional analysis of precipitation and snow cover over Afghanistan. We conclude with an example of how these data are used in integrated food security analysis. For use in new and innovative studies that will improve understanding of this region, these data are hosted by U.S. Geological Survey data portals and the National Aeronautics and Space Administration (NASA). The Central Asia data described in this paper can be accessed via the NASA repository at https://doi.org/10.5067/VQ4CD3Y9YC0R (Jacob and Slinski, 2021), and the global data described in this paper can be accessed via the NASA repository at https://doi.org/10.5067/5NHC22T9375G (McNally, 2018).

Earth System Science Data↗
USGS2004

Evaluating a Radar-Based, Non Contact Streamflow Measurement System in the San Joaquin River at Vernalis, California

Accurate measurement of flow in the San Joaquin River at Vernalis, California, is vital to a wide range of Federal and State agencies, environmental interests, and water contractors. The U.S. Geological Survey uses a conventional stage-discharge rating technique to determine flows at Vernalis. Since the flood of January 1997, the channel has scoured and filled as much as 20 feet in some sections near the measurement site resulting in an unstable stage-discharge rating. In response to recent advances in measurement techniques and the need for more accurate measurement methods, the Geological Survey has undertaken a technology demonstration project to develop and deploy a radar-based streamflow measuring system on the bank of the San Joaquin River at Vernalis, California. The proposed flow-measurement system consists of a ground-penetrating radar system for mapping channel geometries, a microwave radar system for measuring surface velocities, and other necessary infrastructure. Cross-section information derived from ground penetrating radar provided depths similar to those measured by other instruments during the study. Likewise, surface-velocity patterns and magnitudes measured by the pulsed Doppler radar system are consistent with near surface current measurements derived from acoustic velocity instruments. Since the ratio of surface velocity to mean velocity falls to within a small range of theoretical value, using surface velocity as an index velocity to compute river discharge is feasable. Ultimately, the non-contact radar system may be used to make continuous, near-real-time flow measurements during high and medium flows. This report documents the data collected between April 14, 2002 and May 17, 2002 for the purposes of testing this radar based system. Further analyses of the data collected during this field effort will lead to further development and improvement of the system.

Open-File Report↗
USGS2016

Examination of flood characteristics at selected streamgages in the Meramec River Basin, eastern Missouri, December 2015–January 2016

Overview Heavy rainfall resulted in major flooding in the Meramec River Basin in eastern Missouri during late December 2015 through early January 2016. Cumulative rainfall from December 14 to 29, 2015, ranged from 7.6 to 12.3 inches at selected precipitation stations in the basin with flooding driven by the heaviest precipitation (3.9–9.7 inches) between December 27 and 29, 2015. Financial losses from flooding included damage to homes and other structures, damage to roads, and debris removal. Eight of 11 counties in the basin were declared a Federal Disaster Area. The U.S. Geological Survey (USGS), in cooperation with the U.S. Army Corps of Engineers and St. Louis Metropolitan Sewer District, operates multiple streamgages along the Meramec River and its primary tributaries including the Bourbeuse River and Big River. The period of record for streamflow at streamgages in the basin included in this report ranges from 24 to 102 years. Instrumentation in a streamgage shelter automatically makes observations of stage using a variety of methods (submersible pressure transducer, non-submersible pressure transducer, or non-contact radar). These observations are recorded autonomously at a predetermined programmed frequency (typically either 15 or 30 minutes) dependent on drainage-area size and concomitant flashiness of the stream. Although stage data are important, streamflow data are equally or more important for streamflow forecasting, water-quality constituent loads computation, flood-frequency analysis, and flood mitigation planning. Streamflows are computed from recorded stage data using an empirically determined relation between stage and streamflow termed a “rating.” Development and verification of the rating requires periodic onsite discrete measurements of streamflow throughout time and over the range of stages to define local hydraulic conditions. The purpose of this report is to examine characteristics of flooding that occurred in the Meramec River Basin in December 2015–January 2016 including peak stages, peak streamflows, and the flood-frequency statistics associated with the peak flows. A comparison between the December 2015–January 2016 flood and a similar flood in December 1982 in the Meramec River Basin also is included.

Missouri↗
USGS2016

Statistical analysis and mapping of water levels in the Biscayne aquifer, water conservation areas, and Everglades National Park, Miami-Dade County, Florida, 2000–2009

Statistical analyses and maps representing mean, high, and low water-level conditions in the surface water and groundwater of Miami-Dade County were made by the U.S. Geological Survey, in cooperation with the Miami-Dade County Department of Regulatory and Economic Resources, to help inform decisions necessary for urban planning and development. Sixteen maps were created that show contours of (1) the mean of daily water levels at each site during October and May for the 2000–2009 water years; (2) the 25th, 50th, and 75th percentiles of the daily water levels at each site during October and May and for all months during 2000–2009; and (3) the differences between mean October and May water levels, as well as the differences in the percentiles of water levels for all months, between 1990–1999 and 2000–2009. The 80th, 90th, and 96th percentiles of the annual maximums of daily groundwater levels during 1974–2009 (a 35-year period) were computed to provide an indication of unusually high groundwater-level conditions. These maps and statistics provide a generalized understanding of the variations of water levels in the aquifer, rather than a survey of concurrent water levels. Water-level measurements from 473 sites in Miami-Dade County and surrounding counties were analyzed to generate statistical analyses. The monitored water levels included surface-water levels in canals and wetland areas and groundwater levels in the Biscayne aquifer. Maps were created by importing site coordinates, summary water-level statistics, and completeness of record statistics into a geographic information system, and by interpolating between water levels at monitoring sites in the canals and water levels along the coastline. Raster surfaces were created from these data by using the triangular irregular network interpolation method. The raster surfaces were contoured by using geographic information system software. These contours were imprecise in some areas because the software could not fully evaluate the hydrology given available information; therefore, contours were manually modified where necessary. The ability to evaluate differences in water levels between 1990–1999 and 2000–2009 is limited in some areas because most of the monitoring sites did not have 80 percent complete records for one or both of these periods. The quality of the analyses was limited by (1) deficiencies in spatial coverage; (2) the combination of pre- and post-construction water levels in areas where canals, levees, retention basins, detention basins, or water-control structures were installed or removed; (3) an inability to address the potential effects of the vertical hydraulic head gradient on water levels in wells of different depths; and (4) an inability to correct for the differences between daily water-level statistics. Contours are dashed in areas where the locations of contours have been approximated because of the uncertainty caused by these limitations. Although the ability of the maps to depict differences in water levels between 1990–1999 and 2000–2009 was limited by missing data, results indicate that near the coast water levels were generally higher in May during 2000–2009 than during 1990–1999; and that inland water levels were generally lower during 2000–2009 than during 1990–1999. Generally, the 25th, 50th, and 75th percentiles of water levels from all months were also higher near the coast and lower inland during 2000–2009 than during 1990–1999. Mean October water levels during 2000–2009 were generally higher than during 1990–1999 in much of western Miami-Dade County, but were lower in a large part of eastern Miami-Dade County.

Florida↗
USGS2020

Regional regression equations for estimation of four hydraulic properties of streams at approximate bankfull conditions for different ecoregions in Texas

The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, assessed statistical relations between hydraulic properties of streams at approximate bankfull conditions for different ecological regions (ecoregions) in Texas. Data from more than 103,000 records of measured discharge and ancillary hydraulic properties were assembled from summaries of discharge measurements for 424 U.S. Geological Survey streamgages in Texas. The data were subsequently subsetted at each streamgage for a streamgage-specific discharge interval centered on the estimated median annual peak discharge (0.5 annual exceedance probability) obtained from previously published regional regression equations in Texas in conjunction with the streamgage-specific sample median annual peak discharge for the period of record for each streamgage. Discharge measurements at gaged locations representing bankfull conditions (approximated from a discharge interval centered on the estimated median annual peak discharge at a given site) and associated watershed properties were subjected to rigorous statistical analysis. For most discharge measurements (where discharge is symbolically represented as Q ), the following hydraulic properties are available: cross-section area ( A ), water-surface top width ( B ), and reported mean velocity ( V ). Statewide summary statistics were computed by using these four hydraulic properties ( Q , A , B , and V ) and the following five watershed properties: (1) watershed area (contributing drainage area), (2) a multiple of main-channel slope (1,000 times main-channel slope), (3) mean annual precipitation, (4) drainage density, and (5) sinuosity ratio. From the initial set of 424 streamgages, summary statistics were computed for 372 selected streamgages in Texas and constitute the subsetted measurements dataset described in this report. Eight of the 10 ecoregions in Texas are represented in the statewide summary statistics. The resulting statistical relations, expressed as regression equations, can be used to estimate cross-section area, water-surface top width, discharge, and mean velocity of streams in different Texas ecoregions, at approximate bankfull conditions. In the regression equations, watershed properties were the independent variables for applicable watersheds, and predictions from the equations might be useful for estimating the four hydraulic properties at ungaged or unmonitored locations from selected characteristics measured at both the ungaged locations and gaged locations. Four regression equations to estimate the four hydraulic properties were identified as the preferred equations from this study. The four preferred equations use watershed area, mean annual precipitation, and aggregated ecoregion (treated as a categorical variable) to estimate the hydraulic properties, and justification is provided for this preference. For the four equations, the proportions of variance explained by the regression equations as measured by Nash-Sutcliffe efficiency are about 71 percent for cross-section area, 36 percent for top width, 76 percent for discharge, and 25 percent for mean velocity. Residual standard error (RSEs) of the regression equations are 0.252 log10 square feet for cross-section area, 0.319 log10 feet for top width, 0.247 log10 cubic feet per second for discharge, and 0.190 log10 feet per second for mean velocity, and the corresponding standard deviations of response are 0.465 log10 square feet, 0.397 log10 feet, 0.507 log10 cubic feet per second, and 0.220 log10 feet per second, respectively. The residual standard errors are less than the standard deviations as anticipated but show that the uncertainty reduction (percent change) for cross-section area is about −46 percent, about −20 percent for top width, about −51 percent for discharge, and about −14 percent for mean velocity.

Texas↗
USGS1986

Water resources scientific information center

The Water Resources Scientific Information Center (WRSIC) acquires, abstracts and indexes the major water resources related literature of the world, and makes information available to the water resources community and the public. A component of the Water Resources Division of the US Geological Survey, the Center maintains a searchable computerized bibliographic data base, and publishers a monthly journal of abstracts. Through its services, the Center is able to provide reliable scientific and technical information about the most recent water resources developments, as well as long-term trends and changes. WRSIC was established in 1966 by the Secretary of the Interior to further the objectives of the Water Resources Research Act of 1964--legislation that encouraged research in water resources and the prevention of needless duplication of research efforts. It was determined the WRSIC should be the national center for information on water resources, covering research reports, scientific journals, and other water resources literature of the world. WRSIC would evaluate all water resources literature, catalog selected articles, and make the information available in publications or by computer access. In this way WRSIC would increase the availability and awareness of water related scientific and technical information. (Lantz-PTT)

Open-File Report↗
USGS2013

Flood-inundation maps for the Iroquois River at Rensselaer, Indiana

Digital flood-inundation maps for a 4.0-mile reach of the Iroquois River at Rensselaer, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at USGS streamgage 05522500, Iroquois River at Rensselaer, Ind. Current conditions for estimating near-real-time areas of inundation using USGS streamgage information may be obtained on the Internet at (http://waterdata.usgs.gov/in/nwis/uv?site_no=05522500). In addition, the National Weather Service (NWS) forecasts flood hydrographs at the Rensselaer streamgage. That forecasted peak-stage information, also available on the Internet (http://water.weather.gov/ahps/), may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. For this study, flood profiles were computed for the Iroquois River reach by means of a one-dimensional step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the most current (June 27, 2012) stage-discharge relations at USGS streamgage 05522500, Iroquois River at Rensselaer, Ind., and high-water marks from the flood of July 2003. The calibrated hydraulic model was then used to determine nine water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to the highest stage of the current stage-discharge rating curve. The simulated water-surface profiles were then combined with a Geographic Information System digital elevation model (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from the USGS streamgage at Rensselaer, Ind., and forecasted stream stages from the NWS, provides emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.

Indiana↗
USGS2012

Trends in selected streamflow statistics at 19 long-term streamflow-gaging stations indicative of outflows from Texas to Arkansas, Louisiana, Galveston Bay, and the Gulf of Mexico, 1922-2009

Trends in selected streamflow statistics during 1922-2009 were evaluated at 19 long-term streamflow-gaging stations considered indicative of outflows from Texas to Arkansas, Louisiana, Galveston Bay, and the Gulf of Mexico. The U.S. Geological Survey, in cooperation with the Texas Water Development Board, evaluated streamflow data from streamflow-gaging stations with more than 50 years of record that were active as of 2009. The outflows into Arkansas and Louisiana were represented by 3 streamflow-gaging stations, and outflows into the Gulf of Mexico, including Galveston Bay, were represented by 16 streamflow-gaging stations. Monotonic trend analyses were done using the following three streamflow statistics generated from daily mean values of streamflow: (1) annual mean daily discharge, (2) annual maximum daily discharge, and (3) annual minimum daily discharge. The trend analyses were based on the nonparametric Kendall's Tau test, which is useful for the detection of monotonic upward or downward trends with time. A total of 69 trend analyses by Kendall's Tau were computed - 19 periods of streamflow multiplied by the 3 streamflow statistics plus 12 additional trend analyses because the periods of record for 2 streamflow-gaging stations were divided into periods representing pre- and post-reservoir impoundment. Unless otherwise described, each trend analysis used the entire period of record for each streamflow-gaging station. The monotonic trend analysis detected 11 statistically significant downward trends, 37 instances of no trend, and 21 statistically significant upward trends. One general region studied, which seemingly has relatively more upward trends for many of the streamflow statistics analyzed, includes the rivers and associated creeks and bayous to Galveston Bay in the Houston metropolitan area. Lastly, the most western river basins considered (the Nueces and Rio Grande) had statistically significant downward trends for many of the streamflow statistics analyzed.

Arkansas, Colorado, Louisiana, Oklahoma, New Mexic↗
USGS2026

The electric vehicle “EV”-crane—A next-generation system for fluvial sediment and water-quality sampling using an electric cart with integrated crane and accessories

The U.S. Geological Survey (USGS), with support from the Federal Interagency Sedimentation Project (FISP), developed the electric vehicle (EV)-crane, a modified electric cart equipped with a rigid swivel-mounted crane and integrated accessory holders. The EV-crane was developed to improve the efficiency and safety of fluvial sediment and water-quality sampling from bridges. USGS field staff have relied on foldable cranes on a four-wheeled base or nonstandardized platforms, such as utility terrain vehicle (UTV) mounted cranes, which highlight the need for a safer, standardized, and more adaptable solution. This redesigned platform replaces the foldable cranes on a four-wheeled base with a compact, powered system that reduces physical strain, enhances operator safety, and streamlines field operations on bridges. Dedicated holders for samplers, a controller, batteries, counterweights, and a field computer or tablet create a versatile, organized workspace that supports a wide range of sampling and heavy-lift applications. The EV-crane described here is version 1 of the prototype. Evaluation of the design is ongoing, and the findings summarized here are from initial qualitative user feedback and early quantitative testing. Potential plans may include additional testing and refinement to inform subsequent design iterations.

Open-File Report↗
USGS1995

Digital aeromagnetic anomaly data from eastern-most Guyana

The Center for Inter-American Mineral Resource Investigations (CIMRI) supported distribution and analysis of geoscientific and mineral resource related information concerning Latin America. CIMRI staff digitized aeromagnetic data for eastern-most Guyana as part of a preliminary regional assessment of minerals in the Guyana Shield, South America. The data were digitized from 145 aeromagnetic contour maps at a scale of 1:50,000 and merged into a single digital data set. The data were used to examine the Precambrian shield, greenstone belts, and other tectonic boundaries as well as explore ideas concerning mineral deposits within the area. A subset of these digital data were presented to the Guyanan government during early 1995 (Pierce, 1994). This Open-File report, consisting of this text and seven (7) 3.5" IBM-PC compatible ASCII magnetic disks, makes the digital data available to the public. Information regarding the source of data and subsequent processing is included below. The data were collected in Guyana by two contractors at different times. The first data were collected from 1962 to 1963. These data are several aeromagnetic surveys covering parts of 12 quadrangles funded by the United Nations and flown by Aero Service Corporation. The second and more extensive data set was collected from 1971 to 1972 by the Canadian International Development Agency flown by Terra Surveys Ltd. under a contract with the Geological Survey of Guyana. The Guyana Government published the data as contour maps that are available in Georgetown through the Guyana Government. Coverage extends from about 2°45*N to 8°30*N latitude and from 60°0'W to 57°0'W longitude (see Figure 1.). The contour maps were digitized at points where the magnetic contours intersect the flight lines. The data files include XYZ ASCII files, XYZ binary files, ASCII grids, and binary "standard USGS" grids. There are four grids consisting of the following data types: unprotected raw data grid unprotected residual or International Geomagnetic Reference Field (IGRF) removed grid UTM projected residual (IGRF removed) grid UTM projected residual with a second order surface removed These data files were transferred to 3.5" 1.44 megabyte floppy disks readable on IBM-compatible personal computers. These data are also available from the Department of Commerce National Geophysical Data Center.

Open-File Report↗
USGS2013

Flood-inundation maps for the East Fork White River at Columbus, Indiana

Digital flood-inundation maps for a 5.4-mile reach of the East Fork White River at Columbus, Indiana, from where the Flatrock and Driftwood Rivers combine to make up East Fork White River to just upstream of the confluence of Clifty Creek with the East Fork White River, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation, depict estimates of the areal extent of flooding corresponding to selected water levels (stages) at USGS streamgage 03364000, East Fork White River at Columbus, Indiana. Current conditions at the USGS streamgage may be obtained on the Internet from the USGS National Water Information System (http://waterdata.usgs.gov/in/nwis/uv/?site_no=03364000&agency_cd=USGS&). The National Weather Service (NWS) forecasts flood hydrographs for the East Fork White River at Columbus, Indiana at their Advanced Hydrologic Prediction Service (AHPS) flood warning system Website (http://water.weather.gov/ahps/), that may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relation at USGS streamgage 03364000, East Fork White River at Columbus, Indiana. The calibrated hydraulic model was then used to determine 15 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from bankfull to approximately the highest recorded water level at the streamgage. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from Light Detection and Ranging (LiDAR) data), having a 0.37-ft vertical accuracy and a 1.02 ft horizontal accuracy), in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from the USGS streamgage at Columbus, Indiana, and forecasted stream stages from the NWS will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for post-flood recovery efforts.

Indiana↗
USGS2010

Dissolved-Solids Load in Henrys Fork Upstream from the Confluence with Antelope Wash, Wyoming, Water Years 1970-2009

Annual dissolved-solids load at the mouth of Henrys Fork was estimated by using data from U.S. Geological Survey streamflow-gaging station 09229500, Henrys Fork near Manila, Utah. The annual dissolved-solids load for water years 1970-2009 ranged from 18,300 tons in 1977 to 123,300 tons in 1983. Annual streamflows for this period ranged from 14,100 acre-feet in 1977 to 197,500 acre-feet in 1983. The 25-percent trimmed mean dissolved-solids load for water years 1970-2009 was 44,300 tons per year at Henrys Fork near Manila, Utah. Previous simulations using a SPAtially Referenced Regression On Watershed attributes (SPARROW) model for dissolved solids specific to water year 1991 conditions in the Upper Colorado River Basin predicted an annual dissolved-solids load of 25,000 tons for the Henrys Fork Basin upstream from Antelope Wash. On the basis of computed dissolved-solids load data from Henrys Fork near Manila, Utah, together with estimated annual dissolved-solids load from Antelope Wash and Peoples Canal, this prediction was adjusted to 37,200 tons. As determined by simulations with the Upper Colorado River Basin SPARROW model, approximately 56 percent (14,000 tons per year) of the dissolved-solids load at Henrys Fork upstream from Antelope Wash is associated with the 21,500 acres of irrigated agricultural lands in the upper Henrys Fork Basin.

Scientific Investigations Report↗
USGS2015

Hydraulic, geomorphic, and trout habitat conditions of the Lake Fork of the Gunnison River in Hinsdale County, Lake City, Colorado, Water Years 2010-2011

Channel rehabilitation, or reconfiguration, to mitigate a variety of riverine problems has become a common practice in the western United States. However, additional work to monitor and assess the channel response to, and the effectiveness of, these modifications over longer periods of time (decadal or longer) is still needed. The Lake Fork of the Gunnison River has been an area of active channel modification to accommodate the needs of the Lake City community since the 1950s. The Lake Fork Valley Conservancy District began a planning process to assess restoration options for a reach of the Lake Fork in Lake City to enhance hydraulic and ecologic characteristics of the reach. Geomorphic channel form is affected by land-use changes within the basin and geologic controls within the reach. The historic channel was defined as a dynamic, braided channel with an active flood plain. This can result in a natural tendency for the channel to braid. A braided channel can affect channel stability of reconfigured reaches when a single-thread meandering channel is imposed on the stream. The U.S. Geological Survey, in cooperation with the Colorado Water Conservation Board and Colorado River Water Conservation District, began a study in 2010 to quantify existing hydraulic and habitat conditions for a reach of the Lake Fork of the Gunnison River in Lake City, Colorado. The purpose of this report is to quantify existing Lake Fork hydraulic and habitat conditions and establish a baseline against which post-reconfiguration conditions can be compared. This report (1) quantifies the existing hydraulic and geomorphic conditions in a 1.1-kilometer section of the Lake Fork at Lake City that has been proposed as a location for future channel-rehabilitation efforts, (2) characterizes the habitat suitability of the reach for two trout species based on physical conditions within the stream, and (3) characterizes the current riparian canopy density. The FaSTMECH computational flow-model within MD_SWMS was selected to characterize the effects of streamflow on hydraulic and habitat-suitability conditions for a study reach of the Lake Fork. Habitat suitability was evaluated for cutthroat ( Oncorhynchus clarkii ) and brown trout ( Salmo trutta morpha fario ) fry, juveniles, and adults. Microscale (point locations) and mesoscale (reach features) habitats were assessed using the combination of field observations, measurements, and hydraulic simulations within the study reach of the Lake Fork. Microscale trout habitat, presented as weighted usable area, generally increased as streamflow increased for both trout species and all life stages. Areas of suitable microscale habitat occur along the banks for flows of 900 cubic feet per second (ft 3 /s) and less. Out-of-bank areas became more substantial contributors to overall habitat availability for flows of 1,300 ft 3 /s or more when compared to other features. Adult habitat, for both trout species, was the most abundant habitat type for nearly all streamflows. In general, the upper reach provided 2–3 times more available habitat than the lower reach for both trout species. Mesoscale trout habitat of the Lake Fork was assessed based on the conditions present in the 150 ft 3 /s flow simulation as well as field observation. Both the upper and lower reach is primarily characterized as riffle/run habitat. The presence of pool habitat was limited throughout both reaches and occurred along the channel margins. For both reaches, the pool habitat was less than 5 percent of the total wetted area, a percentage that is substantially lower than the recommendations for sustainable populations of 40–70 percent. Areas of cover were adjacent to potential drift feeding areas in the lower reach, and often occurred within the same pool habitat. This may favor energy expenditure ratios of both fish species, wherein little energy is needed to acquire adequate food sources. Sediment mobility is an important process for flushing fine sediments from within the gravel frameworks. Evaluations of channel and flow characteristics at cross-section locations 2–8 show a range of streambed mobility. In general, boundary shear stress and streambed mobility increase with increases in streamflow. Within the cross sections, the greatest boundary shear stress occurs towards the center of the channel. Reach-scale assessment of sediment mobility in the lower reach shows increased streambed mobility. This is due in part to smaller grain sizes in the lower reach, but may also reflect the greater extent of channel alterations, specifically the temporary berms constructed by CDOT in the late 1980s and 1990s, present in this reach.

Colorado↗
USGS2018

Flood-inundation maps for the Patoka River in and near Jasper, southwestern Indiana

Digital flood-inundation maps for a 9.5-mile reach of the Patoka River in and near the city of Jasper, southwestern Indiana (Ind.), from the streamgage near County Road North 175 East, downstream to State Road 162, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science web site at https://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage Patoka River at Jasper, Ind. (station number 03375500). The Patoka streamgage is located at the upstream end of the 9.5-mile river reach. Near-real-time stages at this streamgage may be obtained from the USGS National Water Information System at https://waterdata.usgs.gov/ or the National Weather Service Advanced Hydrologic Prediction Service at http://water.weather.gov/ahps/ , although flood forecasts and stages for action and minor, moderate, and major flood stages are not currently (2017) available at this site (JPRI3). Flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relation at the Patoka River at Jasper, Ind., streamgage and the documented high-water marks from the flood of April 30, 2017. The calibrated hydraulic model was then used to compute five water-surface profiles for flood stages referenced to the streamgage datum ranging from 15 feet (ft), or near bankfull, to 19 ft. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging [lidar] data having a 0.98 ft vertical accuracy and 4.9 ft horizontal resolution) to delineate the area flooded at each water level. The availability of these flood-inundation maps, along with real-time stage from the USGS streamgage at the Patoka River at Jasper, Ind., will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for postflood recovery efforts.

Indiana↗
USGS2019

Methods for estimating the magnitude and frequency of peak streamflows for unregulated streams in Oklahoma developed by using streamflow data through 2017

The U.S. Geological Survey (USGS), in cooperation with the Oklahoma Department of Transportation, updated peak-streamflow regression equations for estimating flows with annual exceedance probabilities from 50 to 0.2 percent for the State of Oklahoma. These regression equations incorporate basin characteristics to estimate peak-streamflow magnitude and frequency throughout the State by use of a generalized least-squares regression analysis. The most statistically significant independent variables required to estimate peak-streamflow magnitude and frequency for unregulated streams in Oklahoma are contributing drainage area, mean-annual precipitation, and main-channel slope. The regression equations are applicable for stream basins with drainage areas less than 2,510 square miles that are not affected by regulation. The standard model error ranged from 31.28 to 49.32 percent for the different annual exceedance probabilities that were computed. Annual-maximum peak flows observed at 212 USGS streamgages through water year 2017 were used for the regression analysis, excluding the Oklahoma Panhandle region. The USGS StreamStats web application was used to obtain the independent variables required for the peak-streamflow regression equations. Limitations on the use of the regression equations and the reliability of regression estimates for natural unregulated streams are described. Log-Pearson Type III analysis information, basin and climate characteristics, and the peak-streamflow frequency estimates for the 212 streamgages in and near Oklahoma are provided in this report. This report contains descriptions of the methods that can be used to estimate peak streamflows at ungaged sites by using estimates from streamgages on unregulated streams. For ungaged sites on urban streams and streams regulated by small floodwater-retarding structures, an adjustment of the statewide regression equations for natural unregulated streams can be used to estimate peak-streamflow magnitude and frequency.

Arkansas, Kansas, Missouri, Oklahoma, Texas↗
USGS2018

A practical primer on geostatistics

Introduction The Challenge —Most geological phenomena are extraordinarily complex in their interrelationships and vast in their geographical extension. Ordinarily, engineers and geoscientists are faced with corporate or scientific requirements to properly prepare geological models with measurements involving a small fraction of the entire area or volume of interest. Exact description of a system such as an oil reservoir is neither feasible nor economically possible. The results are necessarily uncertain. Note that the uncertainty is not an intrinsic property of the systems; it is the result of incomplete knowledge by the observer. The Aim of Geostatistics —The main objective of geostatistics is the characterization of spatial systems that are incompletely known, systems that are common in geology. A key difference from classical statistics is that geostatistics uses the sampling location of every measurement. Unless the measurements show spatial correlation, the application of geostatistics is pointless. Ordinarily the need for additional knowledge goes beyond a few points, which explains the display of results graphically as fishnet plots, block diagrams, and maps. Geostatistical Methods —Geostatistics is a collection of numerical techniques for the characterization of spatial attributes using primarily two tools: probabilistic models, which are used for spatial data in a manner similar to the way in which time-series analysis characterizes temporal data, or pattern recognition techniques. The probabilistic models are used as a way to handle uncertainty in results away from sampling locations, making a radical departure from alternative approaches like inverse distance estimation methods. Differences with Time Series —On dealing with time-series analysis, users frequently concentrate their attention on extrapolations for making forecasts. Although users of geostatistics may be interested in extrapolation, the methods work at their best interpolating. This simple difference has significant methodological implications. Historical Remarks —As a discipline, geostatistics was firmly established in the 1960s by the French engineer Georges Matheron, who was interested in the appraisal of ore reserves in mining. Geostatistics did not develop overnight. Like other disciplines, it has built on previous results, many of which were formulated with different objectives in various fields. Pioneers —Seminal ideas conceptually related to what today we call geostatistics or spatial statistics are found in the work of several pioneers, including: 1940s: A.N. Kolmogorov in turbulent flow and N. Wiener in stochastic processing; 1950s: D. Krige in mining; 1960s: B. Mathern in forestry and L.S. Gandin in meteorology Calculations —Serious applications of geostatistics require the use of digital computers. Although for most geostatistical techniques rudimentary implementation from scratch is fairly straightforward, coding programs from scratch is recommended only as part of a practice that may help users to gain a better grasp of the formulations. Software —For professional work, the reader should employ software packages that have been thoroughly tested to handle any sampling scheme, that run as efficiently as possible, and that offer graphic capabilities for the analysis and display of results. This primer employs primarily the package Stanford Geomodeling Software (SGeMS) - recently developed at the Energy Resources Engineering Department at Stanford University - as a way to show how to obtain results practically. This applied side of the primer should not be interpreted as the notes being a manual for the use of SGeMS. The main objective of the primer is to help the reader gain an understanding of the fundamental concepts and tools in geostatistics. Organization of the Primer —The chapters of greatest importance are those covering kriging and simulation. All other materials are peripheral and are included for better comprehension of these main geostatistical modeling tools. The choice of kriging versus simulation is often a big puzzle to the uninitiated, let alone the different variants of both of them. Chapters 14, 18, and 19 are intended to shed light on those subjects. The critical aspect of assessing and modeling spatial correlation is covered in chapter 7. Chapters 2 and 3 review relevant concepts in classical statistics. Course Objectives —This course offers stochastic solutions to common problems in the characterization of complex geological systems. At the end of the course, participants should have: an understanding of the theoretical foundations of geostatistics; a good grasp of its possibilities and limitations; and reasonable familiarity with the SGeMS software, thus opening the possibility of practically applying geostatistics.

Open-File Report↗
USGS2025

Evaluating Three-Dimensional Elevation Program lidar consistency and accuracy at scale using cloud-native, open-source methods

The U.S. Geological Survey three-dimensional elevation program (3DEP) has significantly expanded national lidar coverage, necessitating scalable, reproducible methods for assessing data quality across diverse terrains and acquisition conditions. This study introduces a cloud-native, open-source workflow designed to evaluate the geometric accuracy and consistency of 3DEP lidar data sets at a national scale. Leveraging tools such as the Point Data Abstraction Library, Open3D, and Amazon Web Services infrastructure, the workflow integrates global navigation satellite system‐surveyed ground control points and terrestrial laser scanning data to validate airborne lidar collections. Two case studies demonstrate the application of this process. In Puerto Rico, the process identified vertical biases and inconsistencies in vegetated areas, while in Iowa and Arizona, the process confirmed high vertical accuracy with minimal bias. The results underscore the effectiveness of combining cloud computing with open-source tools to perform large-scale lidar data quality assessments. This process offers a reproducible, efficient solution for nationwide validation of 3DEP data sets, supporting enhanced decision-making in geospatial applications.

Photogrammetric Engineering and Remote Sensing↗

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