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The Best Management Practices Statistical Estimator (BMPSE) was developed by the U.S. Geological Survey (USGS), in cooperation with the Federal Highway Administration (FHWA) Office of Project Delivery and Environmental Review to provide planning-level information about the performance of structural best management practices for decision makers, planners, and highway engineers to assess and mitigate possible adverse effects of highway and urban runoff on the Nation's receiving waters (Granato 2013, 2014; Granato and others, 2021a,b). The BMPSE was used to calculate statistics and create input files for fitting the trapezoidal distribution to data from studies documenting the performance of individual structural stormwater...
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IMPORTANT NOTE: A more recent version of this data release is available from this link. This data release is the update of the U.S. Geological Survey - ScienceBase data release by Bera and Over (2016), with the processed data through September 30, 2015. The primary data for each year is downloaded from the ANL website (http://gonzalo.er.anl.gov/ANLMET/numeric/) and is processed following the guidelines documented in Over and others (2010) and Bera (2014). Hourly potential evapotranspiration computed using the computer program LXPET (Lamoreux Potential Evapotranspiration). Murphy (2005) describes in detail the computer program LXPET. References Cited: ...
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This data release is the update of the U.S. Geological Survey - ScienceBase data release by Bera and Over (2018), with the data processed through September 30, 2018. The primary data for water year 2018 (a water year is the 12-month period, October 1 through September 30, designated by the calendar year in which it ends) were downloaded from the Argonne National Laboratory (ANL) (Argonne National Laboratory, 2018) and processed following the guidelines documented in Over and others (2010). Daily potential evapotranspiration (PET) is computed from average daily air temperature, average daily dewpoint temperature, daily total wind speed, and daily total solar radiation, and disaggregated to hourly PET by using the...
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This data release (DR) is the update of the U.S. Geological Survey - ScienceBase data release by Bera (2022), with the processed data through September 30, 2022. The primary data for water year 2022 (a water year is the 12-month period, October 1 through September 30, in which it ends) is downloaded from the Argonne National Laboratory (ANL) (Argonne National Laboratory, 2022) and is processed following the guidelines documented in Over and others (2010). This DR also describes the Watershed Data Management (WDM) database file ARGN22.WDM. The WDM file ARGN22.WDM is an update of ARGN21.WDM (Bera, 2022) with the processed data from October 1, 2021, through September 30, 2022, appended to it. ARGN22.WDM file contains...
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The Database was built to enable data integration across sources, as well as to support program planning and observational network design. The Imiq Data Portal provides a snapshot of available hydroclimate data – a map-based view of where , what , and when data have been obtained. Users can submit a custom data query, specifying variable of interest, geographic bounds, and time step. Imiq will aggregate and export data records from multiple sources in a common format, with full metadata records that provide information about the source data.
Categories: Data; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: ABLATION, ABLATION, ACTIVE LAYER, ACTIVE LAYER, ALBEDO, All tags...
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This part of the Data Release contains the raster representation of the water-level altitude and water-level change maps developed every 5 years from 1980-2015 for the upper Rio Grande Focus Area Study. The input point data used to generate the water-level altitude maps can be found in the "Groundwater level measurement data used to develop water-level altitude maps in the upper Rio Grande Alluvial Basins" child item of this data release. These digital data accompany Houston, N.A., Thomas, J.V., Foster, L.K., Pedraza, D.E., and Welborn, T.L., 2020, Hydrogeologic framework, groundwater-level altitudes, groundwater-level changes, and groundwater-storage changes in selected alluvial basins of the upper Rio Grande...
Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Abiquiu Reservoir, Ahumada, Alamosa, Alamosa County, Alamosa Creek, All tags...
This data release documents statistics for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM)(Granato, 2013). The U.S. Geological Survey (USGS) developed SELDM and the statistics documented in this report in cooperation with the Federal Highway Administration (FHWA) to indicate the risk for stormwater flows, concentrations, and loads to be above user-selected water-quality goals and the potential effectiveness of mitigation measures to reduce such risks. In SELDM, three treatment variables, hydrograph extension, runoff volume reduction, and water-quality treatment are modeled by using the trapezoidal distribution and the rank...
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The Highway-Runoff Database (HRDB) was developed by the U.S. Geological Survey (USGS), in cooperation with the Federal Highway Administration (FHWA) Office of Project Delivery and Environmental Review to provide planning-level information for decision makers, planners, and highway engineers to assess and mitigate possible adverse effects of highway runoff on the Nation's receiving waters (Granato and Cazenas, 2009; Granato, 2013; Granato and others, 2018). The HRDB was assembled by using a Microsoft Access database application to facilitate use of the data and to calculate runoff-quality statistics with methods that properly handle censored-concentration data. The HRDB was first published as version 1.0 in cooperation...
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This dataset describes the storm event mean concentrations and loads of total and dissolved forms of phosphorus and nitrogen from paired samples collected in the control and test catchment during the calibration and treatment phase of a leaf removal study in Madison, Wisconsin, USA. Samples were collected in spring 2013 through fall 2015 and are parsed by season where spring represents April – May, summer represents June – September and fall represents October – November. Measured weather parameters for each sampled storm event are also described. These data are interpreted in a journal article published in Science of the Total Environment.
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The Imiq Hydroclimate Database houses hydrologic, climatologic, and soils data collected in Alaska and Western Canada from the early 1900s to the present. This database unifies and preserves numerous data collections that have, until now, been stored in field notebooks, on desktop computers, as well as in disparate databases. Synthesizing and analyzing the large-scale hydroclimate characteristics of this important climatic region have been made easier with this searchable database. The data, originally collected in a Microsoft SQL Server 2008 relational database, has been migrated to an open source PostgreSQL and PostGIS environment. The Imiq Data Portal provides public access to portions of the Imiq Hydroclimate...
Categories: Data, Project; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: ABLATION, ABLATION, ACTIVE LAYER, ACTIVE LAYER, ALBEDO, All tags...
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Impervious runoff-discharge to receiving streams is widely recognized as one of the leading factors contributing to ecological degradation in such streams. Although there are many factors that contribute to ecological degradation with increasing development adverse effects caused by runoff quality is widely recognized as a contributing factor. The objective of this study was to simulate the flows concentrations and loads of impervious-area runoff and stormflows from an undeveloped area over a range of impervious percentages and drainage areas to examine potential relations between these variables and the quantity and quality of downstream flows. Stormwater runoff in a hypothetical stream basin that represents hydrologic...
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A monthly water balance model (MWBM) was driven with precipitation and temperature using a station-based dataset for current conditions (1949 to 2010) and selected statistically-downscaled general circulation models (GCMs) for current and future conditions (1950 to 2099) across the conterminous United States (CONUS) using hydrologic response units from the Geospatial Fabric for National Hydrologic Modeling (Viger and Bock, 2014). Six MWBM output variables (actual evapotranspiration (AET), potential evapotranspiration (PET), runoff (RO), streamflow (STRM), soil moisture storage (SOIL), and snow water equivalent (SWE)) and the two MWBM input variables (atmospheric temperature (TAVE) and precipitation (PPT)) were summarized...
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For about 10 years, the U.S. Geological Survey (USGS) has monitored water quality and streamflow in three agricultural drainage ditches in an effort to evaluate the influence of best management practices on water quality. These ditches are small tributaries to oxbow lakes located in the Mississippi Alluvial Plain of northwestern Mississippi--two sites (LWSR and LWT2) drain to Lake Washington and one site (BLT1) drains to Bee Lake. Streamflow was intermittent at these sites and the ditches were dry much of the year. When streamflow was present, flows were measured on 15-minute intervals and water-quality samples were collected over the course of the flow event using an automated sampler. These datasets were aggregated...
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Santa Rosa Island, part of Channel Islands National Park off the coast of California, has a undergone a history of ecologic degradation due to introduced ungulate grazing for ranching (cattle and sheep) and hunting (deer and elk) purposes. Grazing in many parts of the island has resulted in widespread vegetation loss and subsequent erosion presumably causing changes in infiltration/runoff relations. In some areas, large sections of bedrock are exposed while other areas have thin soils left with much of the organic-rich materials removed. The reestablishment of healthy ecosystems on land severely degraded by long-term alternative use is challenging. This issue is especially critical in cloud forests where the soil...
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Discrete volumetric and mid-section stream discharge measurements were conducted from July through October 2020 in H.J. Andrews Experimental Forest near Blue River, OR. The measured streams are part of the Lookout Creek basin, draining into Blue River and subsequently the McKenzie River on the west slope of the Cascade Range. ORWSC Streamflow measurements supplemented an eco-drought low-flow modeling project in partnership with the Forest and Rangeland Ecosystem Science Center (FRESC) and the USGS Water Mission Area (WMA). Measurements were collected at 25 selected sites with co-located HOBO data loggers and 7 miscellaneous (MISC) sites with no data loggers present. HOBO logger data were collected and processed...
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The Stochastic Empirical Loading and Dilution Model (SELDM) was developed by the U.S. Geological Survey (USGS), in cooperation with the Federal Highway Administration (FHWA) Office of Project Delivery and Environmental Review to transform complex scientific data into meaningful information about the risk of adverse effects of runoff on receiving waters, the potential need for mitigation measures, and the potential effectiveness of such management measures for reducing these risks (Granato 2013; Granato and Jones, 2014). SELDM is a stochastic model because it uses Monte Carlo methods to produce the random combinations of input variable values needed to generate the stochastic population of values for each component...
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Hydrologic data for the Alaska Arctic are sparse, and fewer still are long-term (> 10 year) datasets. This lack of baseline information hinders our ability to assess long-term alterations in streamflow due to changing climate. The Arctic LCC is provided stop-gap funding to continue this long time series hydrological data sets in the Kuparuk and Putuligayuk watersheds.
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The USGS and Arctic National Wildlife Refuge Staff operate and maintain a streamgage at Hulahula River near Kaktovik, Alaska. Data from this station is necessary to complement glacier mass-balance studies and provide information necessary to project stream flow regimes under various scenarios of climate change. This project includes operation, acquiring real-time data, analysis of the data, and internet access. The gauge continues to operate as of 2017.


map background search result map search result map Monthly Water Balance Model Futures Concentration of total and dissolved forms of phosphorus and nitrogen from the control and test catchment during the calibration and treatment phase in Madison, WI (2013 - 2015) Meteorological Database, Argonne National Laboratory, Illinois, January 1, 1948 - September 30, 2015 Streamflow monitoring on the Canning and Tamayariak rivers. Streamflow Monitoring on Upper Kuparuk and Putuligayuk Rivers (2010) Imiq - Hydroclimate Database and Data Portal Hydrologic Monitoring of Glacier-Influenced Watersheds (Hulahula Gage) Imiq Data Portal Hydrologic event-based water-quality and streamflow data for three oxbow tributaries in northwestern Mississippi, 2007-2016 Meteorological Database, Argonne National Laboratory, Illinois, January 1, 1948 - September 30, 2018 Highway-Runoff Database (HRDB) Version 1.1.0 Model archive for analysis of the effects of impervious cover on receiving-water quality with the Stochastic Empirical Loading Dilution Model (SELDM) Groundwater-level altitude and groundwater-level change maps developed for the groundwater component of the upper Rio Grande Focus Area Study Stable isotopic ratios of hydrogen and oxygen in groundwater and calculated fraction of recharge from winter precipitation, South Rim Grand Canyon, Arizona Statistics for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM) Best Management Practices Statistical Estimator (BMPSE) Version 1.2.0 Stochastic Empirical Loading and Dilution Model (SELDM) software archive Hydraulic Property Data at the Santa Rosa Island Cloud Forest Restoration Site 2017-2019, Channel Islands National Park, California, USA Volumetric and Mid-Section Discharge Measurement data, Summer through Fall 2020, H.J. Andrews Experimental Forest, Lookout Creek Basin, Oregon Meteorological Database, Argonne National Laboratory, Illinois, January 1, 1948 - September 30, 2022 Hydraulic Property Data at the Santa Rosa Island Cloud Forest Restoration Site 2017-2019, Channel Islands National Park, California, USA Concentration of total and dissolved forms of phosphorus and nitrogen from the control and test catchment during the calibration and treatment phase in Madison, WI (2013 - 2015) Meteorological Database, Argonne National Laboratory, Illinois, January 1, 1948 - September 30, 2022 Volumetric and Mid-Section Discharge Measurement data, Summer through Fall 2020, H.J. Andrews Experimental Forest, Lookout Creek Basin, Oregon Hydrologic Monitoring of Glacier-Influenced Watersheds (Hulahula Gage) Hydrologic event-based water-quality and streamflow data for three oxbow tributaries in northwestern Mississippi, 2007-2016 Stable isotopic ratios of hydrogen and oxygen in groundwater and calculated fraction of recharge from winter precipitation, South Rim Grand Canyon, Arizona Streamflow monitoring on the Canning and Tamayariak rivers. Streamflow Monitoring on Upper Kuparuk and Putuligayuk Rivers (2010) Model archive for analysis of the effects of impervious cover on receiving-water quality with the Stochastic Empirical Loading Dilution Model (SELDM) Groundwater-level altitude and groundwater-level change maps developed for the groundwater component of the upper Rio Grande Focus Area Study Imiq - Hydroclimate Database and Data Portal Imiq Data Portal Stochastic Empirical Loading and Dilution Model (SELDM) software archive Monthly Water Balance Model Futures Highway-Runoff Database (HRDB) Version 1.1.0 Statistics for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM) Best Management Practices Statistical Estimator (BMPSE) Version 1.2.0