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Low flow water quality data for the Animas River, Arrastra Creek to Silverton, Colorado, September 2021
A synoptic sampling campaign was conducted on the Animas River near Silverton, Colorado, under low flow conditions in September 2021. The sampling campaign was designed to quantify constituent loading and identify sources of contamination along a 3.8-kilometer study reach. The study reach began approximately 170 meters upstream of Arrastra Creek and extended downstream to U.S. Geological Survey (USGS) gage 09358000 within the city of Silverton, Colorado. A continuous, instream injection of a sodium bromide tracer was initiated at the head of the study reach three days prior to the start of the sampling campaign and maintained until the completion of main stem sampling. Bromide concentrations were subsequently used to determine streamflow using the tracer-dilution method. Water quality samples were collected at 23 sites along the Animas River main stem, and 28 inflow sites including springs, seeps, small tributaries, and ponded water. Main stem sites were sampled using three sampling approaches. Under the first approach, a subset of 8 main stem sites were sampled "simultaneously" (in less than 20 minutes) to assess the effects of diel variation in constituent concentration. Under the second approach, all main stem sites were sampled with the sampling team working in the downstream-to-upstream direction, a protocol typically used during synoptic sampling. A subset of 5 main stem sites were also sampled using an Equal Discharge Increment approach that was designed to indicate which side of the stream was responsible for the observed constituent loads. This data release includes field parameters (water temperature, pH, and specific conductivity), concentration data (inorganic cations and anions), estimated streamflow, and calculated loads for the sampling campaign. Calculated loads may be used to identify and rank sources of contamination to the Animas River. The data release consists of a kmz file showing site locations and the following 3 tables: Table 1, Locations of sampling sites Table 2, Synoptic sampling results, September 20-21, 2021 Table 3, Spatial profiles of streamflow and constituent load
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Low flow water quality data for the Animas River, Arrastra Creek to Silverton, Colorado, September 2021
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A synoptic sampling campaign was conducted on the Animas River near Silverton, Colorado, under low flow conditions in September 2021. The sampling campaign was designed to quantify constituent loading and identify sources of contamination along a 3.8-kilometer study reach. The study reach began approximately 170 meters upstream of Arrastra Creek and extended downstream to U.S. Geological Survey (USGS) gage 09358000 within the city of Silverton, Colorado. A continuous, instream injection of a sodium bromide tracer was initiated at the head of the study reach three days prior to the start of the sampling campaign and maintained until the completion of main stem sampling. Bromide concentrations were subsequently used to determine streamflow using the tracer-dilution method. Water quality samples were collected at 23 sites along the Animas River main stem, and 28 inflow sites including springs, seeps, small tributaries, and ponded water. Main stem sites were sampled using three sampling approaches. Under the first approach, a subset of 8 main stem sites were sampled "simultaneously" (in less than 20 minutes) to assess the effects of diel variation in constituent concentration. Under the second approach, all main stem sites were sampled with the sampling team working in the downstream-to-upstream direction, a protocol typically used during synoptic sampling. A subset of 5 main stem sites were also sampled using an Equal Discharge Increment approach that was designed to indicate which side of the stream was responsible for the observed constituent loads. This data release includes field parameters (water temperature, pH, and specific conductivity), concentration data (inorganic cations and anions), estimated streamflow, and calculated loads for the sampling campaign. Calculated loads may be used to identify and rank sources of contamination to the Animas River. The data release consists of a kmz file showing site locations and the following 3 tables: Table 1, Locations of sampling sites Table 2, Synoptic sampling results, September 20-21, 2021 Table 3, Spatial profiles of streamflow and constituent load
Compilation of water-quality data, discharge data, and geochemical equilibrium models for streams, draining mine adits, and springs in the Upper Animas River Watershed, Colorado, 1987–2020
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Acid mine drainage (AMD) can cause ecological harm throughout the state of Colorado, including in the Upper Animas River watershed near Silverton. In the Upper Animas River watershed, a technique that includes the emplacement of hydraulic bulkheads within draining mines has been used to remediate AMD. Data for major ions and trace metal concentrations, isotopic compositions, and discharge from streams, draining mines, and springs were compiled for a period of approximately 30 years to better understand the processes occurring during the impoundment of water within underground mine workings and to define spatial extent of groundwater connectivity. These datasets were evaluated using statistical and geochemical modeling approaches.
Compilation of water-quality data, discharge data, and geochemical equilibrium models for streams, draining mine adits, and springs in the Upper Animas River Watershed, Colorado, 1987–2020
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Acid mine drainage (AMD) can cause ecological harm throughout the state of Colorado, including in the Upper Animas River watershed near Silverton. In the Upper Animas River watershed, a technique that includes the emplacement of hydraulic bulkheads within draining mines has been used to remediate AMD. Data for major ions and trace metal concentrations, isotopic compositions, and discharge from streams, draining mines, and springs were compiled for a period of approximately 30 years to better understand the processes occurring during the impoundment of water within underground mine workings and to define spatial extent of groundwater connectivity. These datasets were evaluated using statistical and geochemical modeling approaches.
Calibration datasets and model archive summaries for regression models developed to estimate metal concentrations at nine sites on the Animas and San Juan Rivers, Colorado, New Mexico, and Utah: U.S. Geological Survey data release, https://doi.org/10.5066/P9THSFE0
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This data release supports the following publication: Mast, M. A., 2018, Estimating metal concentrations with regression analysis and water-quality surrogates at nine sites on the Animas and San Juan Rivers, Colorado, New Mexico, and Utah: U.S. Geological Survey Scientific Investigations Report 2018-5116. The U.S. Geological Survey (USGS), in cooperation with the U. S. Environmental Protection Agency (EPA), developed site-specific regression models to estimate concentrations of selected metals at nine USGS streamflow-gaging stations along the Animas and San Juan Rivers. Multiple linear-regression models were developed by relating metal concentrations in discrete water-quality samples to continuously monitored streamflow and surrogate parameters including specific conductance, pH, turbidity, and water temperature. Models were developed for dissolved and total concentrations of aluminum, arsenic, cadmium, iron, lead, manganese, and zinc using water-quality samples collected during 2005–17 by several agencies, using different collection methods and analytical laboratories. Calibration datasets in comma-separated format (CSV) include the variables of sampling date and time, metal concentrations (in micrograms per liter), stream discharge (in cubic feet per second), specific conductance (in microsiemens per centimeter at 25 degrees Celsius), pH, water temperature (in degrees Celsius), turbidity (in nephelometric turbidity units), and calculated seasonal terms based on Julian day. Surrogate parameters and discrete water-quality samples were used from nine sites including Cement Creek at Silverton, Colo. (USGS station 09358550); Animas River below Silverton, Colo. (USGS station 09359020); Animas River at Durango, Colo. (USGS station 09361500); Animas River Near Cedar Hill, N. Mex. (USGS station 09363500); Animas River below Aztec, N. Mex. (USGS station 09364010); San Juan River at Farmington, N. Mex. (USGS station 09365000); San Juan River at Shiprock, N. Mex (USGS Station 09368000); San Juan River at Four Corners, Colo. (USGS station 09371010); and San Juan River near Bluff, Utah (USGS station 09379500). Model archive summaries in pdf format include model statistics, data, and plots and were generated using a R script developed by USGS Kansas Water Science Center available at https://patrickeslick.github.io/ModelArchiveSummary/. A description of each USGS streamflow gaging station along with information about the calibration datasets also are provided.
Calibration datasets and model archive summaries for regression models developed to estimate metal concentrations at nine sites on the Animas and San Juan Rivers, Colorado, New Mexico, and Utah: U.S. Geological Survey data release, https://doi.org/10.5066/P9THSFE0
공공데이터포털
This data release supports the following publication: Mast, M. A., 2018, Estimating metal concentrations with regression analysis and water-quality surrogates at nine sites on the Animas and San Juan Rivers, Colorado, New Mexico, and Utah: U.S. Geological Survey Scientific Investigations Report 2018-5116. The U.S. Geological Survey (USGS), in cooperation with the U. S. Environmental Protection Agency (EPA), developed site-specific regression models to estimate concentrations of selected metals at nine USGS streamflow-gaging stations along the Animas and San Juan Rivers. Multiple linear-regression models were developed by relating metal concentrations in discrete water-quality samples to continuously monitored streamflow and surrogate parameters including specific conductance, pH, turbidity, and water temperature. Models were developed for dissolved and total concentrations of aluminum, arsenic, cadmium, iron, lead, manganese, and zinc using water-quality samples collected during 2005–17 by several agencies, using different collection methods and analytical laboratories. Calibration datasets in comma-separated format (CSV) include the variables of sampling date and time, metal concentrations (in micrograms per liter), stream discharge (in cubic feet per second), specific conductance (in microsiemens per centimeter at 25 degrees Celsius), pH, water temperature (in degrees Celsius), turbidity (in nephelometric turbidity units), and calculated seasonal terms based on Julian day. Surrogate parameters and discrete water-quality samples were used from nine sites including Cement Creek at Silverton, Colo. (USGS station 09358550); Animas River below Silverton, Colo. (USGS station 09359020); Animas River at Durango, Colo. (USGS station 09361500); Animas River Near Cedar Hill, N. Mex. (USGS station 09363500); Animas River below Aztec, N. Mex. (USGS station 09364010); San Juan River at Farmington, N. Mex. (USGS station 09365000); San Juan River at Shiprock, N. Mex (USGS Station 09368000); San Juan River at Four Corners, Colo. (USGS station 09371010); and San Juan River near Bluff, Utah (USGS station 09379500). Model archive summaries in pdf format include model statistics, data, and plots and were generated using a R script developed by USGS Kansas Water Science Center available at https://patrickeslick.github.io/ModelArchiveSummary/. A description of each USGS streamflow gaging station along with information about the calibration datasets also are provided.
Select elements of concern in surface water of three hydrologic basins (Delaware River, Illinois River and Upper Colorado River) - Data screening for the development of spatial and temporal models
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This data release is focused on the analysis of surface water concentration data associated with 12 elements of concern from three hydrologic basins. Data is analyzed with respect to: a) reporting limits, b) the extent of censored data, c) co-location with USGS real-time sensor data, and d) median concentrations at the catchment spatial scale. The Proxies Project (under the Water Quality Program of the USGS Water Mission Area) is a multi-year effort designed to develop rapid and cost-effective approaches for monitoring and risk assessment of a range of aquatic contaminants in riverine surface waters at multiple spatial scales. One component of this project is focused on 12 Elements of Concern (EoC; Al, As, Cd, Cr, Cu, Fe, Hg, Mn, Pb, Se, U and Zn) in three primary hydrologic basins: Delaware River Basin (DRB), the Illinois River Basin (ILRB) and the Upper Colorado (UCOL) River Basin (USGS, 2023). Two modeling approaches being explored as part of the Proxies Project rely on the analysis of previously published EoC concentration data retrieved from the multi-agency supported Water Quality Portal (www.waterqualitydata.us/). This basin-specific retrieved data, covering the 1900-2022 timeframe, was subsequently screened, harmonized and published as part of an earlier USGS Data Release (Marvin-DiPasquale and others, 2022). The two distinct modeling approaches that leverage this previously published data are: a) machine learning statistical analysis of EoC concentration distributions as a function of geospatial attributes; and b) time series analysis in support of estimating EoC concentrations in (near)real-time at a sub-set of USGS real-time stations using discharge in combination with a range of deployed in-situ sensors. Prior to the final stages of model development, there were several data analysis steps required to further define which elements and aquatic fractions (i.e. filtered, unfiltered, and particulate) best lend themselves to further model exploration and development. These intermediate data analyses include: a) an analysis of the change in detection quantitation limits, by element and methods over time (DR_Table _1); b) an analysis of data censoring, by study basin, element, and fraction (DR_Table_2); c) a calculation of median EoC concentrations at the National Hydrography Dataset Plus (NHDPlus) catchment spatial scale (DR_Table_3); d) an analysis of the percentage of censored median EoC concentration values by study basin, element, and fraction (DR_Table_4); e) decision tree analysis associated with the geospatial machine learning modeling approach, by study basin, element and fraction (DR_Table_5); f) discrete EoC concentration data merged with continuous discharge and in-situ sensor data at USGS real-time stations, by station ID, element and fraction (DR_Table_6); and g) an analysis of the total number of observations and the percentage of censored EoC data associated with the merged discrete EoC and continuous discharge and sensor data retrieved from USGS real-time stations, by station ID, element, and fraction (DR_Table_7). The current data release documents the results of these data analyses. The associated seven data tables presented herein are provided in machine-readable comma separated value (*.csv) format and are more fully described in the associated meta-data. REFERENCES Marvin-DiPasquale, M.C., Sullivan, S.L., Platt, L. R., Gorsky, A., Agee, J.L., McCleskey, B.R., Kakouros, E., Walton-Day, K., Runkel, R. L., Morriss, M. C., Wakefield, B. F., and Bergamaschi, B., 2022, Concentration Data for 12 Elements of Concern Used in the Development of Surrogate Models for Estimating Elemental Concentrations in Surface Water of Three Hydrologic Basins (Delaware River, Illinois River and Upper Colorado River): U.S. Geological Survey data release, https://doi.org/10.5066/P9L06M3G. USGS, 2023, Proxies Project, U.S. Geological Survey webpage, accessed 3/11/2025,
Water-quality and discharge data from draining mine tunnels near Silverton, Colorado 1988-2015
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The American Tunnel, the Black Hawk mine, the Gold King mine, the Mogul mine, and the Red and Bonita mine are located in the Cement Creek watershed, tributary to the upper Animas River near Silverton, Colorado. All five sites have tunnels that drain groundwater from abandoned underground mine workings to the surface. This draining water has elevated concentrations of metals and degrades water quality in Cement Creek. Water quality (pH, and dissolved copper, manganese, and zinc concentrations) and discharge data were compiled from multiple sources to examine changes in these parameters through time. Copper, manganese, and zinc loads calculated from these data are included in the data files. Data are reported for the American Tunnel (November 1988 through July 2015), the Black Hawk mine (September 1991 through September 2005), the Gold King mine (August 1993 through July 2015), the Mogul mine (July 1992 through July 2015), and the Red and Bonita mine (June 1997 through July 2015).
Water-quality and discharge data from draining mine tunnels near Silverton, Colorado 1988-2015
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The American Tunnel, the Black Hawk mine, the Gold King mine, the Mogul mine, and the Red and Bonita mine are located in the Cement Creek watershed, tributary to the upper Animas River near Silverton, Colorado. All five sites have tunnels that drain groundwater from abandoned underground mine workings to the surface. This draining water has elevated concentrations of metals and degrades water quality in Cement Creek. Water quality (pH, and dissolved copper, manganese, and zinc concentrations) and discharge data were compiled from multiple sources to examine changes in these parameters through time. Copper, manganese, and zinc loads calculated from these data are included in the data files. Data are reported for the American Tunnel (November 1988 through July 2015), the Black Hawk mine (September 1991 through September 2005), the Gold King mine (August 1993 through July 2015), the Mogul mine (July 1992 through July 2015), and the Red and Bonita mine (June 1997 through July 2015).
Shenandoah National Park 1979-2022 Water Quality Data from Seven Projects as of 2025-03-28
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This data package was created 2025-03-28 21:29:09 by NPSTORET and includes selected project, location, and result data. Data contained in the Shenandoah National Park (University of Virginia) NPSTORET back-end file (NPS_UVA_NPSTORET_BE_20240122_20240126_0856_20240129_1345.ACCDB) were filtered to include just the data within the park for the following seven projects: Project: - SHEN_UVA_CHANG_1994: Lisa Chang’s Pre-Ph.D. Dissertation Research Data from Shaver Hollow - SHEN_UVA_FISH_IN_SENSITIVE_HABITATS: Fish in Sensitive Habitats - SHEN_UVA_HEADWATER_STUDY_2007: Characterize Threatened and Impaired Headwater Streams and Springs in Shenandoah National Park - SHEN_UVA_HG_BROOK_TROUT_2004: Effects of Stream Water Chemistry on Mercury Concentrations in Brook Trout in Shenandoah National Park - SHEN_UVA_MISC: Miscellaneous data - SHEN_UVA_PRIMARY: University of Virginia's Primary SWAS-VTSSS Program Database - SHEN_UVA_STAN_1995_FLOOD: Understanding the 1995 Staunton River Flood Event in Shenandoah National Park Station: - Include Trip QC And All Station Visit Results Park/Unit Code: - SHEN Activity Start Date (>=1/1/1979 and <=12/31/2022) Value Status: - Accepted or Certified (exported as Final) or Final The data package is organized into five data tables: - Projects.csv - describes the purpose and background of the monitoring efforts - Locations.csv - documents the attributes of the monitoring locations/stations - Results.csv - contains the field measurements, observations, and/or lab analyses for each sample/event/data grouping - HUC.csv - enumerates the domain of allowed values for 8-digit and 12-digit hydrologic unit codes utilized by the Locations data table - Characteristics.csv - enumerates the domain of characteristics available in NPSTORET to identify what was sampled, measured or observed in Results Period of record for filtered data is 1979-11-02 to 2022-12-28. This data package is a snapshot in time of multiple National Park Service projects. The most current data for these projects, which may be more or less extensive than that in this data package, can be found on the Water Quality Portal at: https://www.waterqualitydata.us/data/Result/search?project=SHEN_UVA_CHANG_1994&mimeType=csv&zip=yes&dataProfile=biological&providers=STORET https://www.waterqualitydata.us/data/Result/search?project=SHEN_UVA_FISH_IN_SENSITIVE_HABITATS&mimeType=csv&zip=yes&dataProfile=biological&providers=STORET https://www.waterqualitydata.us/data/Result/search?project=SHEN_UVA_HEADWATER_STUDY_2007&mimeType=csv&zip=yes&dataProfile=biological&providers=STORET https://www.waterqualitydata.us/data/Result/search?project=SHEN_UVA_HG_BROOK_TROUT_2004&mimeType=csv&zip=yes&dataProfile=biological&providers=STORET https://www.waterqualitydata.us/data/Result/search?project=SHEN_UVA_MISC&mimeType=csv&zip=yes&dataProfile=biological&providers=STORET https://www.waterqualitydata.us/data/Result/search?project=SHEN_UVA_PRIMARY&mimeType=csv&zip=yes&dataProfile=biological&providers=STORET https://www.waterqualitydata.us/data/Result/search?project=SHEN_UVA_STAN_1995_FLOOD&mimeType=csv&zip=yes&dataProfile=biological&providers=STORET
Shenandoah National Park 1979-2022 Water Quality Data from Seven Projects as of 2025-03-28
공공데이터포털
This data package was created 2025-03-28 21:29:09 by NPSTORET and includes selected project, location, and result data. Data contained in the Shenandoah National Park (University of Virginia) NPSTORET back-end file (NPS_UVA_NPSTORET_BE_20240122_20240126_0856_20240129_1345.ACCDB) were filtered to include just the data within the park for the following seven projects: Project: - SHEN_UVA_CHANG_1994: Lisa Chang’s Pre-Ph.D. Dissertation Research Data from Shaver Hollow - SHEN_UVA_FISH_IN_SENSITIVE_HABITATS: Fish in Sensitive Habitats - SHEN_UVA_HEADWATER_STUDY_2007: Characterize Threatened and Impaired Headwater Streams and Springs in Shenandoah National Park - SHEN_UVA_HG_BROOK_TROUT_2004: Effects of Stream Water Chemistry on Mercury Concentrations in Brook Trout in Shenandoah National Park - SHEN_UVA_MISC: Miscellaneous data - SHEN_UVA_PRIMARY: University of Virginia's Primary SWAS-VTSSS Program Database - SHEN_UVA_STAN_1995_FLOOD: Understanding the 1995 Staunton River Flood Event in Shenandoah National Park Station: - Include Trip QC And All Station Visit Results Park/Unit Code: - SHEN Activity Start Date (>=1/1/1979 and <=12/31/2022) Value Status: - Accepted or Certified (exported as Final) or Final The data package is organized into five data tables: - Projects.csv - describes the purpose and background of the monitoring efforts - Locations.csv - documents the attributes of the monitoring locations/stations - Results.csv - contains the field measurements, observations, and/or lab analyses for each sample/event/data grouping - HUC.csv - enumerates the domain of allowed values for 8-digit and 12-digit hydrologic unit codes utilized by the Locations data table - Characteristics.csv - enumerates the domain of characteristics available in NPSTORET to identify what was sampled, measured or observed in Results Period of record for filtered data is 1979-11-02 to 2022-12-28. This data package is a snapshot in time of multiple National Park Service projects. The most current data for these projects, which may be more or less extensive than that in this data package, can be found on the Water Quality Portal at: https://www.waterqualitydata.us/data/Result/search?project=SHEN_UVA_CHANG_1994&mimeType=csv&zip=yes&dataProfile=biological&providers=STORET https://www.waterqualitydata.us/data/Result/search?project=SHEN_UVA_FISH_IN_SENSITIVE_HABITATS&mimeType=csv&zip=yes&dataProfile=biological&providers=STORET https://www.waterqualitydata.us/data/Result/search?project=SHEN_UVA_HEADWATER_STUDY_2007&mimeType=csv&zip=yes&dataProfile=biological&providers=STORET https://www.waterqualitydata.us/data/Result/search?project=SHEN_UVA_HG_BROOK_TROUT_2004&mimeType=csv&zip=yes&dataProfile=biological&providers=STORET https://www.waterqualitydata.us/data/Result/search?project=SHEN_UVA_MISC&mimeType=csv&zip=yes&dataProfile=biological&providers=STORET https://www.waterqualitydata.us/data/Result/search?project=SHEN_UVA_PRIMARY&mimeType=csv&zip=yes&dataProfile=biological&providers=STORET https://www.waterqualitydata.us/data/Result/search?project=SHEN_UVA_STAN_1995_FLOOD&mimeType=csv&zip=yes&dataProfile=biological&providers=STORET