Baseflow estimation and trend and correlation analysis results for East Canyon Creek, Summit and Morgan Counties, Utah
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East Canyon Creek is a perennial snowmelt-dominated stream that lies in the Snyderville Basin of Summit and Morgan Counties, Utah. Its headwaters begin as McLeod Creek on the eastern slopes of the Wasatch Mountains before joining Kimball Creek to form East Canyon Creek, proper, below the Interstate 80 overpass where it flows north-northwest into East Canyon Reservoir. The reach between the headwaters and East Canyon Reservoir includes three U.S. Geological Survey streamgages that monitor streamflow and specific conductance. The Snyderville Basin Water Reclamation District provides wastewater collection and reclamation services for Park City, Utah, and the surrounding areas and operates a water reclamation facility on East Canyon Creek near Jeremy Ranch. This data release includes daily, monthly, and annual streamflow and estimated baseflow data from three streamgages (10133650, 10133800, 10133980), monthly and annual climatological data from two snow telemetry stations (684, 814), and results of monthly and annual trend and correlation analyses between the 2011 and 2022 water years.
Geographic Data for the Estimation of Peak Flow Statistics for Illinois
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The U.S. Geological Survey Central Midwest Water Science Center completed a report (Over and others, 2023) documenting methods, results, and applications of an updated flood-frequency study for the State of Illinois. The study developed regional regression equations that relate the peak-flow quantiles and the basin characteristics of selected streamgages in Illinois, Indiana, and Wisconsin, based on data through water year 2017 (a water year is the period from October 1 to September 30 and is designated by the year in which it ends; for example, water year 2017 was from October 1, 2016, to September 30, 2017). The data provided through this data release are those digital datasets of basin characteristics that have been collected, tested, and ultimately selected for use in regional regression equations. These datasets consist of raster grid files for slope (slope100.zip), calculated from a published digital elevation model (DEM) (Schafer and Sharpe, 2023), soil slope (stats_slope100.zip) subsetted and resampled from Wolock (1997), a soil texture permeability index (texp_indx_rnd.zip) computed using data from Wolock (1997), land cover (nlcd16_22_23_24.zip) adapted from Yang and others (2018), a basin soil wetness measure (drclass1a.zip) computed from U.S. Department of Agriculture (USDA) (2013), and an urbanization fraction (urbthe2010.zip) computed from Theobald 2010 data (Theobald, 2005). Some basin characteristics are not included in this data release as they are easily derived from StreamStats basin delineations themselves, such as basin drainage area. The U.S. Geological Survey (USGS), in cooperation with the Illinois Center for Transportation (ICT) and the Illinois Department of Transportation (IDOT), prepared these digital datasets of basin characteristics for use in the Illinois StreamStats application (https://streamstats.usgs.gov/ss/). Two additional shapefiles are provided: a shapefile of the streamgages (IL_StreamStats_Gages.zip) and a shapefile of the associated delineated streamgage drainage basins (IL_StreamStats_DrainageBasins.zip) used in analysis (Over and others, 2023).
Geographic Data for the Estimation of Peak Flow Statistics for Illinois
공공데이터포털
The U.S. Geological Survey Central Midwest Water Science Center completed a report (Over and others, 2023) documenting methods, results, and applications of an updated flood-frequency study for the State of Illinois. The study developed regional regression equations that relate the peak-flow quantiles and the basin characteristics of selected streamgages in Illinois, Indiana, and Wisconsin, based on data through water year 2017 (a water year is the period from October 1 to September 30 and is designated by the year in which it ends; for example, water year 2017 was from October 1, 2016, to September 30, 2017). The data provided through this data release are those digital datasets of basin characteristics that have been collected, tested, and ultimately selected for use in regional regression equations. These datasets consist of raster grid files for slope (slope100.zip), calculated from a published digital elevation model (DEM) (Schafer and Sharpe, 2023), soil slope (stats_slope100.zip) subsetted and resampled from Wolock (1997), a soil texture permeability index (texp_indx_rnd.zip) computed using data from Wolock (1997), land cover (nlcd16_22_23_24.zip) adapted from Yang and others (2018), a basin soil wetness measure (drclass1a.zip) computed from U.S. Department of Agriculture (USDA) (2013), and an urbanization fraction (urbthe2010.zip) computed from Theobald 2010 data (Theobald, 2005). Some basin characteristics are not included in this data release as they are easily derived from StreamStats basin delineations themselves, such as basin drainage area. The U.S. Geological Survey (USGS), in cooperation with the Illinois Center for Transportation (ICT) and the Illinois Department of Transportation (IDOT), prepared these digital datasets of basin characteristics for use in the Illinois StreamStats application (https://streamstats.usgs.gov/ss/). Two additional shapefiles are provided: a shapefile of the streamgages (IL_StreamStats_Gages.zip) and a shapefile of the associated delineated streamgage drainage basins (IL_StreamStats_DrainageBasins.zip) used in analysis (Over and others, 2023).
Water-quality trends for rivers and streams in the Delaware River Basin using Weighted Regressions on Time, Discharge, and Season (WRTDS) models, Seasonal Kendall Trend (SKT) tests, and multisource data, Water Year 1978-2018.
공공데이터포털
This data release provides water-quality trends for rivers and streams in the Delaware River Basin determined using the Weighted Regressions on Time, Discharge, and Season (WRTDS) model and the Seasonal Kendall Trend (SKT) test. Sixteen water-quality parameters were assessed, including nutrients (ammonia, nitrate, filtered orthophosphate, total nitrogen, total phosphorus, and unfiltered orthophosphate), major ions (calcium, chloride, magnesium, potassium, sodium, and sulfate), salinity indicators (total dissolved solids and specific conductance), and sediment (total suspended solids and suspended sediment concentration). The child items include the input and output data used in the modeling and testing of water-quality trends. The attached files include the scripts used in these analyses, a readMe files for these scripts and tables summarizing information about the sites used in the analysis. These trends build off the national efforts of Oelsner and others (2017) and Murphy and others (2018), with some variations in data screening and processing. One major divergence from these previous efforts was that screened site-parameter combinations were screened for the longest period of record that passed various temporal and seasonal criteria ("maximum calibration" approach) instead of screening by pre-defined trend periods. An additional difference was that water-quality data were combined from multiple monitoring locations and collecting organizations using hierarchical clustering based on the distance between monitoring locations on the same stream reach (as determined by the National Hydrography Dataset comid). Data that were a part of these "cluster sites" were manually reviewed prior to running SKT and WRTDS. Input data for SKT includes 124 sites (including individual sites and cluster sites) and 1,208 site-parameter combinations. Input data for WRTDS, which required additional screening beyond those used for the SKT test and a paired streamflow gage, includes 62 sites and 476 site-parameter combinations. For both methods, some site-parameter combinations were not run due to the amount of censored data, or the results were rejected due to poor model fit. Trends are reported for four trend periods (1978-2018, 1998-2018, 2003-2018, and 2008-2018), as the available screened data allow, and for the entire screened period of record for each parameter at each site. This collection of trend results leverages the monitoring efforts of many collecting organizations across the Delaware River Basin and can serve to better understand changing water-quality conditions across this basin. References Cited: Murphy, J.C., Farmer, W.H., Sprague, L.A., De Cicco, L.A., and Hirsch, R.M., 2018, Water-quality trends and trend component estimates for the Nation's rivers and streams using Weighted Regressions on Time, Discharge, and Season (WRTDS) models and generalized flow normalization, 1972-2012: U.S. Geological Survey data release, https://doi.org/10.5066/F7TQ5ZS3. Oelsner, G.P., Sprague, L.A., Murphy, J.C., Zuellig, R.E., Johnson, H.M., Ryberg, K.R., Falcone, J.A., Stets, E.G., Vecchia, A.V., Riskin, M.L., De Cicco, L.A., Mills, T.J., Farmer, W.H., 2017, Water-quality trends in the Nation’s rivers and streams 1972–2012—Data preparation, statistical methods, and trend results: U.S. Geological Survey Scientific Investigations Report, http://dx.doi.org/10.3133/sir20175006. Shoda, M.E., Murphy, J.C., Falcone, J.A., and Duris, J.W., 2019, Multisource surface-water-quality data and U.S. Geological Survey streamgage match for the Delaware River Basin: U.S. Geological Survey data release, https://doi.org/10.5066/P9PX8LZO. National Water Quality Monitoring Council, Water Quality Portal (WQP), https://www.waterqualitydata.us/. Accessed 2020-11-03.
Water-quality trends for rivers and streams in the Delaware River Basin using Weighted Regressions on Time, Discharge, and Season (WRTDS) models, Seasonal Kendall Trend (SKT) tests, and multisource data, Water Year 1978-2018.
공공데이터포털
This data release provides water-quality trends for rivers and streams in the Delaware River Basin determined using the Weighted Regressions on Time, Discharge, and Season (WRTDS) model and the Seasonal Kendall Trend (SKT) test. Sixteen water-quality parameters were assessed, including nutrients (ammonia, nitrate, filtered orthophosphate, total nitrogen, total phosphorus, and unfiltered orthophosphate), major ions (calcium, chloride, magnesium, potassium, sodium, and sulfate), salinity indicators (total dissolved solids and specific conductance), and sediment (total suspended solids and suspended sediment concentration). The child items include the input and output data used in the modeling and testing of water-quality trends. The attached files include the scripts used in these analyses, a readMe files for these scripts and tables summarizing information about the sites used in the analysis. These trends build off the national efforts of Oelsner and others (2017) and Murphy and others (2018), with some variations in data screening and processing. One major divergence from these previous efforts was that screened site-parameter combinations were screened for the longest period of record that passed various temporal and seasonal criteria ("maximum calibration" approach) instead of screening by pre-defined trend periods. An additional difference was that water-quality data were combined from multiple monitoring locations and collecting organizations using hierarchical clustering based on the distance between monitoring locations on the same stream reach (as determined by the National Hydrography Dataset comid). Data that were a part of these "cluster sites" were manually reviewed prior to running SKT and WRTDS. Input data for SKT includes 124 sites (including individual sites and cluster sites) and 1,208 site-parameter combinations. Input data for WRTDS, which required additional screening beyond those used for the SKT test and a paired streamflow gage, includes 62 sites and 476 site-parameter combinations. For both methods, some site-parameter combinations were not run due to the amount of censored data, or the results were rejected due to poor model fit. Trends are reported for four trend periods (1978-2018, 1998-2018, 2003-2018, and 2008-2018), as the available screened data allow, and for the entire screened period of record for each parameter at each site. This collection of trend results leverages the monitoring efforts of many collecting organizations across the Delaware River Basin and can serve to better understand changing water-quality conditions across this basin. References Cited: Murphy, J.C., Farmer, W.H., Sprague, L.A., De Cicco, L.A., and Hirsch, R.M., 2018, Water-quality trends and trend component estimates for the Nation's rivers and streams using Weighted Regressions on Time, Discharge, and Season (WRTDS) models and generalized flow normalization, 1972-2012: U.S. Geological Survey data release, https://doi.org/10.5066/F7TQ5ZS3. Oelsner, G.P., Sprague, L.A., Murphy, J.C., Zuellig, R.E., Johnson, H.M., Ryberg, K.R., Falcone, J.A., Stets, E.G., Vecchia, A.V., Riskin, M.L., De Cicco, L.A., Mills, T.J., Farmer, W.H., 2017, Water-quality trends in the Nation’s rivers and streams 1972–2012—Data preparation, statistical methods, and trend results: U.S. Geological Survey Scientific Investigations Report, http://dx.doi.org/10.3133/sir20175006. Shoda, M.E., Murphy, J.C., Falcone, J.A., and Duris, J.W., 2019, Multisource surface-water-quality data and U.S. Geological Survey streamgage match for the Delaware River Basin: U.S. Geological Survey data release, https://doi.org/10.5066/P9PX8LZO. National Water Quality Monitoring Council, Water Quality Portal (WQP), https://www.waterqualitydata.us/. Accessed 2020-11-03.
Elevation, Flow Accumulation, Flow Direction, and Stream Definition Data in Support of the Illinois StreamStats Upgrade to the Basin Delineation Database
공공데이터포털
The U.S. Geological Survey (USGS), in cooperation with the Illinois Center for Transportation and the Illinois Department of Transportation, prepared hydro-conditioned geographic information systems (GIS) layers for use in the Illinois StreamStats application. These data were used to delineate drainage basins and compute basin characteristics for updated peak flow and flow duration regression equations for Illinois. This dataset consists of raster grid files for elevation (dem), flow accumulation (fac), flow direction (fdr), and stream definition (str900) for each 8-digit Hydrologic Unit Code (HUC) area in Illinois merged into a single dataset. There are 51 full or partial HUC 8s represented by this data set: 04040002, 05120108, 05120109, 05120111, 05120112, 05120113, 05120114, 05120115, 05140202, 05140203, 05140204, 05140206, 07060005, 07080101, 07080104, 07090001, 07090002, 07090003, 07090004, 07090005, 07090006, 07090007, 07110001, 07110004, 07110009, 07120001, 07120002, 07120004 (0712003 was combined into this HUC), 07120005, 07120006, 07120007, 07130001, 07130002, 07130003, 07130004, 07130005, 07130006, 07130007, 07130008, 07130009, 07130010, 07130011, 07130012, 07140101, 07140105, 07140106, 07140108, 07140201, 07140202, 07140203, and 07140204.