Michael G. Rupert L. Niel Plummer 2009 raster digital data U.S. Geological Survey Data Series USGS DS 460 Denver, CO U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?sir095082_mix This raster data set delineates the predicted probability of unmixed young groundwater (defined using chlorofluorocarbon-11 concentrations and tritium activities) in groundwater in the Eagle River watershed valley-fill aquifer, Eagle County, North-Central Colorado, 2006-2007. This data set was developed by a cooperative project between the U.S. Geological Survey, Eagle County, the Eagle River Water and Sanitation District, the Town of Eagle, the Town of Gypsum, and the Upper Eagle Regional Water Authority. This project was designed to evaluate potential land-development effects on groundwater and surface-water resources so that informed land-use and water management decisions can be made. This groundwater probability map and its associated probability maps were developed as follows: (1) A point data set of wells with groundwater quality and groundwater age data was overlaid with thematic layers of anthropogenic (related to human activities) and hydrogeologic data by using a geographic information system to assign each well values for depth to groundwater, distance to major streams and canals, distance to gypsum beds, precipitation, soils, and well depth. These data then were downloaded to a statistical software package for analysis by logistic regression. (2) Statistical models predicting the probability of elevated nitrate concentrations, the probability of unmixed young water (using chlorofluorocarbon-11 concentrations and tritium activities), and the probability of elevated volatile organic compound concentrations were developed using logistic regression techniques. (3) The statistical models were entered into a GIS and the probability map was constructed. The purpose of this data set is to delineate the predicted probability of unmixed young groundwater (defined using chlorofluorocarbon-11 concentrations and tritium activities) in the Eagle River watershed valley-fill aquifer, Eagle County, North-Central Colorado, 2006-2007. Please refer to the following publication for a complete description of how this data set was developed: Rupert, M.G., and Plummer, L.N., 2009, Groundwater quality, age, and probability of contamination, Eagle River Watershed Valley-Fill Aquifer, North-Central Colorado, 2006-2007: U.S. Geological Survey Scientific Investigations Report 2009-5082, 59 p ., accessed August 11, 2009, at http://pubs.usgs.gov/sir/2009/5082/. Two additional raster data sets are associated with this data set (sir095082_nit and sir095082_voc). One predicts the probability of elevated nitrate concentrations in groundwater, and the other predicts the probability of elevated volatile organic compound (VOC) concentrations in groundwater. The statistical models used to create all three raster data sets used different compounds such as nitrate and VOCs to provide an indication of the probability of groundwater contamination under a variety of conditions and contaminant inputs. REFERENCES: Gurdak, J.J., and Qi, S.L., 2006, Vulnerability of recently recharged ground water in the High Plains regional aquifer to nitrate contamination: U.S. Geological Survey Scientific Investigations Report 2006-5050, 39 p., accessed July 21, 2009, at http://pubs.usgs.gov/sir/2006/5050/ Lorenz, D.L., Goldstein, R.M., Cowdery, T.K., and Stoner, J.D., 2003, Comparison of two methods for delineating land use near monitoring wells used for assessing quality of shallow ground water: U.S. Geological Survey Water-Resources Investigations Report 2003-4067, 13 p., accessed December 2005 at http://pubs.usgs.gov/wri/wri03-4067/ Rupert, M.G., 2003, Probability of detecting atrazine/desethyl-atrazine and elevated concentrations of nitrate in ground water in Colorado: U.S. Geological Survey Water-Resources Investigations Report 2002-4269, 35 p., accessed June 17, 2009, at http://pubs.usgs.gov/wri/wri02-4269/. 2006-2007 publication date Complete None planned -107.115478 -106.275619 39.717430 39.545350 None probability of groundwater contamination vulnerability susceptibility ground water groundwater contamination probability groundwater age nitrate logistic regression volatile organic compound VOC chlorofluorocarbon CFC inlandWaters None Eagle County, CO Vail, CO Gypsum, CO Eagle, CO Dotsero, CO Eagle River Brush Creek Gypsum Creek Eagle River Watershed Colorado Wolcott, CO Edwards, CO Minturn, CO None 2006-2007 None This probability map represents the probability of the occurrence of unmixed young groundwater in the Eagle River watershed valley-fill. Probability is a statistical measure of how likely an event will occur. Probability is not the same as certainty. Although the probability maps show predictions as a percent probability, there is inherent uncertainty within these predictions that is not shown in the probability map. This probability map is intended to be a first approximation at developing a consistent rating method for the entire study area and may have several limitations for use at the site or field scale. The model and map does not account for features and processes that may promote focused recharge, preferential groundwater flow, or bypass mechanisms. Additional site-specific data are needed before site-specific decisions are made. The Eagle River watershed is rapidly being developed. As development activities continue, some variables such as surficial soils and irrigation networks may be altered through construction activities, which may have unpredictable effects on the groundwater probability ratings. This probability map should not be used at a scale any larger than 1:24,000, which is the scale of the SSURGO soils data. Probably the most appropriate scale to use this data set is 1:100,000, which would help take into account the combined inaccuracies of the input data sets used to develop this final data set. U.S. Geological Survey Director, Colorado Water Science Center mailing address

Box 25046, MS 415, Denver Federal Center

Lakewood CO 80225 USA (303) 236-4882 (303) 236-4912 GS-W-COden DC@usgs.gov (Warning: Although accurate at the time of production, this contact information may have become obsolete. See the Metadata_Reference_Information section for a current contact.) This data set was developed through a cooperative project with the U.S. Geological Survey, Eagle County, the Eagle River Water and Sanitation District, the Town of Eagle, the Town of Gypsum, and the Upper Eagle Regional Water Authority. None Unclassified None Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 2; ESRI ArcCatalog 9.3.1.1850 U.S. Geological Survey 2009 document Scientific Investigations Report 2009-5082 Denver, Colorado U.S. Geological Survey http://pubs.usgs.gov/sir/2009/5082/ See Entity Attribute information. Not applicable for raster data. The raster data set is complete for the area where all of the input data sets were present within the boundary of the Eagle River watershed alluvial-fill aquifer. Data gaps within the Eagle River watershed alluvial-fill aquifer boundary indicate areas where one or more of the input data sets used to calculate this data set were missing, such as the southernmost portion of Brush Creek and Gypsum Creek. 10 meters Not applicable Day, W.C., Knepper, D.H., Jr., Green, G.N., and Phillips, R.C. 1999 vector digital data Open-File Report 99-427 Denver, CO U.S. Geological Survey http://pubs.usgs.gov/of/1999/ofr-99-0427/ 250000 online 1999 publication date Digital geologic map Used to delineate the Eagle River watershed valley-filll aquifer and the distance to gypsum bedrock U.S. Geological Survey 1999 raster digital data Fact Sheet FS-148-99 Sioux Falls, SC U.S. Geological Survey http://erg.usgs.gov/isb/pubs/factsheets/fs14899.html online 1999 publication date National elevation dataset Used to develop the depth to groundwater map U.S. Geological Survey 2001 raster digital data Fact Sheet FS-088-01 Rolla, MO U.S. Geological Survey http://erg.usgs.gov/isb/pubs/factsheets/fs08801.html 24000 disc 2001 publication date Digital raster graphics Used to delineate the Eagle River watershed valley-fill aquifer U.S. Geological Survey 1999 vector digital data Fact Sheet FS-106-99 Reston, VA U.S. Geological Survey http://erg.usgs.gov/isb/pubs/factsheets/fs10699.html 100000 online 1999 publication date National hydrography dataset Used to delineate distance to surface water Daly, Christopher, Neilson, R.P., and Phillips, D.L. 1994 raster digital data Journal of Applied Meteorology v. 33, p. 140-158 Corvallis, OR Journal of Applied Meteorology Data located at http://www.prism.oregonstate.edu/products/ http://www.prism.oregonstate.edu/pub/prism/docs/jappclim94-modeling_mountain_precip-daly.pdf online 1990 publication date PRISM precipitation data Precipitation data U.S. Department of Agriculture 2008 vector digital data SSURGO soils data CO655 Lakewood, CO U.S. Department of Agriculture http://soildatamart.nrcs.usda.gov/Metadata.aspx?Survey=CO655&UseState=CO 24000 online 2008 publication date SSURGO soils data Fine-scale soils data Schwarz, G.E., and Alexander, R.B., 1995 vector digital data Open-File Report 95-449 Reston, VA U.S. Geological Survey http://water.usgs.gov/lookup/getspatial?ussoils 250000 online 1995 publication date STATSGO soils data Regional soils data U.S. Forest Service, White River National Forest 1999 vector digital data Glenwood Springs, CO U.S. Forest Service http://www.fs.fed.us/r2/whiteriver/projects/gis.shtml 24000 online 1999 publication date White River National Forest soils data Fine-scale soils data OVERVIEW: The groundwater probability maps were developed as follows: (1) A point data set of wells with groundwater quality and groundwater age data was overlaid with thematic layers of anthropogenic and hydrogeologic data by using a geographic information system (GIS) to assign each well values for depth to groundwater, distance to major streams and canals, distance to gypsum beds, precipitation, soils, and well depth. These data then were downloaded to a statistical software package for analysis by logistic regression. (2) Statistical models predicting the probability of elevated nitrate concentrations, the probability of unmixed young water (defined using chlorofluorocarbon-11 concentrations and tritium activities), and the probability of elevated volatile organic compound concentrations were developed using logistic regression techniques. (3) The statistical models were entered into a GIS and the probability maps were constructed. 200601 The boundary of the Eagle River watershed valley-fill aquifer (ERWVFA) was developed by combining information from two data sources. The first data source was a 1:250,000-scale geologic map of the Leadville quadrangle developed by Day and others (1999). The location of Quaternary sediments was used as a first approximation of the ERWVFA. The boundary of the ERWVFA was further refined by overlaying the geologic map with Digital Raster Graphic (DRG) scanned images of 1:24,000 topographic maps (U.S. Geological Survey, 2001). Where appropriate, the boundary of the ERWVFA was remapped to correspond with the abrupt change in topography at the edge of the valley floor throughout the Eagle River watershed. The boundary of the ERWVFA more closely resembles a hydrogeomorphic region presented by Rupert (2003, p. 8) because it is based upon general geographic extents of geologic materials and not on an actual aquifer location as would be determined through a rigorous hydrogeologic investigation. 200712 A depth-to-groundwater GIS data layer was generated by subtracting a water-table map of groundwater elevation in the ERWVFA from the 10 m (32.8 ft) National Elevation Dataset (NED) data (U.S. Geological Survey, 1999a). Please refer to the following publication for a complete description of how the depth-to-groundwater GIS data layer was generated: Rupert, M.G., and Plummer, L.N., 2009, Groundwater quality, age, and probability of contamination, Eagle River Watershed Valley-Fill Aquifer, North-Central Colorado, 2006-2007: U.S. Geological Survey Scientific Investigations Report 2009-5082, 59 p., http://pubs.usgs.gov/sir/2009/5082/. 200804 Geology data were developed by Day and others (1999), who produced a 1:250,000-scale geologic map of the Leadville quadrangle. Geologic units of interest include the Quaternary sediments, which were used to map the boundary of the ERWVFA, and the Eagle Valley Evaporite, which delineates the location of the gypsum beds in the area. Distance of wells from the gypsum beds was used as one of the independent variables in the logistic regression modeling. 200804 The hydrography data in the Eagle River watershed were extracted from the National Hydrography Dataset (NHD) (U.S. Geological Survey, 1999b). The NHD data were edited to include only the major canals, rivers, and streams. Distance of wells from the major canals, rivers, and streams was used as one of the independent variables in the logistic regression modeling. 200804 Estimates of average annual precipitation for 1961-90 were developed by Daly and others (1994), with the Parameter-elevation Regressions on Independent Slopes Model (PRISM). PRISM uses climatic point data and a digital elevation model (DEM) to generate gridded estimates of climatic parameters. 200804 Three sources of soils data were used. The first were the Soil Survey Geographic Database (SSURGO) soils data, which were developed by the Natural Resources Conservation Service (NRCS) at approximately 1:24,000 scale (U.S. Department of Agriculture, 2008). The SSURGO soils data included a variable for depth to groundwater within the soil horizon, which is defined as "the shallowest depth to a wet soil horizon." This is different than the depth to groundwater mentioned earlier, which used water-table elevations to calculate depth to the groundwater in the entire unsaturated zone and not just the soil horizon. In the soils data, depth to groundwater in the soils horizon was set to the maximum value of 201 cm (79 inches) if the depth was greater than the thickness of the soil horizon. The SSURGO data included a soil factor called "the soil septic suitability factor," which rates the suitability of a certain soil for use by septic-tank absorption fields. The suitability factor is based on soil ratings of saturated hydraulic conductivity, depth to water table in soils layer, ponding, depth to bedrock in the soil layer, and flooding between soil depths of 610 and 1,829 mm (24 and 72 inches). The second source of soils data was the White River National Forest (U.S. Department of Agriculture, 1999), who mapped soils data in the portion of the study area where SSURGO soils data were not mapped (east of Vail). The SSURGO and White River National Forest soils data were checked to assure consistency between the two data sets. The third source of soils data were the State Soil Geographic soils data (STATSGO), which are soils data developed at a much smaller scale (approximately 1:250,000 scale), but which cover the entire study area (U.S. Department of Agriculture, 1991). The STATSGO data were not suitable for use in raw form, so STATSGO data compiled by Schwarz and Alexander (1995) were used. The Schwarz and Alexander (1995) data included weighted averaging of many of the soil characteristics. Some SSURGO and STATSGO soil variables, such as soil hydrologic group, were categorical variables. To facilitate modeling with logistic regression, categorical variables were transformed to numerical variables. For instance, soil hydrologic group is rated in four categories from A through D, with A having the highest infiltration and D having the smallest. Soil hydrologic group A was transformed to a numerical rating of one, and soil hydrologic group D was transformed to a numerical rating of four. 200805 A point data set of wells with groundwater quality and groundwater age data was overlaid with thematic layers of anthropogenic and hydrogeologic data by using a geographic information system to assign each well values for depth to groundwater, distance to major streams and canals, distance to gypsum beds, precipitation, soils, and well depth. Upgradient 90-degree pie-shaped zones of influence were calculated for each well where groundwater quality data were collected to determine the average soils properties upgradient from each sampled well, which were then incorporated into the input data sets for the logistic regression modeling. The 90-degree sector represents a simulated contributing area for each well and was shown to be a more statistically significant way to characterize data around the well at the surface (Lorenz and others, 2003; Gurdak and Qi, 2006). The optimum size for the pie-shaped zones (500 m) was calculated using groundwater modeling and particle tracking (Rupert and Plummer, 2009). The orientation of the 90-degree sector was determined by subtracting 180 degrees from the groundwater flow direction at the well location. The groundwater flow direction was determined using the GRID function ASPECT (eight possible directions) on a raster data set of the water-table surface. An Arc Macro Language (AML) program was used to create a 90-degree sector for each well with the appropriate orientation and radius and then to average the soils factors within the sector using the GRID function FOCALMEAN with the WEDGE option. 200805 Logistic regression statistical modeling techniques were used to develop three statistical models that predict the probability of ground-water contamination by various contaminants. These three models predict the probability of elevated nitrate concentrations, the probability of unmixed young water (using CFC-11 concentrations and tritium activities), and the probability of elevated VOC concentrations. These three probability models used different compounds such as nitrate and VOCs to provide an indication of the predisposition to ground-water contamination by anthropogenic compounds under a variety of conditions and contaminant inputs. 200807 Before constructing the probability maps, all GIS data were converted to grids with 10-m (32.8-ft) spacing. The soils data required an additional processing step. The soils data within 500-m (1,640-ft) pie-shaped buffers oriented upgradient from every grid cell in each soils layer/factor were averaged using the GRID function FOCALMEAN with the WEDGE option. The groundwater flow direction was determined using the GRID function ASPECT on a raster data set of the water-table surface. To increase processing speed, grids of the average soils properties within a 90-degree sector were produced for all 8 possible upgradient directions. The GRID function PICK was then used to choose the 90-degree sector from the possible 8 grids, depending on the flow direction at each cell. After the soils data were averaged, then the logistic regression models were entered into a GIS, and a probability rating was calculated for each grid node in the study area. 200906 Raster Grid Cell 1817 7185 1 Albers Conical Equal Area 37.500000 40.500000 -105.500000 37.000000 0.000000 0.000000 row and column 10.000000 10.000000 meters North American Datum of 1983 Geodetic Reference System 80 6378137.000000 298.257222 The values of the raster data set represent the predicted probability of unmixed young groundwater (defined using chlorofluorocarbon-11 concentrations and tritium activities), expressed in terms of percent probability (ranging from 0 to 100 percent probability). Rupert, M.G., and Plummer, L.N., 2009, Ground-Water Quality, Age, and Probability of Contamination, Eagle River Watershed Valley-Fill Aquifer, North-Central Colorado, 2006-2007: U.S. Geological Survey Scientific Investigations Report 2009-5082, 59 p., accessed August 11, 2009, at http://pubs.usgs.gov/sir/2009/5082/. U.S. Geological Survey Ask USGS -- Water Webserver Team mailing address

507 National Center

Reston VA 20192 USA 1-888-275-8747 (1-888-ASK-USGS) http://answers.usgs.gov/cgi-bin/gsanswers?pemail=h2oteam&subject=GIS+Dataset+sir095082_mix Downloadable Data Although these data have been used by the U.S. Geological Survey, U.S. Department of the Interior, no warranty expressed or implied is made by the U.S. Geological Survey as to the accuracy of the data. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by the U.S. Geological Survey in the use of these data, software, or related materials. The use of firm, trade, or brand names in this report is for identification purposes only and does not constitute endorsement by the U.S. Geological Survey. The names mentioned in this document may be trademarks or registered trademarks of their respective trademark owners. ASCII PKZIP compression Winzip 50.388 MB http://water.usgs.gov/GIS/dsdl/sir095082_mix.e00.zip None. This dataset is provided by USGS as a public service. 20090812 U.S. Geological Survey Ask USGS -- Water Webserver Team mailing address

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Reston VA 20192 USA 1-888-275-8747 (1-888-ASK-USGS) http://water.usgs.gov/user_feedback_form.html FGDC Content Standards for Digital Geospatial Metadata FGDC-STD-001-1998 local time ESRI Metadata Profile