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At least 379 records · Page 21Linked to original sources
USGS2012

A science plan for a comprehensive assessment of water supply in the region underlain by fractured rock in Maryland

The fractured rock region of Maryland, which includes land areas north and west of the Interstate 95 corridor, is the source of water supply for approximately 4.4 million Marylanders, or approximately 76 percent of the State's population. Whereas hundreds of thousands of residents rely on wells (both domestic and community), millions rely on surface-water sources. In this region, land use, geology, topography, water withdrawals, impoundments, and other factors affect water-flow characteristics. The unconfined groundwater systems are closely interconnected with rivers and streams, and are affected by seasonal and climatic variations. During droughts, groundwater levels drop, thereby decreasing well yields, and in some cases, wells have gone dry. Low ground-water levels contribute to reduced streamflows, which in turn, can lead to reduced habitat for aquatic life. Increased demand, over-allocation, population growth, and climate change can affect the future sustainability of water supplies in the region of Maryland underlain by fractured rock. In response to recommendations of the 2008 Advisory Committee on the Management and Protection of the State's Water Resources report, the Maryland Department of the Environment's Water Supply Program, the Maryland Geological Survey, the Maryland Department of Natural Resources, Monitoring and Non-Tidal Assessment (MANTA) Division, and the U.S. Geological Survey have developed a science plan for a comprehensive assessment that will provide new scientific information, new data analysis, and new tools for the State to better manage water resources in the fractured rock region of Maryland. The science plan lays out five goals for the comprehensive assessment: (1) develop tools for the improved management and investigation of groundwater and surface-water resources; (2) characterize factors affecting reliable yields of individual groundwater and surface-water supplies; (3) investigate impacts on nearby water withdrawal users caused by groundwater and surface-water withdrawals; (4) assess the role of streamflow and water withdrawals on the ecological integrity of streams; and (5) improve understanding of the distribution of water-quality conditions in fractured rock aquifers. To accomplish these goals, accurate data collection, review, and analysis are needed, including the study of "Research Watersheds" that can provide detailed information about the potential effects that climate change and water withdrawals may have on groundwater, streamflow, and aquatic life. The assessment planning started in 2009 and is being conducted with close interagency coordination. A Fractured Rock Aquifer Information System is currently (2012) undergoing initial development. Other major tasks that will be performed include the development of work plans for each science goal, the estimation of daily streamflow at ungaged streams, and the design and implementation of Research Watersheds. Finally, scenarios will be modeled to evaluate current water allocation permitting methodologies, investigate effects on nearby water withdrawal users caused by groundwater and surface-water withdrawals, and assess the potential impacts of climate change on water resources. Desktop and Web-based tools will be developed in order to meet the diverse research needs of the assessment. These tools, including the Fractured Rock Aquifer Information System will be continuously improved during the assessment to store relevant groundwater and surface-water data in spatially referenced databases, estimate streamflows, locate higher-yielding wells, estimate the impacts of withdrawals on nearby users, and assess the cumulative impacts of withdrawals on the aquatic resource. Tools will be developed to serve the needs of many audiences, including water resource managers, water suppliers, planners, policymakers, and other scientific investigators.

Maryl↗
USGS2010

Estimation of magnitude and frequency of floods in urban basins in Missouri

Streamgage flood-frequency analyses were done for 35 streamgages on urban streams in and adjacent to Missouri for estimation of the magnitude and frequency of floods in urban areas of Missouri. A log-Pearson Type-III distribution was fitted to the annual series of peak flow data retrieved from the U.S. Geological Survey National Water Information System. For this report, the flood frequency estimates are expressed in terms of percent annual exceedance probabilities of 50, 20, 10, 4, 2, 1, and 0.2. Of the 35 streamgages, 30 are located in Missouri. The remaining five non-Missouri streamgages were added to the dataset to improve the range and applicability of the regression analyses from the streamgage frequency analyses. Ordinary least-squares was used to determine the best set of independent variables for the regression equations. Basin characteristics selected for independent variables into the ordinary least-squares regression analyses were based on theoretical relation to flood flows, literature review of possible basin characteristics, and the ability to measure the basin characteristics using digital datasets and geographic information system technology. Results of the ordinary least-squares were evaluated on the basis of Mallow's Cp statistic, the adjusted coefficient of determination, and the statistical significance of the independent variables. The independent variables of drainage area and percent impervious area were determined to be statistically significant and readily determined from existing digital datasets. The drainage area variable was computed using the best elevation data available, either from a statewide 10-meter grid or high-resolution elevation data from urban areas. The impervious area variable was computed from the National Land Cover Dataset 2001 impervious area dataset. The National Land Cover Dataset 2001 impervious area data for each basin was compared to historical imagery and 7.5-minute topographic maps to verify the national dataset represented the urbanization of the basin at the time streamgage data were collected. Eight streamgages had less urbanization during the period of time streamflow data were collected than was shown on the 2001 dataset. The impervious area values for these eight urban basins were adjusted downward as much as 23 percent to account for the additional urbanization since the streamflow data were collected. Weighted least-squares regression techniques were used to determine the final regression equations for the statewide urban flood-frequency equations. Weighted least-squares techniques improve regression equations by adjusting for different and varying lengths in streamflow records. The final flood-frequency equations for the 50-, 20-, 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probability floods for Missouri provide a technique for estimating peak flows on urban streams at gaged and ungaged sites. The applicability of the equations is limited by the range in basin characteristics used to develop the regression equations. The range in drainage area is 0.28 to 189 square miles; range in impervious area is 2.3 to 46.0 percent. Seven of the 35 selected streamgages were used to compare the results of the existing rural and urban equations to the urban equations presented in this report for the 1-percent annual exceedance probability. Results of the comparison indicate that the estimated peak flows for the urban equation in this report ranged from 3 to 52 percent higher than the results from the rural equations. Comparing the estimated urban peak flows from this report to the existing urban equation developed in 1986 indicated the range was 255 percent lower to 10 percent higher. The overall comparison between the current (2010) and 1986 urban equations indicates a reduction in estimated peak flow values for the 1-percent annual exceedance probability flood.

Missouri↗
USGS1998

Probability of detecting atrazine/desethyl-atrazine and elevated concentrations of nitrate (NO2+NO3-N) in ground water in the Idaho part of the upper Snake River basin

Draft Federal regulations may require that each State develop a State Pesticide Management Plan for the herbicides atrazine, alachlor, cyanazine, metolachlor, and simazine. This study developed maps that the Idaho State Department of Agriculture might use to predict the probability of detecting atrazine and desethyl-atrazine (a breakdown product of atrazine) in ground water in the Idaho part of the upper Snake River Basin. These maps can be incorporated in the State Pesticide Management Plan and help provide a sound hydrogeologic basis for atrazine management in the study area. Maps showing the probability of detecting atrazine/desethyl-atrazine in ground water were developed as follows: (1) Ground-water monitoring data were overlaid with hydrogeologic and anthropogenic data using a geographic information system to produce a data set in which each well had corresponding data on atrazine use, depth to ground water, geology, land use, precipitation, soils, and well depth. These data then were downloaded to a statistical software package for analysis by logistic regression. (2) Individual (univariate) relations between atrazine/desethyl-atrazine in ground water and atrazine use, depth to ground water, geology, land use, precipitation, soils, and well depth data were evaluated to identify those independent variables significantly related to atrazine/ desethyl-atrazine detections. (3) Several preliminary multivariate models with various combinations of independent variables were constructed. (4) The multivariate models which best predicted the presence of atrazine/desethyl-atrazine in ground water were selected. (5) The multivariate models were entered into the geographic information system and the probability maps were constructed. Two models which best predicted the presence of atrazine/desethyl-atrazine in ground water were selected; one with and one without atrazine use. Correlations of the predicted probabilities of atrazine/desethyl-atrazine in ground water with the percent of actual detections were good; r-squared values were 0.91 and 0.96, respectively. Models were verified using a second set of groundwater quality data. Verification showed that wells with water containing atrazine/desethyl-atrazine had significantly higher probability ratings than wells with water containing no atrazine/desethylatrazine (p <0.002). Logistic regression also was used to develop a preliminary model to predict the probability of nitrite plus nitrate as nitrogen concentrations greater than background levels of 2 milligrams per liter. A direct comparison between the atrazine/ desethyl-atrazine and nitrite plus nitrate as nitrogen probability maps was possible because the same ground-water monitoring, hydrogeologic, and anthropogenic data were used to develop both maps. Land use, precipitation, soil hydrologic group, and well depth were significantly related with atrazine/desethyl-atrazine detections. Depth to water, land use, and soil drainage were signifi- cantly related with elevated nitrite plus nitrate as nitrogen concentrations. The differences between atrazine/desethyl-atrazine and nitrite plus nitrate as nitrogen relations were attributed to differences in chemical behavior of these compounds in the environment and possibly to differences in the extent of use and rates of their application.

Idaho↗
USGS2019

Flood-inundation maps for the Iowa River at the Meskwaki Settlement in Iowa, 2019

Digital flood-inundation maps for a 9.3-mile reach of the Iowa River along the Meskwaki Settlement, Iowa, were created by the U.S. Geological Survey (USGS) in cooperation with the Sac and Fox Tribe of the Mississippi in Iowa. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science website 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 05451770 on the Iowa River at County Highway E49 near Tama, Iowa. Near-real-time stages at this streamgage may be obtained on the internet from the USGS National Water Information System at https://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at https://water.weather.gov/ahps/ , which also forecasts flood hydrographs at this site. Flood profiles were computed for the stream reach by means of a calibrated one-dimensional and two-dimensional step-backwater hydraulic model. The model was calibrated by using the current stage-discharge relation at the USGS streamgage 05451770 on the Iowa River at County Highway E49 near Tama, Iowa, and stage and discharge data from historic flooding events that were recorded at the streamgage. The hydraulic model was then used to compute eight water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from the NWS “action stage” of 11 feet (ft) to 18 ft, the stage exceeding the estimated 0.2-percent annual exceedance probability (500-year recurrence interval) flood, as determined at the USGS streamgage 05451770. The simulated water-surface profiles were then combined with a geographic information system digital elevation model to delineate the area flooded at each flood stage (water level). In addition, potential modifications to hydraulic structures within the flood plain were modeled so any effects from the potential modifications could be evaluated. Four comparison points, which were along the flood plain, showed little to no change (less than 0.1 ft) in flood elevation from the existing conditions within the flood plain for the 11- to 16-ft stages as referenced to the USGS streamgage 05451770. There were greater changes (more than 0.1 ft) in flood elevation for the 2 comparison points that were closest to the modified hydraulic structure for the 2 highest modeled stages of 17 and 18 ft. The availability of these maps, along with internet information regarding current stage from the USGS streamgage and forecasted high-flow 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 postflood recovery efforts.

Iowa↗
USGS2016

Methods for estimating peak-flow frequencies at ungaged sites in Montana based on data through water year 2011: Chapter F in Montana StreamStats

The U.S. Geological Survey (USGS), in cooperation with the Montana Department of Natural Resources and Conservation, completed a study to update methods for estimating peak-flow frequencies at ungaged sites in Montana based on peak-flow data at streamflow-gaging stations through water year 2011. The methods allow estimation of peak-flow frequencies (that is, peak-flow magnitudes, in cubic feet per second, associated with annual exceedance probabilities of 66.7, 50, 42.9, 20, 10, 4, 2, 1, 0.5, and 0.2 percent) at ungaged sites. The annual exceedance probabilities correspond to 1.5-, 2-, 2.33-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively. Regional regression analysis is a primary focus of Chapter F of this Scientific Investigations Report, and regression equations for estimating peak-flow frequencies at ungaged sites in eight hydrologic regions in Montana are presented. The regression equations are based on analysis of peak-flow frequencies and basin characteristics at 537 streamflow-gaging stations in or near Montana and were developed using generalized least squares regression or weighted least squares regression. All of the data used in calculating basin characteristics that were included as explanatory variables in the regression equations were developed for and are available through the USGS StreamStats application (http://water.usgs.gov/osw/streamstats/) for Montana. StreamStats is a Web-based geographic information system application that was created by the USGS to provide users with access to an assortment of analytical tools that are useful for water-resource planning and management. The primary purpose of the Montana StreamStats application is to provide estimates of basin characteristics and streamflow characteristics for user-selected ungaged sites on Montana streams. The regional regression equations presented in this report chapter can be conveniently solved using the Montana StreamStats application. Selected results from this study were compared with results of previous studies. For most hydrologic regions, the regression equations reported for this study had lower mean standard errors of prediction (in percent) than the previously reported regression equations for Montana. The equations presented for this study are considered to be an improvement on the previously reported equations primarily because this study (1) included 13 more years of peak-flow data; (2) included 35 more streamflow-gaging stations than previous studies; (3) used a detailed geographic information system (GIS)-based definition of the regulation status of streamflow-gaging stations, which allowed better determination of the unregulated peak-flow records that are appropriate for use in the regional regression analysis; (4) included advancements in GIS and remote-sensing technologies, which allowed more convenient calculation of basin characteristics and investigation of many more candidate basin characteristics; and (5) included advancements in computational and analytical methods, which allowed more thorough and consistent data analysis. This report chapter also presents other methods for estimating peak-flow frequencies at ungaged sites. Two methods for estimating peak-flow frequencies at ungaged sites located on the same streams as streamflow-gaging stations are described. Additionally, envelope curves relating maximum recorded annual peak flows to contributing drainage area for each of the eight hydrologic regions in Montana are presented and compared to a national envelope curve. In addition to providing general information on characteristics of large peak flows, the regional envelope curves can be used to assess the reasonableness of peak-flow frequency estimates determined using the regression equations.

Montana↗
USGS2019

Flood-inundation maps of the Meramec River from Eureka to Arnold, Missouri, 2018

Libraries of digital flood-inundation maps that spanned a combined 37.2-mile reach of the Meramec River that extended upstream from Eureka, Missouri, to downstream near the confluence of the Meramec and Mississippi Rivers were created by the U.S. Geological Survey (USGS) in cooperation with the U.S. Army Corps of Engineers, Metropolitan St. Louis Sewer District, Missouri Department of Transportation, Missouri American Water, Federal Emergency Management Agency Region 7, and the cities of Pacific, Eureka, Wildwood, and Arnold. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science website 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 cooperative USGS streamgages for the Meramec River near Eureka, Mo. (USGS station 07019000), the Meramec River at Valley Park, Mo. (USGS station 07019130), the Meramec River at Fenton, Mo. (USGS station 07019210), and the Meramec River at Arnold, Mo. (USGS station 07019300). Near-real-time stage data at these streamgages may be obtained from the USGS National Water Information System at https://doi.org/10.5066/F7P55KJN or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at https://water.weather.gov/ahps/ , which also forecasts flood hydrographs at these sites (listed as NWS sites erkm7, vllm7, fnnm7, and arnm7, respectively). Flood profiles were computed for the stream reach by means of a calibrated one-dimensional step-backwater hydraulic model. The model was calibrated using a stage-discharge relation at the Meramec River near Eureka, Mo., streamgage (USGS station 07019000) and documented high-water marks from the flood of December 2015 through January 2016. The calibrated hydraulic model was used to compute water-surface profiles: 1 set for the Meramec River near Eureka, Mo., streamgage (USGS station 07019000); 1 set for the Meramec River at Valley Park, Mo., streamgage (USGS station 07019130); 7 sets for the Meramec River at Fenton, Mo., streamgage (USGS station 07019210) for a range of Mississippi River conditions; and 8 sets for the Meramec River at Arnold, Mo., streamgage (USGS station 07019300) for a range of Mississippi River conditions. The water-surface profiles were produced for stages at 1-foot (ft) intervals referenced to the datum from each streamgage and ranging from the NWS action stage, or near bankfull discharge, to the stage corresponding to the estimated 0.2-percent annual exceedance probability (500-year recurrence interval) flood, as determined at the Meramec River near Eureka, Mo., streamgage (USGS station 07019000). The simulated water-surface profiles then were combined with a geographic information system digital elevation model (derived from light detection and ranging data having a 0.28-ft vertical accuracy and 3.28-ft horizontal resolution) to delineate the area flooded at each simulated 1-ft stage increment. Previously published flood-inundation maps were updated and incorporated in the flood map libraries for USGS stations 07019130 and 07019210 to complete the map sets corresponding to eight Mississippi River conditions. The availability of these maps, along with internet information regarding current stage from the USGS streamgages and forecasted high-flow 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 and for postflood recovery efforts.

Missouri↗
USGS2009

Development of a Watershed Boundary Dataset for Mississippi

The U.S. Geological Survey, in cooperation with the Mississippi Department of Environmental Quality, U.S. Department of Agriculture-Natural Resources Conservation Service, Mississippi Department of Transportation, U.S. Department of Agriculture-Forest Service, and the Mississippi Automated Resource Information System, developed a 1:24,000-scale Watershed Boundary Dataset for Mississippi including watershed and subwatershed boundaries, codes, names, and drainage areas. The Watershed Boundary Dataset for Mississippi provides a standard geographical framework for water-resources and selected land-resources planning. The original 8-digit subbasins (hydrologic unit codes) were further subdivided into 10-digit watersheds and 12-digit subwatersheds - the exceptions are the Lower Mississippi River Alluvial Plain (known locally as the Delta) and the Mississippi River inside levees, which were only subdivided into 10-digit watersheds. Also, large water bodies in the Mississippi Sound along the coast were not delineated as small as a typical 12-digit subwatershed. All of the data - including watershed and subwatershed boundaries, hydrologic unit codes and names, and drainage-area data - are stored in a Geographic Information System database.

Open-File Report↗
USGS2013

Cost-effectiveness analysis of sandhill crane habitat management

Invasive species often threaten native wildlife populations and strain the budgets of agencies charged with wildlife management. We demonstrate the potential of cost-effectiveness analysis to improve the efficiency and value of efforts to enhance sandhill crane ( Grus canadensis ) roosting habitat. We focus on the central Platte River in Nebraska (USA), a region of international ecological importance for migrating avian species including sandhill cranes. Cost-effectiveness analysis is a valuation process designed to compare alternative actions based on the cost of achieving a pre-determined objective. We estimated costs for removal of invasive vegetation using geographic information system simulations and calculated benefits as the increase in area of sandhill crane roosting habitat. We generated cost effectiveness values for removing invasive vegetation on 7 land parcels and for the entire central Platte River to compare the cost-effectiveness of management at specific sites and for the central Platte River landscape. Median cost effectiveness values for the 7 land parcels evaluated suggest that costs for creating 1 additional hectare of sandhill crane roosting habitat totaled US $1,595. By contrast, we found that creating an additional hectare of sandhill crane roosting habitat could cost as much as US $12,010 for some areas in the central Platte River, indicating substantial cost savings can be achieved by using a cost effectiveness analysis to target specific land parcels for management. Cost-effectiveness analysis, used in conjunction with geographic information systems, can provide decision-makers with a new tool for identifying the most economically efficient allocation of resources to achieve habitat management goals.

Nebraska↗
USGS2012

Specific conductance measurements in central and western New York streams - A retrospective characterization

U.S. Geological Survey (USGS) Data Rescue Program funds were used to recover data from paper records for 139 streamgages across central and western New York State; 6,133 different streamflow measurement forms, collected between 1970-80, contained field water-quality measurements. The water-quality data were entered, reviewed, and uploaded into the USGS National Water Information System. In total, 4,285 unique site visits were added to the database. The new values represent baseline water quality from which to measure change and will lead to a comparison of water-quality change over the last 40 years and into the future. Specific conductance was one of the measured properties and represents a simple way to determine if ambient inorganic water quality has been altered by anthropogenic (road salt runoff, wastewater discharges, or natural gas development) or natural sources. The objective of this report is to describe ambient specific conductance characteristics of surface water across the central and western part of New York. This report presents median specific conductance of stream discharge for the period 1970-80 and a description of the relation between specific conductance and concentrations of total dissolved solids (TDS) retrieved from the USGS National Water Information System (NWIS) database from 1955 to present. The data descriptions provide a baseline of surface-water specific conductance data that can used for comparison to current and future measurements in New York streams.

New York;Pennsylvania↗
USGS2016

Flood-inundation maps for Lake Champlain in Vermont and in northern Clinton County, New York

Digital flood-inundation maps for an approximately100-mile length of Lake Champlain in Addison, Chittenden, Franklin, and Grand Isle Counties in Vermont and northern Clinton County in New York were created by the U.S. Geological Survey (USGS) in cooperation with the International Joint Commission (IJC). The flood-inundationmaps, which can be accessed through the International Joint Commission (IJC) Web site at http://www.ijc.org/en_/ , depict estimates of the areal extent flooding correspondingto selected water levels (stages) at the USGS lake gage on the Richelieu River (Lake Champlain) at Rouses Point, N.Y. (station number 04295000). In this study, wind and seiche effects (standing oscillating wave with a long wavelength) were not taken into account and the flood-inundation mapsreflect 11 stages (elevations) for Lake Champlain that are static for the study length of the lake. Near-real-time stages at this lake gage, and others on Lake Champlain, may be obtained on the Internet from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/ , which also forecasts flood hydrographs at the Richelieu River (Lake Champlain) at Rouses Point. Static flood boundary extents were determined for LakeChamplain in Addison, Chittenden, Franklin, and Grand Isle Counties in Vermont and northern Clinton County in New York using recently acquired (2013–2014) lidar (light detection and ranging) and may be referenced to any of the five USGS lake gages on Lake Champlain. Of these five lakgages, USGS lake gage 04295000, Richelieu River (Lake Champlain) at Rouses Point, N.Y., is the only USGS lake gage that is also a National Weather Service prediction location. Flood boundary extents for the Lake Champlain static flood-inundation map corresponding to the May 201 flood(103.2 feet [ft], National Geodetic Vertical Datum [NGVD] 29) were evaluated by comparing these boundary extents against the inundation area extents determined for the May 2011 flood (which incorporated documented high-water marksfrom the flood of May 201) (Bjerklie and others, 2014). A digital elevation model (DEM) was created by USGS, within a geographic information system (GIS), from the recently flown and processed light detection and ranging(lidar) data (2013–2014) in Vermont and the lake shore area of northern Clinton County in New York. The lidar data have a vertical accuracy of 0.3 to 0.6-ft (9.6 to 18.0-centimeters [cm]) and a horizontal resolution of 2.3 to 4.6 ft (0.7 to 1.4 meters). This DEM was used in determining the floodboundary for 11 flood stages at 0.5-ft intervals from 100.0 to104.0 ft (NGVD 29) and 1-ft intervals from 104.0 to 106.0 ft (NGVD 29) as referenced to the USGS lake gage 04295000, Richelieu River (Lake Champlain) at Rouses Point, N.Y. In addition, the May 2011 flood-inundation area for elevation103.20 ft (NGVD 29) (102.77 ft, North American Vertical Datum [NAVD] 88) was determined from this DEM. The May 2011 flood is the highest recorded lake water level (stage)at the Rouses Point, N.Y., lake gage. Flood stages greater than 101.5 ft (NGVD 29) exceed the “major flood stage”as defined by the NationalWeather Service for USGS lake gage 04295000. The availability of these maps, along with Internet information regarding current stage from the USGS lake gage and forecasted high-flow stages from the NationalWeather Service, will provide emergency management personnel and residents with information that is critical for flood responseactivities such as evacuations and road closures, as well as for post-flood recovery eforts.

New York, Vermont↗
USGS2002

Spatial digital database for the tectonic map of southeast Arizona

A spatial database was created for Drewes' (1980) tectonic map of southeast Arizona: this database supercedes Drewes and others (2001, ver. 1.0). Staff and a contractor at the U.S. Geological Survey in Tucson, Arizona completed an interim digital geologic map database for the east part of the map in 2001, made revisions to the previously released digital data for the west part of the map (Drewes and others, 2001, ver. 1.0), merged data files for the east and west parts, and added additional data not previously captured. Digital base map data files (such as topography, roads, towns, rivers and lakes) are not included: they may be obtained from a variety of commercial and government sources. This digital geospatial database is one of many being created by the U.S. Geological Survey as an ongoing effort to provide geologic information in a geographic information system (GIS) for use in spatial analysis. The resulting digital geologic map database can be queried in many ways to produce a variety of geologic maps and derivative products. Because Drewes' (1980) map sheets include additional text and graphics that were not included in this report, scanned images of his maps (i1109_e.jpg, i1109_w.jpg) are included as a courtesy to the reader. This database should not be used or displayed at any scale larger than 1:125,000 (for example, 1:100,000 or 1:24,000). The digital geologic map plot files (i1109_e.pdf and i1109_w.pdf) that are provided herein are representations of the database (see Appendix A). The map area is located in southeastern Arizona (fig. 1). This report describes the map units (from Drewes, 1980), the methods used to convert the geologic map data into a digital format, the ArcInfo GIS file structures and relationships, and explains how to download the digital files from the U.S. Geological Survey public access World Wide Web site on the Internet. The manuscript and digital data review by Helen Kayser (Information Systems Support, Inc.) is greatly appreciated.

Arizona↗
USGS2007

Mining Claim Activity on Federal Land in the United States

Several statistical compilations of mining claim activity on Federal land derived from the Bureau of Land Management's LR2000 database have previously been published by the U.S Geological Survey (USGS). The work in the 1990s did not include Arkansas or Florida. None of the previous reports included Alaska because it is stored in a separate database (Alaska Land Information System) and is in a different format. This report includes data for all states for which there are Federal mining claim records, beginning in 1976 and continuing to the present. The intent is to update the spatial and statistical data associated with this report on an annual basis, beginning with 2005 data. The statistics compiled from the databases are counts of the number of active mining claims in a section of land each year from 1976 to the present for all states within the United States. Claim statistics are subset by lode and placer types, as well as a dataset summarizing all claims including mill site and tunnel site claims. One table presents data by case type, case status, and number of claims in a section. This report includes a spatial database for each state in which mining claims were recorded, except North Dakota, which only has had two claims. A field is present that allows the statistical data to be joined to the spatial databases so that spatial displays and analysis can be done by using appropriate geographic information system (GIS) software. The data show how mining claim activity has changed in intensity, space, and time. Variations can be examined on a state, as well as a national level. The data are tied to a section of land, approximately 640 acres, which allows it to be used at regional, as well as local scale. The data only pertain to Federal land and mineral estate that was open to mining claim location at the time the claims were staked.

Data Series↗
USGS2003

Raster dataset showing the probability of elevated concentrations of nitrate in ground water in Colorado, hydrogeomorphic regions and fertilizer use estimates included

This dataset is one of eight datasets produced by this study. Four of the datasets predict the probability of detecting atrazine and(or) desethyl-atrazine (a breakdown product of atrazine) in ground water in Colorado; the other four predict the probability of detecting elevated concentrations of nitrate in ground water in Colorado. The four datasets that predict the probability of atrazine and(or) desethyl-atrazine (atrazine/DEA) are differentiated by whether or not they incorporated atrazine use and whether or not they incorporated hydrogeomorphic regions. The four datasets that predict the probability of elevated concentrations of nitrate are differentiated by whether or not they incorporated fertilizer use and whether or not they incorporated hydrogeomorphic regions. Each of the eight datasets has its own unique strengths and weaknesses. The user is cautioned to read Rupert (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 02-4269, 35 p., http://water.usgs.gov/pubs/wri/wri02-4269/) to determine if he(she) is using the most appropriate dataset for his(her) particular needs. This dataset specifically predicts the probability of detecting elevated concentrations of nitrate in ground water in Colorado with hydrogeomorphic regions and fertilizer use included. The following text was extracted from Rupert (2003). Draft Federal regulations may require that each State develop a State Pesticide Management Plan for the herbicides atrazine, alachlor, metolachlor, and simazine. Maps were developed that the State of Colorado could use to predict the probability of detecting atrazine/DEA in ground water in Colorado. These maps can be incorporated into the State Pesticide Management Plan and can help provide a sound hydrogeologic basis for atrazine management in Colorado. Maps showing the probability of detecting elevated nitrite plus nitrate as nitrogen (nitrate) concentrations in ground water in Colorado also were developed because nitrate is a contaminant of concern in many areas of Colorado. Maps showing the probability of detecting atrazine/DEA at or greater than concentrations of 0.1 microgram per liter and nitrate concentrations in ground water greater than 5 milligrams per liter were developed as follows: (1) Ground-water quality data were overlaid with anthropogenic and hydrogeologic data by using a geographic information system (GIS) to produce a dataset in which each well had corresponding data on atrazine use, fertilizer use, geology, hydrogeomorphic regions, land cover, precipitation, soils, and well construction. These data then were downloaded to a statistical software package for analysis by logistic regression. (2) Relations were observed between ground-water quality and the percentage of land-cover categories within circular regions (buffers) around wells. Several buffer sizes were evaluated; the buffer size that provided the strongest relation was selected for use in the logistic regression models. (3) Relations between concentrations of atrazine/DEA and nitrate in ground water and atrazine use, fertilizer use, geology, hydrogeomorphic regions, land cover, precipitation, soils, and well-construction data were evaluated, and several preliminary multivariate models with various combinations of independent variables were constructed. (4) The multivariate models that best predicted the presence of atrazine/DEA and elevated concentrations of nitrate in ground water were selected. (5) The accuracy of the multivariate models was confirmed by validating the models with an independent set of ground-water quality data. (6) The multivariate models were entered into a geographic information system and the probability GRIDS were constructed.

Open-File Report↗
USGS2008

Using logistic regression to predict a probability of debris flows in areas burned by wildfires, southern California, 2003-2006

Logistic regression was used to develop statistical models that can be used to predict the probability of debris flows in areas recently burned by wildfires by using data from 14 wildfires that burned in southern California during 2003-2006. Twenty-eight independent variables describing the basin morphology, burn severity, rainfall, and soil properties of 306 drainage basins located within those burned areas were evaluated. The models were developed as follows: (1) Basins that did and did not produce debris flows soon after the 2003 to 2006 fires were delineated from data in the National Elevation Dataset using a geographic information system; (2) Data describing the basin morphology, burn severity, rainfall, and soil properties were compiled for each basin. These data were then input to a statistics software package for analysis using logistic regression; and (3) Relations between the occurrence or absence of debris flows and the basin morphology, burn severity, rainfall, and soil properties were evaluated, and five multivariate logistic regression models were constructed. All possible combinations of independent variables were evaluated to determine which combinations produced the most effective models, and the multivariate models that best predicted the occurrence of debris flows were identified. Percentage of high burn severity and 3-hour peak rainfall intensity were significant variables in all models. Soil organic matter content and soil clay content were significant variables in all models except Model 5. Soil slope was a significant variable in all models except Model 4. The most suitable model can be selected from these five models on the basis of the availability of independent variables in the particular area of interest and field checking of probability maps. The multivariate logistic regression models can be entered into a geographic information system, and maps showing the probability of debris flows can be constructed in recently burned areas of southern California. This study demonstrates that logistic regression is a valuable tool for developing models that predict the probability of debris flows occurring in recently burned landscapes.

California↗
USGS2003

Probability of detecting atrazine/desethyl-atrazine and elevated concentrations of nitrate in ground water in Colorado

Draft Federal regulations may require that each State develop a State Pesticide Management Plan for the herbicides atrazine, alachlor, metolachlor, and simazine. Maps were developed that the State of Colorado could use to predict the probability of detecting atrazine and desethyl-atrazine (a breakdown product of atrazine) in ground water in Colorado. These maps can be incorporated into the State Pesticide Management Plan and can help provide a sound hydrogeologic basis for atrazine management in Colorado. Maps showing the probability of detecting elevated nitrite plus nitrate as nitrogen (nitrate) concentrations in ground water in Colorado also were developed because nitrate is a contaminant of concern in many areas of Colorado. Maps showing the probability of detecting atrazine and(or) desethyl-atrazine (atrazine/DEA) at or greater than concentrations of 0.1 microgram per liter and nitrate concentrations in ground water greater than 5 milligrams per liter were developed as follows: (1) Ground-water quality data were overlaid with anthropogenic and hydrogeologic data using a geographic information system to produce a data set in which each well had corresponding data on atrazine use, fertilizer use, geology, hydrogeomorphic regions, land cover, precipitation, soils, and well construction. These data then were downloaded to a statistical software package for analysis by logistic regression. (2) Relations were observed between ground-water quality and the percentage of land-cover categories within circular regions (buffers) around wells. Several buffer sizes were evaluated; the buffer size that provided the strongest relation was selected for use in the logistic regression models. (3) Relations between concentrations of atrazine/DEA and nitrate in ground water and atrazine use, fertilizer use, geology, hydrogeomorphic regions, land cover, precipitation, soils, and well-construction data were evaluated, and several preliminary multivariate models with various combinations of independent variables were constructed. (4) The multivariate models that best predicted the presence of atrazine/DEA and elevated concentrations of nitrate in ground water were selected. (5) The accuracy of the multivariate models was confirmed by validating the models with an independent set of ground-water quality data. (6) The multivariate models were entered into a geographic information system and the probability maps were constructed.

Colorado↗
USGS2013

Methods for estimating annual exceedance-probability discharges for streams in Iowa, based on data through water year 2010

A statewide study was performed to develop regional regression equations for estimating selected annual exceedance-probability statistics for ungaged stream sites in Iowa. The study area comprises streamgages located within Iowa and 50 miles beyond the State’s borders. Annual exceedance-probability estimates were computed for 518 streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data through 2010. The estimation of the selected statistics included a Bayesian weighted least-squares/generalized least-squares regression analysis to update regional skew coefficients for the 518 streamgages. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low flows. Also, geographic information system software was used to measure 59 selected basin characteristics for each streamgage. Regional regression analysis, using generalized least-squares regression, was used to develop a set of equations for each flood region in Iowa for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. A total of 394 streamgages were included in the development of regional regression equations for three flood regions (regions 1, 2, and 3) that were defined for Iowa based on landform regions and soil regions. Average standard errors of prediction range from 31.8 to 45.2 percent for flood region 1, 19.4 to 46.8 percent for flood region 2, and 26.5 to 43.1 percent for flood region 3. The pseudo coefficients of determination for the generalized least-squares equations range from 90.8 to 96.2 percent for flood region 1, 91.5 to 97.9 percent for flood region 2, and 92.4 to 96.0 percent for flood region 3. The regression equations are applicable only to stream sites in Iowa with flows not significantly affected by regulation, diversion, channelization, backwater, or urbanization and with basin characteristics within the range of those used to develop the equations. These regression equations will be implemented within the U.S. Geological Survey StreamStats Web-based geographic information system tool. StreamStats allows users to click on any ungaged site on a river and compute estimates of the eight selected statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged sites also are provided by the Web-based tool. StreamStats also allows users to click on any streamgage in Iowa and estimates computed for these eight selected statistics are provided for the streamgage.

Iowa↗
USGS2014

Anthropogenic organic compounds in source water of select community water systems in the United States, 2002-10

Drinking water delivered by community water systems (CWSs) comes from one or both of two sources: surface water and groundwater. Source water is raw, untreated water used by CWSs and is usually treated before distribution to consumers. Beginning in 2002, the U.S. Geological Survey’s (USGS) National Water-Quality Assessment Program initiated Source Water-Quality Assessments (SWQAs) at select CWSs across the United States, primarily to characterize the occurrence of a large number of anthropogenic organic compounds that are predominantly unregulated by the U.S. Environmental Protection Agency. Source-water samples from CWSs were collected during 2002–10 from 20 surface-water sites (river intakes) and during 2002–09 from 448 groundwater sites (supply wells). River intakes were sampled approximately 16 times during a 1-year sampling period, and supply wells were sampled once. Samples were monitored for 265 anthropogenic organic compounds. An additional 3 herbicides and 16 herbicide degradates were monitored in samples collected from 8 river intakes and 118 supply wells in areas where these compounds likely have been used. Thirty-seven compounds have an established U.S. Environmental Protection Agency (EPA) Maximum Contaminant Level (MCL) for drinking water, 123 have USGS Health-Based Screening Levels (HBSLs), and 29 are included on the EPA Contaminant Candidate List 3. All compounds detected in source water were evaluated both with and without an assessment level and were grouped into 13 categories (hereafter termed as “use groups”) based on their primary use or source. The CWS sites were characterized in a national context using an extract of the EPA Safe Drinking Water Information System to develop spatially derived and system-specific ancillary data. Community water system information is contained in the EPA Public Supply Database, which includes 2,016 active river intakes and 112,099 active supply wells. Ancillary variables including population served, watershed size, land use, population density, and recharge were characterized for each of the watersheds for river intakes and contributing areas for supply wells. A total of 313 samples were collected from 20 river intakes. Between the years of 2002 through 2010, samples were collected approximately 16 times over the course of a year. Seventy-one compounds from 12 of the 13 use groups commonly occurred (detected in greater than or equal to 1 percent of samples using an assessment level of 0.05 microgram per liter or when a compound was detected in greater than or equal to 10 percent of samples without an assessment level) indicating a wide variety of sources and pathways to these rivers and highlighting the importance of source-water protection strategies. A total of 448 supply wells were sampled once during 2002–10 as part of 30 independent groundwater studies. About 15 CWS supply wells were sampled for each independent groundwater study. Twenty-eight compounds from 7 of the 13 use groups commonly occurred indicating a wide variety of sources and pathways exist for these compounds to reach these wells and highlighting the importance of wellhead protection strategies. About one-half the 265 compounds monitored (122) were detected in both surface water and groundwater samples. A more diverse suite of compounds were detected in surface water in comparison to groundwater. However, herbicides and herbicide degradates were the most frequent group of compounds detected in both surface water and groundwater. Sixty-five of the most commonly occurring compounds were detected in one or more samples from both surface water and groundwater. Human-health benchmarks (MCLs for regulated compounds and HBSLs for unregulated compounds) were available for more than one-half the compounds (160 of the 265) monitored in this study. Fifty-eight percent (41 of 71) of the commonly occurring compounds in surface water have a human-health benchmark to which concentrations can be compared; 19 have MCLs and 22 have HBSLs. Eighty-three percent (24 of 28) of the most commonly occurring compounds in groundwater have a human-health benchmark for which concentrations can be compared; 14 have MCLs and 10 have HBSLs. To put results from this study into context with the national distribution of river intakes and supply wells used by CWSs, sites were grouped into the respective national population of land-use quartiles. The increase in compound occurrence with increasing urban and agricultural land use in the watershed or contributing area was more evident for rivers than for supply wells. The increase in detection frequency of herbicides and herbicide degradates with increasing agricultural land use was more evident for rivers than for supply wells. The occurrence of solvents did not change substantially with increasing urban land use for rivers or supply wells. Basic co-occurrence analyses were completed with and without an assessment level. Considering all detections in surface water without an assessment level, approximately 86 percent of source-water samples contained 2 or more compounds, and 50 percent of samples contained at least 14 compounds. Considering all detections in groundwater without an assessment level, 50 percent of samples contained at least three compounds. For the most part, the compounds detected most frequently as individual compounds in the environment often composed the most frequent unique mixtures. Five of the 10 most frequently co-occurring unique mixtures in both surface water and groundwater were the same: atrazine and deethylatrazine; atrazine and chloroform; deethylatrazine and simazine; atrazine and simazine; and deethylatrazine, atrazine, and simazine. Because similar mixtures were identified in both surface water and groundwater without an assessment level, future studies could be directed toward better understanding the toxicological importance of these unique mixtures. Summed concentrations of herbicide degradates were compared to concentrations of the parent herbicides in surface-water and groundwater samples collected from 8 river intakes and 118 CWS wells, from which samples were analyzed for an additional 3 herbicides and 16 degradates. The toxicity to humans for many of these degradate products is largely unknown and thus points to the importance of monitoring these compounds (both the parent and degradate) in the environment. This study highlights the importance of anthropogenic organic compounds in source water of select CWSs in the United States by characterizing their occurrence in surface-water and groundwater samples. Compound concentrations and occurrence are summarized and evaluated in a human-health context, when possible. Additionally, compounds found to co-occur as mixtures for both surface water and groundwater highlight the significance of low-level compound co-occurrence.

Scientific Investigations Report↗
USGS2000

Forest soil chemistry and terrain attributes in a Catskills watershed

Knowledge of soil chemistry is useful in assessing the sensitivity of forested areas to natural and anthropogenic disturbances, but characterizing large areas is expensive because of the large sample numbers required and the cost of soil chemical analyses. We collected and chemically analyzed soil samples from 72 sites within a 214-ha watershed in the Catskill Mountains of New York to evaluate factors that influence soil chemistry and whether terrain features could be used to predict soil chemical properties. Using geographic information system (GIS) techniques, we determined five terrain attributes at each sampling location: (i) slope, (ii) aspect, (iii) elevation, (iv) topographic index, and (v) flow accumulation. These attributes were ineffective in predicting the chemical properties of organic and mineral soil samples; together they explained only 4 to 25% of the variance in pH(w), effective cation-exchange capacity (CEC(e)), exchangeable bases, exchangeable acidity, total C, total N, and C/N ratio. Regressions among soil properties were much better; total C and pH(w) together explained 33 to 66% of the variation in exchangeable bases and CEC(e). Total C was positively correlated with N (r = 0.91 and 0.96 in Oa horizons and mineral soil, respectively), exchangeable bases (r = 0.65, 0.76), and CEC(e) (r = 0.54, 0.44), indicating the importance of organic matter to the chemistry of these acidic soils. The fraction of CEC(e) occupied by H explained 44% of the variation in pH(w). Soil chemical properties at this site vary on spatial scales finer than typical GIS analyses, resulting in relationships with poor predictive power. Thus, interrelationships among soil properties are more reliable for prediction.Knowledge of soil chemistry is useful in assessing the sensitivity of forested areas to natural and anthropogenic disturbances, but characterizing large areas is expensive because of the large sample numbers required and the cost of soil chemical analyses. We collected and chemically analyzed soil samples from 72 sites within a 214-ha watershed in the Catskill Mountains of New York to evaluate factors that influence soil chemistry and whether terrain features could be used to predict soil chemical properties. Using geographic information system (GIS) techniques, we determined five terrain attributes at each sampling location: (i) slope, (ii) aspect, (iii) elevation, (iv) topographic index, and (v) flow accumulation. These attributes were ineffective in predicting the chemical properties of organic and mineral soil samples; together they explained only 4 to 25% of the variance in pHw, effective cation-exchange capacity (CECe), exchangeable bases, exchangeable acidity, total C, total N, and C/N ratio. Regressions among soil properties were much better; total C and pHw together explained 33 to 66% of the variation in exchangeable bases and CECe. Total C was positively correlated with N (r = 0.91 and 0.96 in Oa horizons and mineral soil, respectively), exchangeable bases (r = 0.65, 0.76), and CECe (r = 0.54, 0.44), indicating the importance of organic matter to the chemistry of these acidic soils. The fraction of CECe occupied by H explained 44% of the variation in pHw. Soil chemical properties at this site vary on spatial scales finer than typical GIS analyses, resulting in relationships with poor predictive power. Thus, interrelationships among soil properties are more reliable for prediction.

New York↗