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At least 469 records · Page 26Linked to original sources
USGS1991

Techniques and strategies for data integration in mineral resource assessment

The Geologic and the National Mapping divisions of the U.S. Geological Survey have been involved formally in cooperative research and development of computer-based geographic information systems (GISs) applied to mineral-resource assessment objectives since 1982. Experience in the Conterminous United States Mineral Assessment Program (CUSMAP) projects including the Rolla, Missouri; Dillon, Montana; Butte, Montana; and Tonopah, Nevada 1?? ?? 2?? quadrangles, has resulted in the definition of processing requirements for geographically and mineral-resource data that are common to these studies. The diverse formats of data sets collected and compiled for regional mineral-resource assessments necessitate capabilities for digitally encoding and entering data into appropriate tabular, vector, and raster subsystems of the GIS. Although many of the required data sets are either available or can be provided in a digital format suitable for direct entry, their utility is largely dependent on the original intent and consequent preprocessing of the data. In this respect, special care must be taken to ensure the digital data type, encoding, and format will meet assessment objectives. Data processing within the GIS is directed primarily toward the development and application of models that can be used to describe spatially geological, geophysical, and geochemical environments either known or inferred to be associated with specific types of mineral deposits. Consequently, capabilities to analyze spatially, aggregate, and display relations between data sets are principal processing requirements. To facilitate the development of these models within the GIS, interfaces must be developed among vector-, raster-, and tabular-based processing subsystems to reformat resident data sets for comparative analyses and multivariate display of relations.

Conference Paper↗
USGS2012

Comparison of two regression-based approaches for determining nutrient and sediment fluxes and trends in the Chesapeake Bay watershed

Nutrient and sediment fluxes and changes in fluxes over time are key indicators that water resource managers can use to assess the progress being made in improving the structure and function of the Chesapeake Bay ecosystem. The U.S. Geological Survey collects annual nutrient (nitrogen and phosphorus) and sediment flux data and computes trends that describe the extent to which water-quality conditions are changing within the major Chesapeake Bay tributaries. Two regression-based approaches were compared for estimating annual nutrient and sediment fluxes and for characterizing how these annual fluxes are changing over time. The two regression models compared are the traditionally used ESTIMATOR and the newly developed Weighted Regression on Time, Discharge, and Season (WRTDS). The model comparison focused on answering three questions: (1) What are the differences between the functional form and construction of each model? (2) Which model produces estimates of flux with the greatest accuracy and least amount of bias? (3) How different would the historical estimates of annual flux be if WRTDS had been used instead of ESTIMATOR? One additional point of comparison between the two models is how each model determines trends in annual flux once the year-to-year variations in discharge have been determined. All comparisons were made using total nitrogen, nitrate, total phosphorus, orthophosphorus, and suspended-sediment concentration data collected at the nine U.S. Geological Survey River Input Monitoring stations located on the Susquehanna, Potomac, James, Rappahannock, Appomattox, Pamunkey, Mattaponi, Patuxent, and Choptank Rivers in the Chesapeake Bay watershed. Two model characteristics that uniquely distinguish ESTIMATOR and WRTDS are the fundamental model form and the determination of model coefficients. ESTIMATOR and WRTDS both predict water-quality constituent concentration by developing a linear relation between the natural logarithm of observed constituent concentration and three explanatory variables—the natural log of discharge, time, and season. ESTIMATOR uses two additional explanatory variables—the square of the log of discharge and time-squared. Both models determine coefficients for variables for a series of estimation windows. ESTIMATOR establishes variable coefficients for a series of 9-year moving windows; all observed constituent concentration data within the 9-year window are used to establish each coefficient. Conversely, WRTDS establishes variable coefficients for each combination of discharge and time using only observed concentration data that are similar in time, season, and discharge to the day being estimated. As a result of these distinguishing characteristics, ESTIMATOR reproduces concentration-discharge relations that are closely approximated by a quadratic or linear function with respect to both the log of discharge and time. Conversely, the linear model form of WRTDS coupled with extensive model windowing for each combination of discharge and time allows WRTDS to reproduce observed concentration-discharge relations that are more sinuous in form. Another distinction between ESTIMATOR and WRTDS is the reporting of uncertainty associated with the model estimates of flux and trend. ESTIMATOR quantifies the standard error of prediction associated with the determination of flux and trends. The standard error of prediction enables the determination of the 95-percent confidence intervals for flux and trend as well as the ability to test whether the reported trend is significantly different from zero (where zero equals no trend). Conversely, WRTDS is unable to propagate error through the many (over 5,000) models for unique combinations of flow and time to determine a total standard error. As a result, WRTDS flux estimates are not reported with confidence intervals and a level of significance is not determined for flow-normalized fluxes. The differences between ESTIMATOR and WRTDS, with regard to model form and determination of model coefficients, have an influence on the determination of nutrient and sediment fluxes and associated changes in flux over time as a result of management activities. The comparison between the model estimates of flux and trend was made for combinations of five water-quality constituents at nine River Input Monitoring stations. The major findings with regard to nutrient and sediment fluxes are as follows: (1)WRTDS produced estimates of flux for all combinations that were more accurate, based on reduction in root mean squared error, than flux estimates from ESTIMATOR; (2) for 67 percent of the combinations, WRTDS and ESTIMATOR both produced estimates of flux that were minimally biased compared to observed fluxes(flux bias = tendency to over or underpredict flux observations); however, for 33 percent of the combinations, WRTDS produced estimates of flux that were considerably less biased (by at least 10 percent) than flux estimates from ESTIMATOR; (3) the average percent difference in annual fluxes generated by ESTIMATOR and WRTDS was less than 10 percent at 80 percent of the combinations; and (4) the greatest differences related to flux bias and annual fluxes all occurred for combinations where the pattern in observed concentration-discharge relation was sinuous (two points of inflection) rather than linear or quadratic (zero or one point of inflection). The major findings with regard to trends are as follows: (1) both models produce water-quality trends that have factored in the year-to-year variations in flow; (2) trends in water-quality condition are represented by ESTIMATOR as a trend in flow-adjusted concentration and by WRTDS as a flow normalized flux; (3) for 67 percent of the combinations with trend estimates, the WRTDS trends in flow-normalized flux are in the same direction and magnitude to the ESTIMATOR trends in flow-adjusted concentration, and at the remaining 33 percent the differences in trend magnitude and direction are related to fundamental differences between concentration and flux; and (4) the majority (85 percent) of the total nitrogen, nitrate, and orthophosphorus combinations exhibited long-term (1985 to 2010) trends in WRTDS flow-normalized flux that indicate improvement or reduction in associated flux and the majority (83 percent) of the total phosphorus (from 1985 to 2010) and suspended sediment (from 2001 to 2010) combinations exhibited trends in WRTDS flow-normalized flux that indicate degradation or increases in the flux delivered.

Delaware, Maryland, New York, Pennsylvania, Virgin↗
USGS2004

SAM 2.1—A computer program for plotting and formatting surveying data for estimating peak discharges by the slope-area method

The U.S. Geological Survey (USGS) measures discharge in streams using several methods. However, measurement of peak discharges is often impossible or impractical due to difficult access, inherent danger of making measurements during flood events, and timing often associated with flood events. Thus, many peak discharge values often are calculated after the fact by use of indirect methods. The most common indirect method for estimating peak dis- charges in streams is the slope-area method. This, like other indirect methods, requires measuring the flood profile through detailed surveys. Processing the survey data for efficient entry into computer streamflow models can be time demanding; SAM 2.1 is a program designed to expedite that process. The SAM 2.1 computer program is designed to be run in the field on a portable computer. The program processes digital surveying data obtained from an electronic surveying instrument during slope- area measurements. After all measurements have been completed, the program generates files to be input into the SAC (Slope-Area Computation program; Fulford, 1994) or HEC-RAS (Hydrologic Engineering Center-River Analysis System; Brunner, 2001) computer streamflow models so that an estimate of the peak discharge can be calculated.

Fact Sheet↗
USGS1993

Plans for a sensitivity analysis of bridge-scour computations

Plans for an analysis of the sensitivity of Level 2 bridge-scour computations are described. Cross-section data from 15 bridge sites in Texas are modified to reflect four levels of field effort ranging from no field surveys to complete surveys. Data from United States Geological Survey (USGS) topographic maps will be used to supplement incomplete field surveys. The cross sections are used to compute the water-surface profile through each bridge for several T-year recurrence-interval design discharges. The effect of determining the downstream energy grade-line slope from topographic maps is investigated by systematically varying the starting slope of each profile. The water-surface profile analyses are then used to compute potential scour resulting from each of the design discharges. The planned results will be presented in the form of exceedance-probability versus scour-depth plots with the maximum and minimum scour depths at each T-year discharge presented as error bars.

Conference Paper↗
USGS2013

Geologic map of Chickasaw National Recreation Area, Murray County, Oklahoma

This 1:24,000-scale geologic map is a compilation of previous geologic maps and new geologic mapping of areas in and around Chickasaw National Recreation Area. The geologic map includes revisions of numerous unit contacts and faults and a number of previously “undifferentiated” rock units were subdivided in some areas. Numerous circular-shaped hills in and around Chickasaw National Recreation Area are probably the result of karst-related collapse and may represent the erosional remnants of large, exhumed sinkholes. Geospatial registration of existing, smaller scale (1:72,000- and 1:100,000-scale) geologic maps of the area and construction of an accurate Geographic Information System (GIS) database preceded 2 years of fieldwork wherein previously mapped geology (unit contacts and faults) was verified and new geologic mapping was carried out. The geologic map of Chickasaw National Recreation Area and this pamphlet include information pertaining to how the geologic units and structural features in the map area relate to the formation of the northern Arbuckle Mountains and its Arbuckle-Simpson aquifer. The development of an accurate geospatial GIS database and the use of a handheld computer in the field greatly increased both the accuracy and efficiency in producing the 1:24,000-scale geologic map.

Oklahoma↗
USGS1997

GeoChange Global Change Data

GeoChange is an online data system providing access to research results and data generated by the U.S. Geological Survey's Global Change Research Program. Researchers in this program study climate history and the causes of climatic variations, as well as providing baseline data sets on contemporary atmospheric chemistry, high-resolution meteorology, and dust deposition. Research results are packaged as data sets, groups of digital files containing scientific observations, documentation, and interpretation. The data sets are arranged in a consistent manner using standard file formats so that users of a variety of computer systems can access and use them.

Fact Sheet↗
USGS1984

Geohydrologic conditions in the Vekol Valley, Pinal and Maricopa Counties, Arizona-1983

Vekol Valley is a north-trending valley in south-central Arizona. The valley includes 270 mi 2 and is bounded by the Table Top and Vekol Mountains on the east, the Sand Tank and Maricopa Mountains and the White Hills on the west, and the Both and Haley Hills on the north. The climate is semiarid and precipitation occurs as local summer thunderstorms and regional winter storms. The average annual precipitation is 7 to 8 in., and the potential evaporation rate is about 10 times that of the average annual rainfall (Sells and Hill, 1974, p. 7, 44). Storm runoff occurs mainly as sheetflow and floods of short duration. Although some runoff is diverted into catchment tanks for use by livestock, runoff is not used for irrigation or public supply. Vekol Valley is underlain by a thick sequence of basin sediments, sedimentary rocks, and volcanic rocks. The surrounding mountains are composed of crystalline and volcanic rocks, which also underlie the basin sediments to form the sides and bottom of the basin. The valley is divided into a northern part and a southern part by a bedrock outcrop of crystalline rocks between the White Hills on the west and the Table Top Mountains on the east (R. P. Wilson, 1979, p. 8). The northern part is about 90 mi 2 (J. R. Marie and K. J. Hollett, U.S. Geological Survey, written commun., 1984) and the southern part is about 180 mi 2 . The hydrologic data on which this map is based are available, for the most part, in computer-printout form and may be consulted at the Arizona Department of Water Resources, 99 East Virginia, Phoenix, and the U.S. Geological Survey offices in: Federal Building, 301 West Congress Street, Tucson , and 3788 North 16th Street, Suite E, Phoenix. Material from which copies can be made at private expense is available at the Tuscon and Phoenix offices of the U.S. Geological Survey.

Arizona↗
USGS2022

Dynamic rating method for computing discharge from time-series stage data

Ratings are used for a variety of reasons in water-resources investigations. The simplest rating relates discharge to the stage of the river. From a pure hydrodynamics perspective, all rivers and streams have some form of hysteresis in the relation between stage and discharge because of unsteady flow as a flood wave passes. Simple ratings are unable to represent hysteresis in a stage/discharge relation. A dynamic rating method is capable of capturing hysteresis owing to the variable energy slope caused by unsteady momentum and pressure. A dynamic rating method developed to compute discharge from stage for compact channel geometry, referred to as DYNMOD, previously has been developed through a simplification of the one-dimensional Saint-Venant equations. A dynamic rating method, which accommodates compound and compact channel geometry, referred to as DYNPOUND, has been developed through a similar simplification as a part of this study. The DYNMOD and DYNPOUND methods were implemented in the Python programming language. Discharge time series computed with the dynamic rating method implementations were then compared to simulated discharge time series and discrete discharge measurements made at U.S. Geological Survey streamgage sites. Four sets of stage and discharge time series were created using one-dimensional unsteady simulation software with compound channel geometry to compare the results of both dynamic rating methods to results from the full one-dimensional shallow water equations. Discharge time series were computed from stage time series using DYNMOD and DYNPOUND. DYNPOUND outperformed DYNMOD in all four scenarios. The minimum and maximum mean squared logarithmic error (MSLE) for the DYNMOD results were 2.75×10 −2 and 3.40×10 −2 , respectively. The minimum and maximum MSLE for the DYNPOUND results were 2.51×10 −7 and 1.91×10 −4 , respectively. The dynamic rating methods were calibrated for six U.S. Geological Survey streamgage sites using observed discharge data collected at the sites. The calibration objective for each site was to minimize the MSLE of the discharge computed with the rating method with respect to observed discharge. For each site, the calibration included all field measurements within a selected water year. The DYNMOD method failed to compute discharge for the full calibration time series for three sites. A method fails to compute when the implementation returns a nonfinite value at a time step. Because the values computed for following time steps are dependent on the previous time step, a nonfinite value results in nonfinite values that follow. For the three sites for which DYNMOD computed the complete discharge time series, the minimum MSLE for calibration was 2.19×10 −3 and the maximum was 9.77×10 −3 . The MSLE of the DYNPOUND computed discharge calibration time series for the six sites ranged from 3.70×10 −3 to 1.25. For each site, an event-based time period was selected to compare the discharge time series computed with the dynamic rating methods to discrete discharge field measurements made at the streamgage sites. The DYNMOD-computed discharge time series for the three sites had an MSLE range of 2.76×10 −3 to 3.14×10 −2 . The range of MSLE for the six DYNPOUND sites was 3.64×10 −3 to 7.23×10 −2 . Although the DYNMOD method outperforms the DYNPOUND method when calibrated streamgage sites are under consideration, the DYNMOD method failed to compute a discharge time series at three of the six sites. The DYNPOUND method, therefore, was more robust than the DYNMOD method. Improvements to the implementation of the DYNPOUND method may improve the accuracy of the method.

Open-File Report↗
USGS2010

Low-flow frequency and flow duration of selected South Carolina streams in the Broad River basin through March 2008

In 2008, the U.S. Geological Survey, in cooperation with the South Carolina Department of Health and Environmental Control, initiated a study to update low-flow statistics at continuous-record streamgaging stations operated by the U.S. Geological Survey in South Carolina. This report presents the low-flow statistics for 23 selected streamgaging stations in the Broad River basin in South Carolina, and includes flow durations of 5-, 10-, 25-, 50-, 75-, 90-, and 95-percent probability of exceedance and the annual minimum 1-, 3-, 7-, 14-, 30-, 60-, and 90-day mean flows with recurrence intervals of 2, 5, 10, 20, 30, and 50 years, depending on the length of record available at the streamgaging station. The low-flow statistics were computed from records available through March 31, 2008. In addition, flow duration information is presented for one streamgaging station 021556525, Pacolet River below Lake Blalock near Cowpens, SC, where recurrence interval computations were not appropriate. Of the 23 streamgaging stations for which recurrence interval computations were made, 14 had low-flow statistics that were published in previous U.S. Geological Survey reports. A comparison of the low-flow statistics for the minimum mean flow for a 7-consecutive-day period with a 10-year recurrence interval (7Q10) from this study with the most recently published values indicated that 8 of the 14 streamgaging stations had values that were within plus or minus 25 percent of the previous value. Ten of the 14 streamgaging stations had negative percent differences indicating the low-flow statistic had decreased since the previous study, and 4 streamgaging stations had positive percent differences indicating that the low-flow statistic had increased since the previous study. The low-flow statistics are influenced by length of record, hydrologic regime under which the record was collected, techniques used to do the analysis, and other changes, such as urbanization, diversions, and so on, that may have occurred in the basin.

South Carolina↗
USGS2010

A geostatistical approach to mapping site response spectral amplifications

If quantitative estimates of the seismic properties do not exist at a location of interest then the site response spectral amplifications must be estimated from data collected at other locations. Currently, the most common approach employs correlations of site class with maps of surficial geology. Analogously, correlations of site class with topographic slope can be employed where the surficial geology is unknown. Our goal is to identify and validate a method to estimate site response with greater spatial resolution and accuracy for regions where additional effort is warranted. This method consists of three components: region-specific data collection, a spatial model for interpolating seismic properties, and a theoretical method for computing spectral amplifications from the interpolated seismic properties. We consider three spatial interpolation schemes: correlations with surficial geology, termed the geologic trend (GT), ordinary kriging (OK), and kriging with a trend (KT). We estimate the spectral amplifications from seismic properties using the square root of impedance method, thereby linking the frequency-dependent spectral amplifications to the depth-dependent seismic properties. Thus, the range of periods for which this method is applicable is limited by the depth of exploration. A dense survey of near-surface S-wave slowness (Ss) throughout Kobe, Japan shows that the geostatistical methods give more accurate estimates of Ss than the topographic slope and GT methods, and the OK and KT methods perform equally well. We prefer the KT model because it can be seamlessly integrated with geologic maps that cover larger regions. Empirical spectral amplifications show that the region-specific data achieve more accurate estimates of observed median short-period amplifications than the topographic slope method. ?? 2010 Elsevier B.V.

Engineering Geology↗
USGS2003

Probabilistic assessment methodology for continuous-type petroleum accumulations

The analytic resource assessment method, called ACCESS (Analytic Cell-based Continuous Energy Spreadsheet System), was developed to calculate estimates of petroleum resources for the geologic assessment model, called FORSPAN, in continuous-type petroleum accumulations. The ACCESS method is based upon mathematical equations derived from probability theory in the form of a computer spreadsheet system. ?? 2003 Elsevier B.V. All rights reserved.

International Journal of Coal Geology↗
USGS2024

Improved computational methods for probabilistic liquefaction hazard analysis

Current procedures for analysis of and design against liquefaction hazards focus primarily on the use of probabilistic ground motions at a single ground-shaking hazard level, with the cyclic loading represented by a peak ground acceleration ( PGA ) corresponding to a target return period and a single representative moment magnitude M w . These parameters are typically used in conjunction with deterministic simplified procedures for estimating liquefaction triggering and consequences that largely neglect the considerable uncertainties inherent to liquefaction problems. Motivated by these limitations and the resulting inconsistencies in liquefaction design levels, early methods for probabilistic liquefaction hazard analysis (PLHA) were proposed that incorporate the full ground motion hazard space, integrated with probabilistic liquefaction triggering models. Such methods provide liquefaction factor of safety ( FS L ) hazard curves for standard penetration test (SPT) data. Recognizing the increased use of higher-resolution cone penetrometer test (CPT) data in engineering analysis and design and the potential computational challenges it presents, an expanded suite of probabilistic triggering models, and wider availability of more detailed seismic hazard data, an improved PLHA computational methodology is presented in this study. The methods described utilize the U.S. Geological Survey National Seismic Hazard Model directly through web services to obtain PGA hazard and disaggregation calculations for any site and average shear wave velocity in the upper 30 m of the site ( V s 30 ) in the conterminous United States, to reconstruct the PGA hazard space for use in PLHA calculations, and to employ array calculations for efficient liquefaction hazard curve estimates for the thousands of CPT measurements in a given profile. The framework presented here is modular in nature, and discussion on the use of alternative models and extension to probabilistic liquefaction consequence evaluation is presented. The importance of appropriate representation of probabilistic liquefaction model uncertainties is also highlighted, along with the impacts of different levels of uncertainty on the PLHA calculation. Finally, a potential roadmap for incorporation of the PLHA framework in seismic provisions is presented, with an illustration of how it can address current limitations and impacts in liquefaction hazard analysis and design.

Soil Dynamics and Earthquake Engineering↗
USGS1979

Digital image processing system For Landsat 3

The Department of Interior (DOI) and the National Aeronautics and Space Administration (NASA) have entered into a joint program to provide a digital image processing system in support of the Landsat 3 mission. NASA will provide the data reception and pre-processing facilities, while the DOI provides the production image processing system that generates film products and computer compatible tapes for users. The system procured by the DOI's U.S. Geological Survey was installed at the Earth Resources Observation System Data Center (EDC) in Sioux Falls, South Dakota. The EDC Digital Image Processing System (EDIPS) is capable of operating in standard or special formats. During 13 hours of operation, the system can process up to 200 five-band Multispectral Scanner (MSS) scenes and 160 Return Beam Vidicon (RBV) subscenes in the standard mode plus up to 60 scenes/subscenes in the special-order mode. The input media for the system are High Density Tapes (HDT's) generated by NASA's Goddard Space Flight Center (GSFC). These tapes contain two types of data: those that have been radiometrically and geometrically corrected with resampling of the data to fit a known map projection, and those that have been radiometrically corrected but have not been geometrically corrected or resampled. The system can provide 185 mm (MSS) and 198 mm (RBV) black and white film products for each MSS band or RBV subscene via a high resolution laser beam recorder. The CCT's generated by the system are compatible with the HDT format, and are available either in Band Sequential (BSQ) or Band Interleaved by Line (BIL) data. This paper will present both an overview of the total NASA/DOI system and a detailed discussion of the EDC Digital Image Processing System that is installed at the USGS facility in Sioux Falls, South Dakota.

South Dakota↗
USGS2008

Streamflow characteristics of streams in the Helmand Basin, Afghanistan

A majority of the Afghan population lacks adequate and safe supplies of water because of contamination, lack of water-resources management regulation, and lack of basic infrastructure, compounded by periods of drought and seasonal flooding. Characteristics of historical streamflows are needed to assist with efforts to quantify the water resources of the Helmand Basin. The Helmand Basin is the largest river basin in Afghanistan. It comprises the southern half of the country, draining waters from the Sia Koh Mountains in Herat Province to the eastern mountains in Gardez Province (currently known as the Paktia Province) and the Parwan Mountains northwest of Kabul, and finally draining into the unique Sistan depression between Iran and Afghanistan (Favre and Kamal, 2004). The Helmand Basin is a desert environment with rivers fed by melting snow from the high mountains and infrequent storms. Great fluctuations in streamflow, from flood to drought, can occur annually. Knowledge of the magnitude and time distribution of streamflow is needed to quantify water resources and for water management and environmental planning. Agencies responsible for the development and management of Afghanistan's surface-water resources can use this knowledge for making safe, economical, and environmentally sound water-resource planning decisions. To provide the Afghan managers with necessary streamflow information, the U.S. Geological Survey (USGS), in cooperation with the U.S. Agency for International Development (USAID), computed streamflow statistics for data collected at historical gaging stations within the Helmand Basin. The historical gaging stations used are shown in figure 1 and listed in table 1.

Helmand Basin↗
USGS2010

Real Time Flood Alert System (RTFAS) for Puerto Rico

The Real Time Flood Alert System is a web-based computer program, developed as a data integration tool, and designed to increase the ability of emergency managers to rapidly and accurately predict flooding conditions of streams in Puerto Rico. The system includes software and a relational database to determine the spatial and temporal distribution of rainfall, water levels in streams and reservoirs, and associated storms to determine hazardous and potential flood conditions. The computer program was developed as part of a cooperative agreement between the U.S. Geological Survey Caribbean Water Science Center and the Puerto Rico Emergency Management Agency, and integrates information collected and processed by these two agencies and the National Weather Service.

Fact Sheet↗
USGS2010

Simulation of Streamflow, Evapotranspiration, and Groundwater Recharge in the Lower San Antonio River Watershed, South-Central Texas, 2000-2007

The U.S. Geological Survey (USGS), in cooperation with the San Antonio River Authority, the Evergreen Underground Water Conservation District, and the Goliad County Groundwater Conservation District, configured, calibrated, and tested a watershed model for a study area consisting of about 2,150 square miles of the lower San Antonio River watershed in Bexar, Guadalupe, Wilson, Karnes, DeWitt, Goliad, Victoria, and Refugio Counties in south-central Texas. The model simulates streamflow, evapotranspiration (ET), and groundwater recharge using rainfall, potential ET, and upstream discharge data obtained from National Weather Service meteorological stations and USGS streamflow-gaging stations. Additional time-series inputs to the model include wastewater treatment-plant discharges, withdrawals for cropland irrigation, and estimated inflows from springs. Model simulations of streamflow, ET, and groundwater recharge were done for 2000-2007. Because of the complexity of the study area, the lower San Antonio River watershed was divided into four subwatersheds; separate HSPF models were developed for each subwatershed. Simulation of the overall study area involved running simulations of the three upstream models, then running the downstream model. The surficial geology was simplified as nine contiguous water-budget zones to meet model computational limitations and also to define zones for which ET, recharge, and other water-budget information would be output by the model. The model was calibrated and tested using streamflow data from 10 streamflow-gaging stations; additionally, simulated ET was compared with measured ET from a meteorological station west of the study area. The model calibration is considered very good; streamflow volumes were calibrated to within 10 percent of measured streamflow volumes. During 2000-2007, the estimated annual mean rainfall for the water-budget zones ranged from 33.7 to 38.5 inches per year; the estimated annual mean rainfall for the entire watershed was 34.3 inches. Using the HSPF model it was estimated that for 2000-2007, less than 10 percent of the annual mean rainfall on the study watershed exited the watershed as streamflow, whereas about 82 percent, or an average of 28.2 inches per year, exited the watershed as ET. Estimated annual mean groundwater recharge for the entire study area was 3.0 inches, or about 9 percent of annual mean rainfall. Estimated annual mean recharge was largest in water-budget zone 3, the zone where the Carrizo Sand outcrops. In water-budget zone 3, the estimated annual mean recharge was 5.1 inches or about 15 percent of annual mean rainfall. Estimated annual mean recharge was smallest in water-budget zone 6, about 1.1 inches or about 3 percent of annual mean rainfall. The Cibolo Creek subwatershed and the subwatershed of the San Antonio River upstream from Cibolo Creek had the largest and smallest basin yields, about 4.8 inches and 1.2 inches, respectively. Estimated annual ET and annual recharge generally increased with increasing annual rainfall. Also, ET was larger in zones 8 and 9, the most downstream zones in the watershed. Model limitations include possible errors related to model conceptualization and parameter variability, lack of data to quantify certain model inputs, and measurement errors. Uncertainty regarding the degree to which available rainfall data represent actual rainfall is potentially the most serious source of measurement error.

Open-File Report↗
USGS2012

Automated delineation and characterization of watersheds for more than 3,000 surface-water-quality monitoring stations active in 2010 in Texas

The U.S. Geological Survey (USGS), in cooperation with the Texas Commission on Environmental Quality, developed computer scripts and applications to automate the delineation of watershed boundaries and compute watershed characteristics for more than 3,000 surface-water-quality monitoring stations in Texas that were active during 2010. Microsoft Visual Basic applications were developed using ArcGIS ArcObjects to format the source input data required to delineate watershed boundaries. Several automated scripts and tools were developed or used to calculate watershed characteristics using Python, Microsoft Visual Basic, and the RivEX tool. Automated methods were augmented by the use of manual methods, including those done using ArcMap software. Watershed boundaries delineated for the monitoring stations are limited to the extent of the Subbasin boundaries in the USGS Watershed Boundary Dataset, which may not include the total watershed boundary from the monitoring station to the headwaters.

Texas↗
USGS1989

Review of edgematchimg procedures for digital cartographic data used in Geographic Information Systems (GIS)

In the process of developing a continuous hydrographic data layer for water resources applications in the Pacific Northwest, map-edge discontinuities in the U.S. Geological Survey 1:100 ,000-scale digital data that required application of computer-assisted edgematching procedures were identified. The spatial data sets required by the project must have line features that match closely enough across map boundaries to ensure full line topology when adjacent files are joined by the computer. Automated edgematching techniques are evaluated as to their effects on positional accuracy. Interactive methods such as selective node-matching and on-screen editing are also reviewed. Interactive procedures complement automated methods by allowing supervision of edgematching in a cartographic and hydrologic context. Common edge conditions encountered in the preparation of the Northwest Rivers data base are described, as are recommended processing solutions. Suggested edgematching procedures for 1:100,000-scale hydrography data are included in an appendix to encourage consistent processing of this theme on a national scale. (USGS)

Open-File Report↗