USGS Science⌕ Search

Geology topics

Gary D. Tasker

Publications and source records attributed to Gary D. Tasker.

At least 37 records · Page 2Linked to original sources
USGS2000

Estimating magnitude and frequency of peak discharges for rural, unregulated, streams in West Virginia

Multiple and simple least-squares regression models for the log10-transformed 100-year discharge with independent variables describing the basin characteristics (log10-transformed and untransformed) for 267 streamflow-gaging stations were evaluated, and the regression residuals were plotted as areal distributions that defined three regions of the State, designated East, North, and South. Exploratory data analysis procedures identified 31 gaging stations at which discharges are different than would be expected for West Virginia. Regional equations for the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year peak discharges were determined by generalized least-squares regression using data from 236 gaging stations. Log10-transformed drainage area was the most significant independent variable for all regions.Equations developed in this study are applicable only to rural, unregulated, streams within the boundaries of West Virginia. The accuracy of estimating equations is quantified by measuring the average prediction error (from 27.7 to 44.7 percent) and equivalent years of record (from 1.6 to 20.0 years).

Water-Resources Investigations Report↗
USGS1999

Notes on numerical reliability of several statistical analysis programs

This report presents a benchmark analysis of several statistical analysis programs currently in use in the USGS. The benchmark consists of a comparison between the values provided by a statistical analysis program for variables in the reference data set ANASTY and their known or calculated theoretical values. The ANASTY data set is an amendment of the Wilkinson NASTY data set that has been used in the statistical literature to assess the reliability (computational correctness) of calculated analytical results.

Open-File Report↗
USGS1999

Estimating the magnitude and frequency of floods in rural basins of North Carolina

A statewide study was conducted to develop two methods for estimating the magnitude and frequency of floods in rural ungaged basins in North Carolina. Flood-frequency estimates for gaged sites in North Carolina were computed by fitting the annual peak flows for each site to a log-Pearson Type III distribution. As part of the computation of flood-frequency estimates for gaged sites, new values for generalized skew coefficients were developed. Basin characteristics for these gaged sites were computed by using a geographic information system and automated computer algorithms. Flood-frequency estimates and basin characteristics for 317 gaged sites were combined to form the data base that was used for this analysis. Regional regression analysis, using generalized least-squares regression, was used to develop a set of predictive equations that can be used to estimate the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence interval discharges for rural ungaged basins in the Blue Ridge-Piedmont, Coastal Plain, and Sand Hills hydrologic areas. The predictive equations are all functions of drainage area. Average errors of prediction for these regression equations range from 36 to 65 percent. A region-of-influence method also was developed that interactively estimates recurrence interval discharges for rural ungaged basins in the Blue Ridge-Piedmont and Coastal Plain hydrologic areas of North Carolina. Regression techniques are used to develop a unique relation between flood discharge and basin characteristics for a subset of gaged sites with similar basin characteristics. This, then, can be used to estimate flood discharges at ungaged sites. Because the computations required for this method are somewhat complex, a computer application was developed that performs the computations and compares the predictive errors for this method. The computer application also includes the option of using the regression equations to compute estimated flood discharges and errors of prediction specific to each ungaged site. Root mean square errors, computed for each recurrence interval and hydrologic area, are generally only slightly lower for the region-of-influence method than for the regression equations and do not provide sufficient basis for recommending one method over the other. In addition, the region-of-influence method is a new method that is still being improved. As a result, the regional regression equations are considered to be the primary method for computing flood-frequency estimates at ungaged sites.

North Carolina↗
USGS1996

Computer model of Raritan River Basin water-supply system in central New Jersey

This report describes a computer model of the Raritan River Basin water-supply system in central New Jersey. The computer model provides a technical basis for evaluating the effects of alternative patterns of operation of the Raritan River Basin water-supply system during extended periods of below-average precipitation. The computer model is a continuity-accounting model consisting of a series of interconnected nodes. At each node, the inflow volume, outflow volume, and change in storage are determined and recorded for each month. The model runs with a given set of operating rules and water-use requirements including releases, pumpages, and diversions. The model can be used to assess the hypothetical performance of the Raritan River Basin water- supply system in past years under alternative sets of operating rules. It also can be used to forecast the likelihood of specified outcomes, such as the depletion of reservoir contents below a specified threshold or of streamflows below statutory minimum passing flows, for a period of up to 12 months. The model was constructed on the basis of current reservoir capacities and the natural, unregulated monthly runoff values recorded at U.S. Geological Survey streamflow- gaging stations in the basin.

Open-File Report↗
USGS1995

Magnitude and frequency of floods in Arkansas

Methods are presented for estimating the magnitude and frequency of peak discharges of streams in Arkansas. Regression analyses were developed in which a stream's physical and flood characteristics were related. Four sets of regional regression equations were derived to predict peak discharges with selected recurrence intervals of 2, 5, 10, 25, 50, 100, and 500 years on streams draining less than 7,770 square kilometers. The regression analyses indicate that size of drainage area, main channel slope, mean basin elevation, and the basin shape factor were the most significant basin characteristics that affect magnitude and frequency of floods. The region of influence method is included in this report. This method is still being improved and is to be considered only as a second alternative to the standard method of producing regional regression equations. This method estimates unique regression equations for each recurrence interval for each ungaged site. The regression analyses indicate that size of drainage area, main channel slope, mean annual precipitation, mean basin elevation, and the basin shape factor were the most significant basin and climatic characteristics that affect magnitude and frequency of floods for this method. Certain recommendations on the use of this method are provided. A method is described for estimating the magnitude and frequency of peak discharges of streams for urban areas in Arkansas. The method is from a nationwide U.S. Geeological Survey flood frequency report which uses urban basin characteristics combined with rural discharges to estimate urban discharges. Annual peak discharges from 204 gaging stations, with drainage areas less than 7,770 square kilometers and at least 10 years of unregulated record, were used in the analysis. These data provide the basis for this analysis and are published in the Appendix of this report as supplemental data. Large rivers such as the Red, Arkansas, White, Black, St. Francis, Mississippi, and Ouachita Rivers have floodflow characteristics that differ from those of smaller tributary streams and were treated individually. Regional regression equations are not applicable to these large rivers. The magnitude and frequency of floods along these rivers are based on specific station data. This section is provided in the Appendix and has not been updated since the last Arkansas flood frequency report (1987b), but is included at the request of the cooperator.

Water-Resources Investigations Report↗
USGS1994

Sensitivity of water resources in the Delaware River basin to climate variability and change

Because of the greenhouse effect, projected increases in atmospheric carbon dioxide levels might cause global warming, which in turn could result in changes in precipitation patterns and evapotranspiration and in increases in sea level. This report describes the greenhouse effect; discusses the problems and uncertainties associated with the detection, prediction, and effects of climate change; and presents the results of sensitivity analyses of how climate change might affect water resources in the Delaware River basin. Sensitivity analyses suggest that potentially serious shortfalls of certain water resources in the basin could result if some scenarios for climate change come true . The results of model simulations of the basin streamflow demonstrate the difficulty in distinguishing the effects that climate change versus natural climate variability have on streamflow and water supply . The future direction of basin changes in most water resources, furthermore, cannot be precisely determined because of uncertainty in current projections of regional temperature and precipitation . This large uncertainty indicates that, for resource planning, information defining the sensitivities of water resources to a range of climate change is most relevant . The sensitivity analyses could be useful in developing contingency plans for evaluating and responding to changes, should they occur.

Water Supply Paper↗
USGS1993

Sensitivity of water resources in the Delaware River basin to climate variability and change

Because of the "greenhouse effect," projected increases in atmospheric carbon dioxide levels might cause global warming, which in turn could result in changes in precipitation patterns and evapotranspiration and in increases in sea level. This report describes the greenhouse effect; discusses the problems and uncertainties associated with the detection, prediction, and effects of climatic change, and presents the results of sensitivity-analysis studies of the potential effects of climate change on water resources in the Delaware River basin. On the basis of sensitivity analyses, potentially serious shortfalls of certain water resources in the basin could result if some climatic-change scenarios become true. The results of basin streamflow-model simulations in this study demonstrate the difficulty in distinguishing effects of climatic change on streamflow and water supply from effects of natural variability in current climate. The future direction of basin changes in most water resources, furthermore, cannot be determined precisely because of uncertainty in current projections of regional temperature and precipitation. This large uncertainty indicates that, for resource planning, information defining the sensitivities of water resources to a range of climate change is most relevant. The sensitivity analyses could be useful in developing contingency plans on how to evaluate and respond to changes, should they occur.

Delaware;New Jersey;Pennsylvania↗
USGS1993

Effects of climate change on drought risks in the Apalachicola, Chattahoochee, and Flint River basin

Possible effects of climate change on the Apalachicola-Chattahoochee-Flint (ACF) River basin is simulated with a computer model. Model inputs are monthly temperature and precipitation that simulate several possible climate change scenarios. Preliminary results for climate scenarios based on output for three popular general circulation models indicate that lower flows will occur more frequently if the regional climate warms and monthly precipitation decreases during critical summer months.

Conference Paper↗
USGS1990

Techniques for estimation of storm-runoff loads, volumes, and selected constituent concentrations in urban watersheds in the United States

Urban planners and managers need information on the quantity of precipitation and the quality and quantity of run off in their cities and towns if they are to adequately plan for the effects of storm runoff from urban areas. As a result of this need, four sets of linear regression models were developed for estimating storm-runoff constituent loads, storm-runoff volumes, storm-runoff mean concentrations of constituents, and mean seasonal or mean annual constituent loads from physical, land-use, and climatic characteristics of urban watersheds in the United States. Thirty-four regression models of storm-runoff constituent loads and storm-runoff volumes were developed, and 31 models of storm-runoff mean concentrations were developed . Ten models of mean seasonal or mean annual constituent loads were developed by analyzing long-term storm-rainfall records using at-site linear regression models. Three statistically different regions, delineated on the basis of mean annual rainfall, were used to improve linear regression models where adequate data were available . Multiple regression analyses, including ordinary least squares and generalized least squares, were used to determine the optimum linear regression models . These models can be used to estimate storm-runoff constituent loads, storm-runoff volumes, storm-runoff mean concentrations of constituents, and mean seasonal or mean annual constituent loads at gaged and ungaged urban watersheds. The most significant explanatory variables in all linear regression models were total storm rainfall and total contributing drainage area. Impervious area, land-use, and mean annual climatic characteristics also were significant in some models. Models for estimating loads of dissolved solids, total nitrogen, and total ammonia plus organic nitrogen as nitrogen generally were the most accurate, whereas models for suspended solids were the least accurate. The most accurate models were those for application in the more arid Western States, and the least accurate models were those for areas that had large mean annual rainfall.

Water Supply Paper↗
USGS1990

Some hydrological impacts of climate change for the Delaware River Basin

To gain insight into possible impacts of climate change on water availability in the Delaware River, two models are linked. The first model is a monthly water balance model that converts the temperature and precipitation values generated by a random number generator to monthly streamflow values. The monthly streamflow values are input to a second model that simulates the operation of reservoirs and diversions within the basin. The output for the two linked models consists of time series of reservoir levels and streamflow at key points in the basin. Model results for a base case, in which monthly temperature and precipitation statistics are unchanged from historical records, are compared to several changed-climate scenarios under a standard set of rules of operation.

Conference Paper↗
USGS1989

An operational GLS model for hydrologic regression

Recent Monte Carlo studies have documented the value of generalized least squares (GLS) procedures to estimate empirical relationships between streamflow statistics and physiographic basin characteristics. This paper presents a number of extensions of the GLS method that deal with realities and complexities of regional hydrologic data sets that were not addressed in the simulation studies. These extensions include: (1) a more realistic model of the underlying model errors; (2) smoothed estimates of cross correlation of flows; (3) procedures for including historical flow data; (4) diagnostic statistics describing leverage and influence for GLS regression; and (5) the formulation of a mathematical program for evaluating future gaging activities.

Journal of Hydrology↗
USGS1988

Estimation of urban stormwater quality

Two data-based methods for estimating urban stormwater quality have recently been made available - a planning level method developed by the U.S. Environmental Protection Agency (EPA), and a nationwide regression method developed by the U.S. Geological Survey. Each method uses urban stormwater water-quality constituent data collected for the Nationwide Urban Runoff Program (NURP) during 1979-83. The constituents analyzed include 10 chemical constituents - chemical oxygen demand (COD), total suspended solids (TSS), dissolved solids (DS), total nitrogen (TN), total ammonia plus nitrogen (AN), total phosphorus (TP), dissolved phosphorous (DP), total copper (CU), total lead (PB), and total zinc (ZN). The purpose of this report is to briefly compare features of the two estimation methods.

Conference Paper↗
USGS1987

Regional regression of flood characteristics employing historical information

Streamflow gauging networks provide hydrologic information for use in estimating the parameters of regional regression models. The regional regression models can be used to estimate flood statistics, such as the 100 yr peak, at ungauged sites as functions of drainage basin characteristics. A recent innovation in regional regression is the use of a generalized least squares (GLS) estimator that accounts for unequal station record lengths and sample cross correlation among the flows. However, this technique does not account for historical flood information. A method is proposed here to adjust this generalized least squares estimator to account for possible information about historical floods available at some stations in a region. The historical information is assumed to be in the form of observations of all peaks above a threshold during a long period outside the systematic record period. A Monte Carlo simulation experiment was performed to compare the GLS estimator adjusted for historical floods with the unadjusted GLS estimator and the ordinary least squares estimator. Results indicate that using the GLS estimator adjusted for historical information significantly improves the regression model.

Journal of Hydrology↗
USGS1987

Analysis of surface-water data network in Kansas for effectiveness in providing regional streamflow information; with a section on theory and application of generalized least squares

This report documents the results of an analysis of the surface-water data network in Kansas for its effectiveness in providing regional streamflow information. The network was analyzed using generalized least squares regression. The correlation and time-sampling error of the streamflow characteristic are considered in the generalized least squares method. Unregulated medium-, low-, and high-flow characteristics were selected to be representative of the regional information that can be obtained from streamflow-gaging-station records for use in evaluating the effectiveness of continuing the present network stations, discontinuing some stations, and (or) adding new stations. The analysis used streamflow records for all currently operated stations that were not affected by regulation and for discontinued stations for which unregulated flow characteristics, as well as physical and climatic characteristics, were available. The State was divided into three network areas, western, northeastern, and southeastern Kansas, and analysis was made for the three streamflow characteristics in each area, using three planning horizons. The analysis showed that the maximum reduction of sampling mean-square error for each cost level could be obtained by adding new stations and discontinuing some current network stations. Large reductions in sampling mean-square error for low-flow information could be achieved in all three network areas, the reduction in western Kansas being the most dramatic. The addition of new stations would be most beneficial for mean-flow information in western Kansas. The reduction of sampling mean-square error for high-flow information would benefit most from the addition of new stations in western Kansas. Southeastern Kansas showed the smallest error reduction in high-flow information. A comparison among all three network areas indicated that funding resources could be most effectively used by discontinuing more stations in northeastern and southeastern Kansas and establishing more new stations in western Kansas.

Water Supply Paper↗
USGS1985

Analysis of surface-water data network in Kansas for effectiveness in providing regional streamflow information

The surface water data network in Kansas was analyzed using generalized least squares regression for its effectiveness in providing regional streamflow information. The correlation and time-sampling error of the streamflow characteristic are considered in the generalized least squares method. Unregulated medium-flow, low-flow and high-flow characteristics were selected to be representative of the regional information that can be obtained from streamflow gaging station records for use in evaluating the effectiveness of continuing the present network stations, discontinuing some stations; and/or adding new stations. The analysis used streamflow records for all currently operated stations that were not affected by regulation and discontinued stations for which unregulated flow characteristics, as well as physical and climatic characteristics, were available. The state was divided into three network areas, western, northeastern, and southeastern Kansas, and analysis was made for three streamflow characteristics in each area, using three planning horizons. The analysis showed that the maximum reduction of sampling mean square error for each cost level could be obtained by adding new stations and discontinuing some of the present network stations. Large reductions in sampling mean square error for low-flow information could be accomplished in all three network areas, with western Kansas having the most dramatic reduction. The addition of new stations would be most beneficial for man-flow information in western Kansas, and to lesser degrees in the other two areas. The reduction of sampling mean square error for high-flow information would benefit most from the addition of new stations in western Kansas, and the effect diminishes to lesser degrees in the other two areas. Southeastern Kansas showed the smallest error reduction in high-flow information. A comparison among all three network areas indicated that funding resources could be most effectively used by discontinuing more stations in northeastern and southeastern Kansas and establishing more new stations in western Kansas. (Author's abstract)

Kansas↗
USGS1983

Effective record length for the T-year event

The effect of serial dependence on the reliability of an estimate of the T -yr. event is of importance in hydrology because design decisions are based upon the estimate. In this paper the reliability of estimates of the T -yr. event from two common distributions is given as a function of number of observations and lag-one serial correlation coefficient for T = 2, 10, 20, 50, and 100 yr. A lag-one autoregressive model is assumed with either a normal or Pearson Type-III disturbance term. Results indicate that, if observations are serially correlated, the effective record length should be used to estimate the discharge associated with the expected exceedance probability.

Journal of Hydrology↗