Geology topics

Audrey L. Ishii

Publications and source records attributed to Audrey L. Ishii.

9 recordsLinked to original sources

USGS2019

Full Equations Model Graphical Data Inspector (FEQ–GDI) user guide

The Full Equations Model Graphical Data Inspector (FEQ–GDI) is a menu-driven utility program that enables users to visualize and check the geometric and hydraulic properties of channel cross sections, selected control structures, and stream profiles in the input files for the Full Equations (FEQ) Model and the Full Equations Utilities (FEQUTL) Model. The FEQ Model is a computer program for the simulation of one-dimensional, unsteady flow in open channels and through control structures using the full, dynamic equations of motion. The input to FEQ Model includes the output from the FEQUTL Model, which computes tables relating the hydraulic properties of channel cross sections and control structures to depth, flow, and (or) other specified parameters. FEQ–GDI can be used to help users quickly detect anomalies in the data that may indicate errors in the input files.

Open-File Report↗

USGS2016

Estimation of peak discharge quantiles for selected annual exceedance probabilities in northeastern Illinois

This report provides two sets of equations for estimating peak discharge quantiles at annual exceedance probabilities (AEPs) of 0.50, 0.20, 0.10, 0.04, 0.02, 0.01, 0.005, and 0.002 (recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively) for watersheds in Illinois based on annual maximum peak discharge data from 117 watersheds in and near northeastern Illinois. One set of equations was developed through a temporal analysis with a two-step least squares-quantile regression technique that measures the average effect of changes in the urbanization of the watersheds used in the study. The resulting equations can be used to adjust rural peak discharge quantiles for the effect of urbanization, and in this study the equations also were used to adjust the annual maximum peak discharges from the study watersheds to 2010 urbanization conditions. The other set of equations was developed by a spatial analysis. This analysis used generalized least-squares regression to fit the peak discharge quantiles computed from the urbanization-adjusted annual maximum peak discharges from the study watersheds to drainage-basin characteristics. The peak discharge quantiles were computed by using the Expected Moments Algorithm following the removal of potentially influential low floods defined by a multiple Grubbs-Beck test. To improve the quantile estimates, regional skew coefficients were obtained from a newly developed regional skew model in which the skew increases with the urbanized land use fraction. The skew coefficient values for each streamgage were then computed as the variance-weighted average of at-site and regional skew coefficients. The drainage-basin characteristics used as explanatory variables in the spatial analysis include drainage area, the fraction of developed land, the fraction of land with poorly drained soils or likely water, and the basin slope estimated as the ratio of the basin relief to basin perimeter. This report also provides the following: (1) examples to illustrate the use of the spatial and urbanization-adjustment equations for estimating peak discharge quantiles at ungaged sites and to improve flood-quantile estimates at and near a gaged site; (2) the urbanization-adjusted annual maximum peak discharges and peak discharge quantile estimates at streamgages from 181 watersheds including the 117 study watersheds and 64 additional watersheds in the study region that were originally considered for use in the study but later deemed to be redundant. The urbanization-adjustment equations, spatial regression equations, and peak discharge quantile estimates developed in this study will be made available in the web application StreamStats, which provides automated regression-equation solutions for user-selected stream locations. Figures and tables comparing the observed and urbanization-adjusted annual maximum peak discharge records by streamgage are provided at https://doi.org/10.3133/sir20165050 for download.

Illinois↗

USGS2010

Development and analysis of a meteorological database, Argonne National Laboratory, Illinois

A database of hourly values of air temperature, dewpoint temperature, wind speed, and solar radiation from January 1, 1948, to September 30, 2003, primarily using data collected at the Argonne National Laboratory station, was developed for use in continuous-time hydrologic modeling in northeastern Illinois. Missing and apparently erroneous data values were replaced with adjusted values from nearby stations used as 'backup'. Temporal variations in the statistical properties of the data resulting from changes in measurement and data-storage methodologies were adjusted to match the statistical properties resulting from the data-collection procedures that have been in place since January 1, 1989. The adjustments were computed based on the regressions between the primary data series from Argonne National Laboratory and the backup series using data obtained during common periods; the statistical properties of the regressions were used to assign estimated standard errors to values that were adjusted or filled from other series. Each hourly value was assigned a corresponding data-source flag that indicates the source of the value and its transformations. An analysis of the data-source flags indicates that all the series in the database except dewpoint have a similar fraction of Argonne National Laboratory data, with about 89 percent for the entire period, about 86 percent from 1949 through 1988, and about 98 percent from 1989 through 2003. The dewpoint series, for which observations at Argonne National Laboratory did not begin until 1958, has only about 71 percent Argonne National Laboratory data for the entire period, about 63 percent from 1948 through 1988, and about 93 percent from 1989 through 2003, indicating a lower reliability of the dewpoint sensor. A basic statistical analysis of the filled and adjusted data series in the database, and a series of potential evapotranspiration computed from them using the computer program LXPET (Lamoreux Potential Evapotranspiration) also was carried out. This analysis indicates annual cycles in solar radiation and potential evapotranspiration that follow the annual cycle of extraterrestrial solar radiation, whereas temperature and dewpoint annual cycles are lagged by about 1 month relative to the solar cycle. The annual cycle of wind has a late summer minimum, and spring and fall maximums. At the annual time scale, the filled and adjusted data series and computed potential evapotranspiration have significant serial correlation and possibly have significant temporal trends. The inter-annual fluctuations of temperature and dewpoint are weakest, whereas those of wind and potential evapotranspiration are strongest.

Open-File Report↗

USGS2010

Implementation and Evaluation of the Streamflow Statistics (StreamStats) Web Application for Computing Basin Characteristics and Flood Peaks in Illinois

Illinois StreamStats (ILSS) is a Web-based application for computing selected basin characteristics and flood-peak quantiles based on the most recently (2010) published (Soong and others, 2004) regional flood-frequency equations at any rural stream location in Illinois. Limited streamflow statistics including general statistics, flow durations, and base flows also are available for U.S. Geological Survey (USGS) streamflow-gaging stations. ILSS can be accessed on the Web at http://streamstats.usgs.gov/ by selecting the State Applications hyperlink and choosing Illinois from the pull-down menu. ILSS was implemented for Illinois by obtaining and projecting ancillary geographic information system (GIS) coverages; populating the StreamStats database with streamflow-gaging station data; hydroprocessing the 30-meter digital elevation model (DEM) for Illinois to conform to streams represented in the National Hydrographic Dataset 1:100,000 stream coverage; and customizing the Web-based Extensible Markup Language (XML) programs for computing basin characteristics for Illinois. The basin characteristics computed by ILSS then were compared to the basin characteristics used in the published study, and adjustments were applied to the XML algorithms for slope and basin length. Testing of ILSS was accomplished by comparing flood quantiles computed by ILSS at a an approximately random sample of 170 streamflow-gaging stations computed by ILSS with the published flood quantile estimates. Differences between the log-transformed flood quantiles were not statistically significant at the 95-percent confidence level for the State as a whole, nor by the regions determined by each equation, except for region 1, in the northwest corner of the State. In region 1, the average difference in flood quantile estimates ranged from 3.76 percent for the 2-year flood quantile to 4.27 percent for the 500-year flood quantile. The total number of stations in region 1 was small (21) and the mean difference is not large (less than one-tenth of the average prediction error for the regression-equation estimates). The sensitivity of the flood-quantile estimates to differences in the computed basin characteristics are determined and presented in tables. A test of usage consistency was conducted by having at least 7 new users compute flood quantile estimates at 27 locations. The average maximum deviation of the estimate from the mode value at each site was 1.31 percent after four mislocated sites were removed. A comparison of manual 100-year flood-quantile computations with ILSS at 34 sites indicated no statistically significant difference. ILSS appears to be an accurate, reliable, and effective tool for flood-quantile estimates.

Scientific Investigations Report↗

USGS2006

Watershed Data Management (WDM) Database for Salt Creek Streamflow Simulation, DuPage County, Illinois

The U.S. Geological Survey (USGS), in cooperation with DuPage County Department of Engineering, Stormwater Management Division, maintains a database of hourly meteorologic and hydrologic data for use in a near real-time streamflow simulation system, which assists in the management and operation of reservoirs and other flood-control structures in the Salt Creek watershed in DuPage County, Illinois. The majority of the precipitation data are collected from a tipping-bucket rain-gage network located in and near DuPage County. The other meteorologic data (wind speed, solar radiation, air temperature, and dewpoint temperature) are collected at Argonne National Laboratory in Argonne, Illinois. Potential evapotranspiration is computed from the meteorologic data. The hydrologic data (discharge and stage) are collected at USGS streamflow-gaging stations in DuPage County. These data are stored in a Watershed Data Management (WDM) database. This report describes a version of the WDM database that was quality-assured and quality-controlled annually to ensure the datasets were complete and accurate. This version of the WDM database contains data from January 1, 1997, through September 30, 2004, and is named SEP04.WDM. This report provides a record of time periods of poor data for each precipitation dataset and describes methods used to estimate the data for the periods when data were missing, flawed, or snowfall-affected. The precipitation dataset data-filling process was changed in 2001, and both processes are described. The other meteorologic and hydrologic datasets in the database are fully described in the annual U.S. Geological Survey Water Data Report for Illinois and, therefore, are described in less detail than the precipitation datasets in this report.

Open-File Report↗

USGS2004

Estimating flood-peak discharge magnitudes and frequencies for rural streams in Illinois

Flood-peak discharge magnitudes and frequencies at streamflow-gaging sites were developed with the annual maximum series (AMS) and the partial duration series (PDS) in this study. Regional equations for both flood series were developed for estimating flood-peak discharge magnitudes at specified recurrence intervals of rural Illinois streams. The regional equations are techniques for estimating flood quantiles at ungaged sites or for improving estimated flood quantiles at gaged sites with short records or unrepresentative data. Besides updating at-site floodfrequency estimates using flood data up to water year 1999, this study updated the generalized skew coefficients for Illinois to be used with the Log-Pearson III probability distribution for analyzing the AMS, developed a program for analyzing the partial duration series with the Generalized Pareto probability distribution, and applied the BASINSOFT program with digital datasets in soil, topography, land cover, and precipitation to develop a set of basin characteristics. The multiple regression analysis was used to develop the regional equations with subsets of the basin characteristics and the updated at-site flood frequencies. Seven hydrologic regions were delineated using physiographic and hydrologic characteristics of drainage basins of Illinois. The seven hydrologic regions were used for both the AMS and PDS analyses. Examples are presented to illustrate the use of the AMS regional equations to estimate flood quantiles at an ungaged site and to improve flood-quantile estimates at and near a gaged site. Flood-quantile estimates in four regulated channel reaches of Illinois also are approximated by linear interpolation. Documentation of the flood data preparation and evaluation, procedures for determining the flood quantiles, basin characteristics, generalized skew coefficients, hydrologic region delineations, and the multiple regression analyses used to determine the regional equations are presented in the main text and appendixes.

Illinois↗

USGS1996

Implementation and verification of a one-dimensional, unsteady-flow model for Spring Brook near Warrenville, Illinois

A model based on de Sant-Venant equations for dynamic flow in open channels was calibrated and verified for a 0.75-mile urbanized reach of Spring Brook, a tributary to the West Branch Du Page River. The model was used to simulate flow in the reach, which passes through two short culverts, one with overbank flow during periods of high flow. Stage and discharge data were collected at 10 sites with the study reach during three high-flow periods. Simulated stages and discharges were compared graphically to field-collected data. Errors in simulated stage and discharge were small except when debris, not represented in the model, clogged the culvert.

Water Supply Paper↗

USGS1996

Verification of a one-dimensional, unsteady-flow model for the Fox River in Illinois

The previously-calibrated application of the Full EQuations (FEQ) model of one-dimensional, unsteady flow to a 30.7-mile reach of the Fox River in northeastern Illinois was verified with discharge, stage, and dye-transport data collected during a 12-day period in October-November 1990. The period included unsteady flow induced by the operation of a sluice gate dam located at the upstream end of the reach. The model flow field was input to the Branched Lagrangian Transport Model (BLTM) for the simulation of dye transport. The results of the FEQ and BLTM model simulations are compared with the measured data and sensitivity analyses of the model parameters for this application are presented.

Water Supply Paper↗

USGS1986

RAINFALL-LOSS PARAMETER ESTIMATION FOR ILLINOIS.

The U. S. Geological Survey is currently conducting an investigation to estimate values of parameters for two rainfall-loss computation methods used in a commonly used flood-hydrograph model. Estimates of six rainfall-loss parameters are required: four for the Exponential Loss-Rate method and two for the Initial and Uniform Loss-Rate method. Multiple regression analyses on calibrated data from 616 storms at 98 gaged basins are being used to develop parameter-estimating techniques for these six parameters at ungaged basins in Illinois. Parameter-estimating techniques are being verified using data from a total of 105 storms at 35 uncalibrated gaged basins.

Conference Paper↗