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At least 19 recordsLinked to original sources
USGS2012

Regional regression models of watershed suspended-sediment discharge for the eastern United States

Estimates of mean annual watershed sediment discharge, derived from long-term measurements of suspended-sediment concentration and streamflow, often are not available at locations of interest. The goal of this study was to develop multivariate regression models to enable prediction of mean annual suspended-sediment discharge from available basin characteristics useful for most ungaged river locations in the eastern United States. The models are based on long-term mean sediment discharge estimates and explanatory variables obtained from a combined dataset of 1201 US Geological Survey (USGS) stations derived from a SPAtially Referenced Regression on Watershed attributes (SPARROW) study and the Geospatial Attributes of Gages for Evaluating Streamflow (GAGES) database. The resulting regional regression models summarized for major US water resources regions 1–8, exhibited prediction R 2 values ranging from 76.9% to 92.7% and corresponding average model prediction errors ranging from 56.5% to 124.3%. Results from cross-validation experiments suggest that a majority of the models will perform similarly to calibration runs. The 36-parameter regional regression models also outperformed a 16-parameter national SPARROW model of suspended-sediment discharge and indicate that mean annual sediment loads in the eastern United States generally correlates with a combination of basin area, land use patterns, seasonal precipitation, soil composition, hydrologic modification, and to a lesser extent, topography.

Journal of Hydrologic Engineering↗
USGS1996

Upscaled soil-water retention using van Genuchten's function

Soils are often layered at scales smaller than the block size used in numerical and conceptual models of variably saturated flow. Consequently, the small-scale variability in water content within each block must be homogenized (upscaled). Laboratory results have shown that a linear volume average (LVA) of water content at a uniform suction is a good approximation to measured water contents in heterogeneous cores. Here, we upscale water contents using van Genuchten's function for both the local and upscaled soil-water-retention characteristics. The van Genuchten (vG) function compares favorably with LVA results, laboratory experiments under hydrostatic conditions in 3-cm cores, and numerical simulations of large-scale gravity drainage. Our method yields upscaled vG parameter values by fitting the vG curve to the LVA of water contents at various suction values. In practice, it is more efficient to compute direct averages of the local vG parameter values. Nonlinear power averages quantify a feasible range of values for each upscaled vG shape parameter; upscaled values of N are consistently less than the harmonic means, reflecting broad pore-size distributions of the upscaled soils. The vG function is useful for modeling soil-water retention at large scales, and these results provide guidance for its application.

Journal of Hydrologic Engineering↗
USGS1997

Application of two direct runoff prediction methods in Puerto Rico

Two methods for predicting direct runoff from rainfall data were applied to several basins and the resulting hydrographs compared to measured values. The first method uses a geomorphology-based unit hydrograph to predict direct runoff through its convolution with the excess rainfall hyetograph. The second method shows how the resulting hydraulic routing flow equation from a kinematic wave approximation is solved using a spectral method based on the matrix representation of the spatial derivative with Chebyshev collocation and a fourth-order Runge-Kutta time discretization scheme. The calibrated Green-Ampt (GA) infiltration parameters are obtained by minimizing the sum, over several rainfall events, of absolute differences between the total excess rainfall volume computed from the GA equations and the total direct runoff volume computed from a hydrograph separation technique. The improvement made in predicting direct runoff using a geomorphology-based unit hydrograph with the ephemeral and perennial stream network instead of the strictly perennial stream network is negligible. The hydraulic routing scheme presented here is highly accurate in predicting the magnitude and time of the hydrograph peak although the much faster unit hydrograph method also yields reasonable results.

Journal of Hydrologic Engineering↗
USGS1998

Estimating ice-affected streamflow by extended Kalman filtering

An extended Kalman filter was developed to automate the real-time estimation of ice-affected streamflow on the basis of routine measurements of stream stage and air temperature and on the relation between stage and streamflow during open-water (ice-free) conditions. The filter accommodates three dynamic modes of ice effects: sudden formation/ablation, stable ice conditions, and eventual elimination. The utility of the filter was evaluated by applying it to historical data from two long-term streamflow-gauging stations, St. John River at Dickey, Maine and Platte River at North Bend, Nebr. Results indicate that the filter was stable and that parameters converged for both stations, producing streamflow estimates that are highly correlated with published values. For the Maine station, logarithms of estimated streamflows are within 8% of the logarithms of published values 87.2% of the time during periods of ice effects and within 15% 96.6% of the time. Similarly, for the Nebraska station, logarithms of estimated streamflows are within 8% of the logarithms of published values 90.7% of the time and within 15% 97.7% of the time. In addition, the correlation between temporal updates and published streamflows on days of direct measurements at the Maine station was 0.777 and 0.998 for ice-affected and open-water periods, respectively; for the Nebraska station, corresponding correlations were 0.864 and 0.997.

Journal of Hydrologic Engineering↗
USGS1999

Geostatistical applications in ground-water modeling in south-central Kansas

This paper emphasizes the supportive role of geostatistics in applying ground-water models. Field data of 1994 ground-water level, bedrock, and saltwater-freshwater interface elevations in south-central Kansas were collected and analyzed using the geostatistical approach. Ordinary kriging was adopted to estimate initial conditions for ground-water levels and topography of the Permian bedrock at the nodes of a finite difference grid used in a three-dimensional numerical model. Cokriging was used to estimate initial conditions for the saltwater-freshwater interface. An assessment of uncertainties in the estimated data is presented. The kriged and cokriged estimation variances were analyzed to evaluate the adequacy of data employed in the modeling. Although water levels and bedrock elevations are well described by spherical semivariogram models, additional data are required for better cokriging estimation of the interface data. The geostatistically analyzed data were employed in a numerical model of the Siefkes site in the project area. Results indicate that the computed chloride concentrations and ground-water drawdowns reproduced the observed data satisfactorily.This paper emphasizes the supportive role of geostatistics in applying ground-water models. Field data of 1994 ground-water level, bedrock, and saltwater-freshwater interface elevations in south-central Kansas were collected and analyzed using the geostatistical approach. Ordinary kriging was adopted to estimate initial conditions for ground-water levels and topography of the Permian bedrock at the nodes of a finite difference grid used in a three-dimensional numerical model. Cokriging was used to estimate initial conditions for the saltwater-freshwater interface. An assessment of uncertainties in the estimated data is presented. The kriged and cokriged estimation variances were analyzed to evaluate the adequacy of data employed in the modeling. Although water levels and bedrock elevations are well described by spherical semivariogram models, additional data are required for better cokriging estimation of the interface data. The geostatistically analyzed data were employed in a numerical model of the Siefkes site in the project area. Results indicate that the computed chloride concentrations and ground-water drawdowns reproduced the observed data satisfactorily.

Journal of Hydrologic Engineering↗
USGS1999

Effects of unsaturated zone on ground-water mounding

The design of infiltration basins used to dispose of treated wastewater or for aquifer recharge often requires estimation of ground-water mounding beneath the basin. However, the effect that the unsaturated zone has on water-table response to basin infiltration often has been overlooked in this estimation. A comparison was made between two methods used to estimate ground-water mounding-an analytical approach that is limited to the saturated zone and a numerical approach that incorporates both the saturated and the unsaturated zones. Results indicate that the error that is introduced by a method that ignores the effects of the unsaturated zone on ground-water mounding increases as the basin-loading period is shortened; as the depth to the water table increases, with increasing subsurface anisotropy; and with the inclusion of fine-textured strata. Additionally, such a method cannot accommodate the dynamic nature of basin infiltration, the finite transmission time of the infiltration front to the water table, or the interception of the basin floor by the capillary fringe.The design of infiltration basins used to dispose of treated wastewater or for aquifer recharge often requires estimation of ground-water mounding beneath the basin. However, the effect that the unsaturated zone has on water-table response to basin infiltration often has been overlooked in this estimation. A comparison was made between two methods used to estimate ground-water mounding - an analytical approach that is limited to the saturated zone and a numerical approach that incorporates both the saturated and the unsaturated zones. Results indicate that the error that is introduced by a method that ignores the effects of the unsaturated zone on ground-water mounding increases as the basin-loading period is shortened; as the depth to the water table increases, with increasing subsurface anisotropy; and with the inclusion of fine-textured strata. Additionally, such a method cannot accommodate the dynamic nature of basin infiltration, the finite transmission time of the infiltration front to the water, or the interception of the basin floor by the capillary fringe.

Journal of Hydrologic Engineering↗
USGS2001

Evaluation of mixed-population flood-frequency analysis

A mixed population of flood flows was shown to cause quality-of-fit problems if a single-population flood-frequency distribution was used to describe the flood data. The three populations in this mix were "ordinary," tropical cyclone, and ice-jam-release floods. Parametric descriptions of the single and separated flood populations were evaluated using probability-plot correlation-coefficient tests. These tests quantified how well the flood-probability distributions agreed with plotting-position descriptions of the data and quantified the differences due to the mixed-population analysis. High outliers caused the high skewness found in the single- population analyses. The tropical cyclone component was underestimated by single-population analyses at gauging stations in Massachusetts that had little data.

Journal of Hydrologic Engineering↗
USGS2001

Estimating equation for mixed populations of floods in Massachusetts

A single equation for estimating the peak flows of annual floods at ungauged sites in Massachusetts was developed by combining the conditional probabilities of floods caused by tropical cyclones and ice-jam releases with the conditional probability of "ordinary" floods. Regression equations for these three flood populations demonstrated that two basin characteristics, drainage-basin area and basin head, and frequency of flooding determined the corresponding peak-flow rates.

Journal of Hydrologic Engineering↗
USGS2001

User interface for ground-water modeling: Arcview extension

Numerical simulation for ground-water modeling often involves handling large input and output data sets. A geographic information system (GIS) provides an integrated platform to manage, analyze, and display disparate data and can greatly facilitate modeling efforts in data compilation, model calibration, and display of model parameters and results. Furthermore, GIS can be used to generate information for decision making through spatial overlay and processing of model results. Arc View is the most widely used Windows-based GIS software that provides a robust user-friendly interface to facilitate data handling and display. An extension is an add-on program to Arc View that provides additional specialized functions. An Arc View interface for the ground-water flow and transport models MODFLOW and MT3D was built as an extension for facilitating modeling. The extension includes preprocessing of spatially distributed (point, line, and polygon) data for model input and postprocessing of model output. An object database is used for linking user dialogs and model input files. The Arc View interface utilizes the capabilities of the 3D Analyst extension. Models can be automatically calibrated through the Arc View interface by external linking to such programs as PEST. The efficient pre- and postprocessing capabilities and calibration link were demonstrated for ground-water modeling in southwest Kansas.

Journal of Hydrologic Engineering↗
USGS2001

Evaluation of flash-flood discharge forecasts in complex terrain using precipitation

Operational prediction of flash floods produced by thunderstorm (convective) precipitation in mountainous areas requires accurate estimates or predictions of the precipitation distribution in space and time. The details of the spatial distribution are especially critical in complex terrain because the watersheds are generally small in size, and small position errors in the forecast or observed placement of the precipitation can distribute the rain over the wrong watershed. In addition to the need for good precipitation estimates and predictions, accurate flood prediction requires a surface-hydrologic model that is capable of predicting stream or river discharge based on the precipitation-rate input data. Different techniques for the estimation and prediction of convective precipitation will be applied to the Buffalo Creek, Colorado flash flood of July 1996, where over 75 mm of rain from a thunderstorm fell on the watershed in less than 1 h. The hydrologic impact of the precipitation was exacerbated by the fact that a significant fraction of the watershed experienced a wildfire approximately two months prior to the rain event. Precipitation estimates from the National Weather Service's operational Weather Surveillance Radar-Doppler 1988 and the National Center for Atmospheric Research S-band, research, dual-polarization radar, colocated to the east of Denver, are compared. In addition, very short range forecasts from a convection-resolving dynamic model, which is initialized variationally using the radar reflectivity and Doppler winds, are compared with forecasts from an automated-algorithmic forecast system that also employs the radar data. The radar estimates of rain rate, and the two forecasting systems that employ the radar data, have degraded accuracy by virtue of the fact that they are applied in complex terrain. Nevertheless, the radar data and forecasts from the dynamic model and the automated algorithm could be operationally useful for input to surface-hydrologic models employed for flood warning. Precipitation data provided by these various techniques at short time scales and at fine spatial resolutions are employed as detailed input to a distributed-parameter hydrologic model for flash-flood prediction and analysis. With the radar-based precipitation estimates employed as input, the simulated flood discharge was similar to that observed. The dynamic-model precipitation forecast showed the most promise in providing a significant discharge-forecast lead time. The algorithmic system's precipitation forecast did not demonstrate as much skill, but the associated discharge forecast would still have been sufficient to have provided an alert of impending flood danger.

Journal of Hydrologic Engineering↗
USGS2002

Dynamic fuzzy modeling of storm water infiltration in urban fractured aquifers

In an urban fractured-rock aquifer in the Mt. Eden area of Auckland, New Zealand, disposal of storm water is via "soakholes" drilled directly into the top of the fractured basalt rock. The dynamic response of the groundwater level due to the storm water infiltration shows characteristics of a strongly time-varying system. A dynamic fuzzy modeling approach, which is based on multiple local models that are weighted using fuzzy membership functions, has been developed to identify and predict groundwater level fluctuations caused by storm water infiltration. The dynamic fuzzy model is initialized by the fuzzy clustering algorithm and optimized by the gradient-descent algorithm in order to effectively derive the multiple local models-each of which is associated with a locally valid model that represents the groundwater level state as a response to different intensities of rainfall events. The results have shown that even if the number of fuzzy local models derived is small, the fuzzy modeling approach developed provides good prediction results despite the highly time-varying nature of this urban fractured-rock aquifer system. Further, it allows interpretable representations of the dynamic behavior of the groundwater system due to storm water infiltration.

Journal of Hydrologic Engineering↗
USGS2003

Vertical velocity variance in the mixed layer from radar wind profilers

Vertical velocity variance data were derived from remotely sensed mixed layer turbulence measurements at the Atmospheric Boundary Layer Experiments (ABLE) facility in Butler County, Kansas. These measurements and associated data were provided by a collection of instruments that included two 915 MHz wind profilers, two radio acoustic sounding systems, and two eddy correlation devices. The data from these devices were available through the Atmospheric Boundary Layer Experiment (ABLE) database operated by Argonne National Laboratory. A signal processing procedure outlined by Angevine et al. was adapted and further built upon to derive vertical velocity variance, w_pm???2, from 915 MHz wind profiler measurements in the mixed layer. The proposed procedure consisted of the application of a height-dependent signal-to-noise ratio (SNR) filter, removal of outliers plus and minus two standard deviations about the mean on the spectral width squared, and removal of the effects of beam broadening and vertical shearing of horizontal winds. The scatter associated with w_pm???2 was mainly affected by the choice of SNR filter cutoff values. Several different sets of cutoff values were considered, and the optimal one was selected which reduced the overall scatter on w_pm???2 and yet retained a sufficient number of data points to average. A similarity relationship of w_pm???2 versus height was established for the mixed layer on the basis of the available data. A strong link between the SNR and growth/decay phases of turbulence was identified. Thus, the mid to late afternoon hours, when strong surface heating occurred, were observed to produce the highest quality signals.

Journal of Hydrologic Engineering↗
USGS2004

Use of qualitative and quantitative information in neural networks for assessing agricultural chemical contamination of domestic wells

A neural network analysis of agrichemical occurrence in groundwater was conducted using data from a pilot study of 192 small-diameter drilled and driven wells and 115 dug and bored wells in Illinois, a regional reconnaissance network of 303 wells across 12 Midwestern states, and a study of 687 domestic wells across Iowa. Potential factors contributing to well contamination (e.g., depth to aquifer material, well depth, and distance to cropland) were investigated. These contributing factors were available in either numeric (actual or categorical) or descriptive (yes or no) format. A method was devised to use the numeric and descriptive values simultaneously. Training of the network was conducted using a standard backpropagation algorithm. Approximately 15% of the data was used for testing. Analysis indicated that training error was quite low for most data. Testing results indicated that it was possible to predict the contamination potential of a well with pesticides. However, predicting the actual level of contamination was more difficult. For pesticide occurrence in drilled and driven wells, the network predictions were good. The performance of the network was poorer for predicting nitrate occurrence in dug and bored wells. Although the data set for Iowa was large, the prediction ability of the trained network was poor, due to descriptive or categorical input parameters, compared with smaller data sets such as that for Illinois, which contained more numeric information.

Journal of Hydrologic Engineering↗
USGS2007

Flood regionalization: A hybrid geographic and predictor-variable region-of-influence regression method

To facilitate estimation of streamflow characteristics at an ungauged site, hydrologists often define a region of influence containing gauged sites hydrologically similar to the estimation site. This region can be defined either in geographic space or in the space of the variables that are used to predict streamflow (predictor variables). These approaches are complementary, and a combination of the two may be superior to either. Here we propose a hybrid region-of-influence (HRoI) regression method that combines the two approaches. The new method was applied with streamflow records from 1,091 gauges in the southeastern United States to estimate the 50-year peak flow (Q50). The HRoI approach yielded lower root-mean-square estimation errors and produced fewer extreme errors than either the predictor-variable or geographic region-of-influence approaches. It is concluded, for Q50 in the study region, that similarity with respect to the basin characteristics considered (area, slope, and annual precipitation) is important, but incomplete, and that the consideration of geographic proximity of stations provides a useful surrogate for characteristics that are not included in the analysis. ?? 2007 ASCE.

Journal of Hydrologic Engineering↗
USGS2008

Coupled semivariogram uncertainty of hydrogeological and geophysical data on capture zone uncertainty analysis

This study investigates capture zone uncertainty that relates to the coupled semivariogram uncertainty of hydrogeological and geophysical data. Semivariogram uncertainty is represented by the uncertainty in structural parameters (range, sill, and nugget). We used the beta distribution function to derive the prior distributions of structural parameters. The probability distributions of structural parameters were further updated through the Bayesian approach with the Gaussian likelihood functions. Cokriging of noncollocated pumping test data and electrical resistivity data was conducted to better estimate hydraulic conductivity through autosemivariograms and pseudo-cross-semivariogram. Sensitivities of capture zone variability with respect to the spatial variability of hydraulic conductivity, porosity and aquifer thickness were analyzed using ANOVA. The proposed methodology was applied to the analysis of capture zone uncertainty at the Chicot aquifer in Southwestern Louisiana, where a regional groundwater flow model was developed. MODFLOW-MODPATH was adopted to delineate the capture zone. The ANOVA results showed that both capture zone area and compactness were sensitive to hydraulic conductivity variation. We concluded that the capture zone uncertainty due to the semivariogram uncertainty is much higher than that due to the kriging uncertainty for given semivariograms. In other words, the sole use of conditional variances of kriging may greatly underestimate the flow response uncertainty. Semivariogram uncertainty should also be taken into account in the uncertainty analysis. ?? 2008 ASCE.

Journal of Hydrologic Engineering↗
USGS2008

Low-Level detections of halogenated volatile organic compounds in groundwater: Use in vulnerability assessments

Concentrations of halogenated volatile organic compounds (VOCs) were determined by gas chromatography (GC) with an electron-capture detector (GC-ECD) and by gas chromatography with mass spectrometry (GC-MS) in 109 groundwater samples from five study areas in the United States. In each case, the untreated water sample was used for drinking-water purposes or was from a monitoring well in an area near a drinking-water source. The minimum detection levels (MDLs) for 25 VOCs that were identified in GC-ECD chromatograms, typically, were two to more than four orders of magnitude below the GC-MS MDLs. At least six halogenated VOCs were detected in all of the water samples analyzed by GC-ECD, although one or more VOCs were detected in only 43% of the water samples analyzed by GC-MS. In nearly all of the samples, VOC concentrations were very low and presented no known health risk. Most of the low-level VOC detections indicated post-1940s recharge, or mixtures of recharge that contained a fraction of post-1940s water. Concentrations of selected halogenated VOCs in groundwater from natural and anthropogenic atmospheric sources were estimated and used to recognize water samples that are being impacted by nonatmospheric sources. A classification is presented to perform vulnerability assessments at the scale of individual wells using the number of halogenated VOC detections and total dissolved VOC concentrations in samples of untreated drinking water. The low-level VOC detections are useful in vulnerability assessments, particularly for samples in which no VOCs are detected by GC-MS analysis.

Journal of Hydrologic Engineering↗
USGS2009

Evaluation of a moderate resolution, satellite-based impervious surface map using an independent, high-resolution validation data set

Given the relatively high cost of mapping impervious surfaces at regional scales, substantial effort is being expended in the development of moderate-resolution, satellite-based methods for estimating impervious surface area (ISA). To rigorously assess the accuracy of these data products high quality, independently derived validation data are needed. High-resolution data were collected across a gradient of development within the Mid-Atlantic region to assess the accuracy of National Land Cover Data (NLCD) Landsat-based ISA estimates. Absolute error (satellite predicted area - "reference area") and relative error [satellite (predicted area - "reference area")/ "reference area"] were calculated for each of 240 sample regions that are each more than 15 Landsat pixels on a side. The ability to compile and examine ancillary data in a geographic information system environment provided for evaluation of both validation and NLCD data and afforded efficient exploration of observed errors. In a minority of cases, errors could be explained by temporal discontinuities between the date of satellite image capture and validation source data in rapidly changing places. In others, errors were created by vegetation cover over impervious surfaces and by other factors that bias the satellite processing algorithms. On average in the Mid-Atlantic region, the NLCD product underestimates ISA by approximately 5%. While the error range varies between 2 and 8%, this underestimation occurs regardless of development intensity. Through such analyses the errors, strengths, and weaknesses of particular satellite products can be explored to suggest appropriate uses for regional, satellite-based data in rapidly developing areas of environmental significance. ?? 2009 ASCE.

Journal of Hydrologic Engineering↗
USGS2010

Effect of historic land cover change on runoff curve number estimation in Iowa

Within three decades of European-descended settlers arriving in Iowa, much of the land cover across the state was transformed from prairie and forest to farmland, patches of forest, and urbanized areas. Between 1832 and 1859, the General Land Office surveyed the state of Iowa to aid in the disbursement of land. In 1875, an illustrated atlas of the State of Iowa was published. Using these two data resources for classifying land cover, the hydrologic impact of the land cover change resulting from the first three decades of settlement is presented in terms of the effect on the area-weighted average curve number, a term commonly used to predict runoff from rainstorms. In the four watersheds studied, the area-weighted average curve number increased by a mean of 16.4 from 61.4 to 77.8 with the greatest magnitude of change occurring in the two western Iowa watersheds as opposed to the two more heavily forested eastern Iowa watersheds.

Iowa↗