Geology Reports⌕ Search

SEARCH · Geology Reports

Results for “Algorithms”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,315 records · Page 73Linked to original sources
USGS2009

Capacitively Coupled Resistivity Survey of Selected Irrigation Canals Within the North Platte River Valley, Western Nebraska and Eastern Wyoming, 2004 and 2007-2009

Due to water resources of portions of the North Platte River basin being designated as over-appropriated by the State of Nebraska Department of Natural Resources (DNR), the North Platte Natural Resources District (NPNRD), in cooperation with the DNR, is developing an Integrated Management Plan (IMP) for groundwater and surface water in the NPNRD. As part of the IMP, a three-dimensional numerical finite difference groundwater-flow model is being developed to evaluate the effectiveness of using leakage of water from selected irrigation canal systems to manage groundwater recharge. To determine the relative leakage potential of the upper 8 m of the selected irrigation canals within the North Platte River valley in western Nebraska and eastern Wyoming, the U.S. Geological Survey performed a land-based capacitively coupled (CC) resistivity survey along nearly 630 km of 13 canals and 2 laterals in 2004 and from 2007 to 2009. These 13 canals were selected from the 27 irrigation canals in the North Platte valley due to their location, size, irrigated area, and relation to the active North Platte valley flood plain and related paleochannels and terrace deposits where most of the saturated thickness in the alluvium exists. The resistivity data were then compared to continuous cores at 62 test holes down to a maximum depth of 8 m. Borehole electrical conductivity (EC) measurements at 36 of those test holes were done to correlate resistivity values with grain sizes in order to determine potential vertical leakage along the canals as recharge to the underlying alluvial aquifer. The data acquired in 2004, as well as the 25 test hole cores from 2004, are presented elsewhere. These data were reprocessed using the same updated processing and inversion algorithms used on the 2007 through 2009 datasets, providing a consistent and complete dataset for all collection periods. Thirty-seven test hole cores and borehole electrical conductivity measurements were acquired based on the 2008 data. This report presents comparisons between the CC resistivity data and results from the 37 test holes and includes all binned and inverted CC resistivity datasets from all four years as well as the EC log data for the 37 test holes acquired in 2008 and 2009. The information gained from these data can help State and local water managers and scientists better understand the characteristics of the shallow subsurface underlying the irrigation canals so that the water resources can be managed more effectively.

Scientific Investigations 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↗
USGS2009

Regression models to estimate real-time concentrations of selected constituents in two tributaries to Lake Houston near Houston, Texas, 2005-07

In December 2005, the U.S. Geological Survey in cooperation with the City of Houston, Texas, began collecting discrete water-quality samples for nutrients, total organic carbon, bacteria (total coliform and Escherichia coli), atrazine, and suspended sediment at two U.S. Geological Survey streamflow-gaging stations upstream from Lake Houston near Houston (08068500 Spring Creek near Spring, Texas, and 08070200 East Fork San Jacinto River near New Caney, Texas). The data from the discrete water-quality samples collected during 2005-07, in conjunction with monitored real-time data already being collected - physical properties (specific conductance, pH, water temperature, turbidity, and dissolved oxygen), streamflow, and rainfall - were used to develop regression models for predicting water-quality constituent concentrations for inflows to Lake Houston. Rainfall data were obtained from a rain gage monitored by Harris County Homeland Security and Emergency Management and colocated with the Spring Creek station. The leaps and bounds algorithm was used to find the best subsets of possible regression models (minimum residual sum of squares for a given number of variables). The potential explanatory or predictive variables included discharge (streamflow), specific conductance, pH, water temperature, turbidity, dissolved oxygen, rainfall, and time (to account for seasonal variations inherent in some water-quality data). The response variables at each site were nitrite plus nitrate nitrogen, total phosphorus, organic carbon, Escherichia coli, atrazine, and suspended sediment. The explanatory variables provide easily measured quantities as a means to estimate concentrations of the various constituents under investigation, with accompanying estimates of measurement uncertainty. Each regression equation can be used to estimate concentrations of a given constituent in real time. In conjunction with estimated concentrations, constituent loads were estimated by multiplying the estimated concentration by the corresponding streamflow and applying the appropriate conversion factor. By computing loads from estimated constituent concentrations, a continuous record of estimated loads can be available for comparison to total maximum daily loads. The regression equations presented in this report are site specific to the Spring Creek and East Fork San Jacinto River streamflow-gaging stations; however, the methods that were developed and documented could be applied to other tributaries to Lake Houston for estimating real-time water-quality data for streams entering Lake Houston.

Scientific Investigations Report↗
USGS2011

Simulation of streamflow in the Pleasant, Narraguagus, Sheepscot, and Royal Rivers, Maine, using watershed models

The U.S. Geological Survey (USGS) began a study in 2008 to investigate anticipated changes in summer streamflows and stream temperatures in four coastal Maine river basins and the potential effects of those changes on populations of endangered Atlantic salmon. To achieve this purpose, it was necessary to characterize the quantity and timing of streamflow in these rivers by developing and evaluating a distributed-parameter watershed model for a part of each river basin by using the USGS Precipitation-Runoff Modeling System (PRMS). The GIS (geographic information system) Weasel, a USGS software application, was used to delineate the four study basins and their many subbasins, and to derive parameters for their geographic features. The models were calibrated using a four-step optimization procedure in which model output was evaluated against four datasets for calibrating solar radiation, potential evapotranspiration, annual and seasonal water balances, and daily streamflows. The calibration procedure involved thousands of model runs that used the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The calibrated watershed models performed satisfactorily, in that Nash-Sutcliffe efficiency (NSE) statistic values for the calibration periods ranged from 0.59 to 0.75 (on a scale of negative infinity to 1) and NSE statistic values for the evaluation periods ranged from 0.55 to 0.73. The calibrated watershed models simulate daily streamflow at many locations in each study basin. These models enable natural resources managers to characterize the timing and amount of streamflow in order to support a variety of water-resources efforts including water-quality calculations, assessments of water use, modeling of population dynamics and migration of Atlantic salmon, modeling and assessment of habitat, and simulation of anticipated changes to streamflow and water temperature resulting from changes forecast for air temperature and precipitation.

Scientific Investigations Report↗
USGS2011

Magnitude and Frequency of Floods for Urban and Small Rural Streams in Georgia, 2008

A study was conducted that updated methods for estimating the magnitude and frequency of floods in ungaged urban basins in Georgia that are not substantially affected by regulation or tidal fluctuations. Annual peak-flow data for urban streams from September 2008 were analyzed for 50 streamgaging stations (streamgages) in Georgia and 6 streamgages on adjacent urban streams in Florida and South Carolina having 10 or more years of data. Flood-frequency estimates were computed for the 56 urban streamgages by fitting logarithms of annual peak flows for each streamgage to a Pearson Type III distribution. Additionally, basin characteristics for the streamgages were computed by using a geographical information system and computer algorithms. Regional regression analysis, using generalized least-squares regression, was used to develop a set of equations for estimating flows with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities for ungaged urban basins in Georgia. In addition to the 56 urban streamgages, 171 rural streamgages were included in the regression analysis to maintain continuity between flood estimates for urban and rural basins as the basin characteristics pertaining to urbanization approach zero. Because 21 of the rural streamgages have drainage areas less than 1 square mile, the set of equations developed for this study can also be used for estimating small ungaged rural streams in Georgia. Flood-frequency estimates and basin characteristics for 227 streamgages were combined to form the final database used in the regional regression analysis. Four hydrologic regions were developed for Georgia. The final equations are functions of drainage area and percentage of impervious area for three of the regions and drainage area, percentage of developed land, and mean basin slope for the fourth region. Average standard errors of prediction for these regression equations range from 20.0 to 74.5 percent.

Georgia↗
USGS2011

Refinement and evaluation of the Massachusetts firm-yield estimator model version 2.0

The firm yield is the maximum average daily withdrawal that can be extracted from a reservoir without risk of failure during an extended drought period. Previously developed procedures for determining the firm yield of a reservoir were refined and applied to 38 reservoir systems in Massachusetts, including 25 single- and multiple-reservoir systems that were examined during previous studies and 13 additional reservoir systems. Changes to the firm-yield model include refinements to the simulation methods and input data, as well as the addition of several scenario-testing capabilities. The simulation procedure was adapted to run at a daily time step over a 44-year simulation period, and daily streamflow and meteorological data were compiled for all the reservoirs for input to the model. Another change to the model-simulation methods is the adjustment of the scaling factor used in estimating groundwater contributions to the reservoir. The scaling factor is used to convert the daily groundwater-flow rate into a volume by multiplying the rate by the length of reservoir shoreline that is hydrologically connected to the aquifer. Previous firm-yield analyses used a constant scaling factor that was estimated from the reservoir surface area at full pool. The use of a constant scaling factor caused groundwater flows during periods when the reservoir stage was very low to be overestimated. The constant groundwater scaling factor used in previous analyses was replaced with a variable scaling factor that is based on daily reservoir stage. This change reduced instability in the groundwater-flow algorithms and produced more realistic groundwater-flow contributions during periods of low storage. Uncertainty in the firm-yield model arises from many sources, including errors in input data. The sensitivity of the model to uncertainty in streamflow input data and uncertainty in the stage-storage relation was examined. A series of Monte Carlo simulations were performed on 22 reservoirs to assess the sensitivity of firm-yield estimates to errors in daily-streamflow input data. Results of the Monte Carlo simulations indicate that underestimation in the lowest stream inflows can cause firm yields to be underestimated by an average of 1 to 10 percent. Errors in the stage-storage relation can arise when the point density of bathymetric survey measurements is too low. Existing bathymetric surfaces were resampled using hypothetical transects of varying patterns and point densities in order to quantify the uncertainty in stage-storage relations. Reservoir-volume calculations and resulting firm yields were accurate to within 5 percent when point densities were greater than 20 points per acre of reservoir surface. Methods for incorporating summer water-demand-reduction scenarios into the firm-yield model were developed as well as the ability to relax the no-fail reliability criterion. Although the original firm-yield model allowed monthly reservoir releases to be specified, there have been no previous studies examining the feasibility of controlled releases for downstream flows from Massachusetts reservoirs. Two controlled-release scenarios were tested—with and without a summer water-demand-reduction scenario—for a scenario with a no-fail criterion and a scenario that allows for a 1-percent failure rate over the entire simulation period. Based on these scenarios, about one-third of the reservoir systems were able to support the flow-release scenarios at their 2000–2004 usage rates. Reservoirs with higher storage ratios (reservoir storage capacity to mean annual streamflow) and lower demand ratios (mean annual water demand to annual firm yield) were capable of higher downstream release rates. For the purposes of this research, all reservoir systems were assumed to have structures which enable controlled releases, although this assumption may not be true for many of the reservoirs studied.

Massachusetts↗
USGS2012

Predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwestern United States

The National Water-Quality Assessment (NAWQA) Program of the U.S. Geological Survey (USGS) is conducting a regional analysis of water quality in the principal aquifer systems across the United States. The Southwest Principal Aquifers (SWPA) study is building a better understanding of the susceptibility and vulnerability of basin-fill aquifers in the region to groundwater contamination by synthesizing baseline knowledge of groundwater-quality conditions in 16 basins previously studied by the NAWQA Program. The improved understanding of aquifer susceptibility and vulnerability to contamination is assisting in the development of tools that water managers can use to assess and protect the quality of groundwater resources. Human-health concerns and economic considerations associated with meeting drinking-water standards motivated a study of the vulnerability of basin-fill aquifers to nitrate con­tamination and arsenic enrichment in the southwestern United States. Statistical models were developed by using the random forest classifier algorithm to predict concentrations of nitrate and arsenic across a model grid that represents about 190,600 square miles of basin-fill aquifers in parts of Arizona, California, Colorado, Nevada, New Mexico, and Utah. The statistical models, referred to as classifiers, reflect natural and human-related factors that affect aquifer vulnerability to contamina­tion and relate nitrate and arsenic concentrations to explana­tory variables representing local- and basin-scale measures of source, aquifer susceptibility, and geochemical conditions. The classifiers were unbiased and fit the observed data well, and misclassifications were primarily due to statistical sampling error in the training datasets. The classifiers were designed to predict concentrations to be in one of six classes for nitrate, and one of seven classes for arsenic. Each classification scheme allowed for identification of areas with concentrations that were equal to or exceeding the U.S. Environmental Protection Agency drinking-water standard. Whereas 2.4 percent of the area underlain by basin-fill aquifers in the study area was predicted to equal or exceed this standard for nitrate (10 milligrams per liter as N; mg/L), 42.7 percent was predicted to equal or exceed the standard for arsenic (10 micrograms per liter; μg/L). Areas predicted to equal or exceed the drinking-water standard for nitrate include basins in central Arizona near Phoenix; the San Joaquin, Inland, and San Jacinto basins of California; and the San Luis Valley of Colorado. Much of the area predicted to equal or exceed the drinking-water standard for arsenic is within a belt of basins along the western portion of the Basin and Range Physiographic Province in Nevada, California, and Arizona. Predicted nitrate and arsenic concentrations are substantially lower than the drinking-water standards in much of the study area—about 93.0 percent of the area underlain by basin-fill aquifers was less than one-half the standard for nitrate (5.0 mg/L), and 50.2 percent was less than one-half the standard for arsenic (5.0 μg/L).

Arizona, California, Colorado, Nevada, New Mexico,↗
USGS2012

Development and application of a groundwater/surface-water flow model using MODFLOW-NWT for the Upper Fox River Basin, southeastern Wisconsin

The Fox River is a 199-mile-long tributary to the Illinois River within the Mississippi River Basin in the states of Wisconsin and Illinois. For the purposes of this study the Upper Fox River Basin is defined as the topographic basin that extends from the upstream boundary of the Fox River Basin to a large wetland complex in south-central Waukesha County called the Vernon Marsh. The objectives for the study are to (1) develop a baseline study of groundwater conditions and groundwater/surface-water interactions in the shallow aquifer system of the Upper Fox River Basin, (2) develop a tool for evaluating possible alternative water-supply options for communities in Waukesha County, and (3) contribute to the methodology of groundwater-flow modeling by applying the recently published U.S. Geological Survey MODFLOW-NWT computer code, (a Newton formulation of MODFLOW-2005 intended for solving difficulties involving drying and rewetting nonlinearities of the unconfined groundwater-flow equation) to overcome computational problems connected with fine-scaled simulation of shallow aquifer systems by means of thin model layers. To simulate groundwater conditions, a MODFLOW grid is constructed with thin layers and small cell dimensions (125 feet per side). This nonlinear unconfined problem incorporates the streamflow/lake (SFR/LAK) packages to represent groundwater/surface-water interactions, which yields an unstable solution sensitive to initial conditions when solved using the Picard-based preconditioned-gradient (PCG2) solver. A particular problem is the presence of many isolated wet water-table cells over dry cells, causing the simulated water table to assume unrealistically high values. Attempts to work around the problem by converting to confined conditions or converting active to inactive cells introduce unacceptable bias. Application of MODFLOW-NWT overcomes numerical problem by smoothing the transition from wet to dry cells and keeps all cells active. The simulation is insensitive to initial conditions and the water-table trend is smooth across layers. The MODFLOW-NWT code permits rigorous calibration and also robust application of the model to transient scenarios. Runtimes on a 64-bit computer are kept reasonably short by use of updated initial conditions and informed choices of solver parameters. The shallow aquifer system consists of unconsolidated material of varying thickness over Silurian dolomite. The unconsolidated material, largely of glacial origin, contains fine-textured and coarse-textured deposits that vary in permeability over short distances. This study at least partly encompasses the inevitable uncertainty in the hydraulic conductivity zones by developing two models—one favors the continuity of fine-grained deposits and a second favors the continuity of coarse-grained deposits. The separate calibration processes for the fine-favored and coarse-favored models using MODFLOW-NWT and the nonlinear regression algorithms in the parameter estimation (PEST) code produce distinct parameter values for hydraulic conductivity zones, storage parameters, and streambed conductance zones. Both models are applied to a hypothetical scenario involving 27 "riparian" wells completed adjacent to the river channel and open to the shallow aquifer systems along a 10-mile stretch of the Fox River. The results suggest that a riparian well system withdrawing about 9 million gallons per day would induce about one-third to one-half its total discharge from the river, and that this riverbank inducement would appreciably limit drawdown around the hypothetical wells.

Wisconsin↗
USGS2012

Magnitude of flood flows for selected annual exceedance probabilities in Rhode Island through 2010

Heavy persistent rains from late February through March 2010 caused severe widespread flooding in Rhode Island that set or nearly set record flows and water levels at many long-term streamgages in the State. In response, the U.S. Geological Survey, in partnership with the Federal Emergency Management Agency, conducted a study to update estimates of flood magnitudes at streamgages and regional equations for estimating flood flows at ungaged locations. This report provides information needed for flood plain management, transportation infrastructure design, flood insurance studies, and other purposes that can help minimize future flood damages and risks. The magnitudes of floods were determined from the annual peak flows at 43 streamgages in Rhode Island (20 sites), Connecticut (14 sites), and Massachusetts (9 sites) using the standard Bulletin 17B log-Pearson type III method and a modification of this method called the expected moments algorithm (EMA) for 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probability (AEP) floods. Annual-peak flows were analyzed for the period of record through the 2010 water year; however, records were extended at 23 streamgages using the maintenance of variance extension (MOVE) procedure to best represent the longest period possible for determining the generalized skew and flood magnitudes. Generalized least square regression equations were developed from the flood quantiles computed at 41 streamgages (2 streamgages in Rhode Island with reported flood quantiles were not used in the regional regression because of regulation or redundancy) and their respective basin characteristics to estimate magnitude of floods at ungaged sites. Of 55 basin characteristics evaluated as potential explanatory variables, 3 were statistically significant—drainage area, stream density, and basin storage. The pseudo-coefficient of determination (pseudo- R2 ) indicates these three explanatory variables explain 95 to 96 percent of the variance in the flood magnitudes from 20- to 0.2-percent AEPs. Estimates of uncertainty of the at-site and regression flood magnitudes are provided and were combined with their respective estimated flood quantiles to improve estimates of flood flows at streamgages. This region has a long history of urban development, which is considered to have an important effect on flood flows. This study includes basins that have an impervious area ranging from 0.5 to 37 percent. Although imperviousness provided some explanatory power in the regression, it was not statistically significant at the 95-percent confidence level for any of the AEPs examined. Influence of urbanization on flood flows indicates a complex interaction with other characteristics that confounds a statistical explanation of its effects. Standard methods for calculating magnitude of floods for given AEP are based on the assumption of stationarity, that is, the annual peak flows exhibit no significant trend over time. A subset of 16 streamgages with 70 or more years of unregulated systematic record indicates all but 4 streamgages have a statistically significant positive trend at the 95-percent confidence level; three of these are statistically significant at about the 90-percent confidence level or above. If the trend continues linearly in time, the estimated magnitude of floods for any AEP, on average, will increase by 6, 13, and 21 percent in 10, 20, and 30 years' time, respectively. In 2010, new peaks of record were set at 18 of the 21 active streamgages in Rhode Island. The updated flood frequency analysis indicates the peaks at these streamgages ranged from 2- to 0.2-percent AEP. Many streamgages in the State peaked at a 0.5- and 0.2-percent AEP, except for streamgages in the Blackstone River Basin, which peaked from a 4- to 2-percent AEP.

Rhode Island↗
USGS2012

Methods for determining magnitude and frequency of floods in California, based on data through water year 2006

Methods for estimating the magnitude and frequency of floods in California that are not substantially affected by regulation or diversions have been updated. Annual peak-flow data through water year 2006 were analyzed for 771 streamflow-gaging stations (streamgages) in California having 10 or more years of data. Flood-frequency estimates were computed for the streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to logarithms of annual peak flows for each streamgage. Low-outlier and historic information were incorporated into the flood-frequency analysis, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low outliers. Special methods for fitting the distribution were developed for streamgages in the desert region in southeastern California. Additionally, basin characteristics for the streamgages were computed by using a geographical information system. Regional regression analysis, using generalized least squares regression, was used to develop a set of equations for estimating flows with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities for ungaged basins in California that are outside of the southeastern desert region. Flood-frequency estimates and basin characteristics for 630 streamgages were combined to form the final database used in the regional regression analysis. Five hydrologic regions were developed for the area of California outside of the desert region. The final regional regression equations are functions of drainage area and mean annual precipitation for four of the five regions. In one region, the Sierra Nevada region, the final equations are functions of drainage area, mean basin elevation, and mean annual precipitation. Average standard errors of prediction for the regression equations in all five regions range from 42.7 to 161.9 percent. For the desert region of California, an analysis of 33 streamgages was used to develop regional estimates of all three parameters (mean, standard deviation, and skew) of the log-Pearson Type III distribution. The regional estimates were then used to develop a set of equations for estimating flows with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities for ungaged basins. The final regional regression equations are functions of drainage area. Average standard errors of prediction for these regression equations range from 214.2 to 856.2 percent. Annual peak-flow data through water year 2006 were analyzed for eight streamgages in California having 10 or more years of data considered to be affected by urbanization. Flood-frequency estimates were computed for the urban streamgages by fitting a Pearson Type III distribution to logarithms of annual peak flows for each streamgage. Regression analysis could not be used to develop flood-frequency estimation equations for urban streams because of the limited number of sites. Flood-frequency estimates for the eight urban sites were graphically compared to flood-frequency estimates for 630 non-urban sites. The regression equations developed from this study will be incorporated into the U.S. Geological Survey (USGS) StreamStats program. The StreamStats program is a Web-based application that provides streamflow statistics and basin characteristics for USGS streamgages and ungaged sites of interest. StreamStats can also compute basin characteristics and provide estimates of streamflow statistics for ungaged sites when users select the location of a site along any stream in California.

California↗
USGS2013

Investigations of groundwater system and simulation of regional groundwater flow for North Penn Area 7 Superfund site, Montgomery County, Pennsylvania

Groundwater in the vicinity of several industrial facilities in Upper Gwynedd Township and vicinity, Montgomery County, in southeast Pennsylvania has been shown to be contaminated with volatile organic compounds (VOCs), the most common of which is the solvent trichloroethylene (TCE). The 2-square-mile area was placed on the National Priorities List as the North Penn Area 7 Superfund site by the U.S. Environmental Protection Agency (USEPA) in 1989. The U.S. Geological Survey (USGS) conducted geophysical logging, aquifer testing, and water-level monitoring, and measured streamflows in and near North Penn Area 7 from fall 2000 through fall 2006 in a technical assistance study for the USEPA to develop an understanding of the hydrogeologic framework in the area as part of the USEPA Remedial Investigation. In addition, the USGS developed a groundwater-flow computer model based on the hydrogeologic framework to simulate regional groundwater flow and to estimate directions of groundwater flow and pathways of groundwater contaminants. The study area is underlain by Triassic- and Jurassic-age sandstones and shales of the Lockatong Formation and Brunswick Group in the Mesozoic Newark Basin. Regionally, these rocks strike northeast and dip to the northwest. The sequence of rocks form a fractured-sedimentary-rock aquifer that acts as a set of confined to partially confined layers of differing permeabilities. Depth to competent bedrock typically is less than 20 ft below land surface. The aquifer layers are recharged locally by precipitation and discharge locally to streams. The general configuration of the potentiometric surface in the aquifer is similar to topography, except in areas affected by pumping. The headwaters of Wissahickon Creek are nearby, and the stream flows southwest, parallel to strike, to bisect North Penn Area 7. Groundwater is pumped in the vicinity of North Penn Area 7 for industrial use, public supply, and residential supply. Results of field investigations by USGS at the site and results from other studies support, and are consistent with, a conceptual model of a layered leaky aquifer where the dip of the beds has a strong control on hydraulic connections in the groundwater system. Connections within and (or) parallel to bedding tend to be greater than across bedding. Transmissivities of aquifer intervals isolated by packers ranged over three orders of magnitude [from about 2.8 to 2,290 square feet per day (ft 2 /d) or 0.26 to 213 square meters per day (m 2 /d)], did not appear to differ much by mapped geologic unit, but showed some relation to depth being relatively smaller in the shallowest and deepest intervals (0 to 50 ft and more than 250 ft below land surface, respectively) compared to the intermediate depth intervals (50 to 250 ft below land surface) tested. Transmissivities estimated from multiple-observation well aquifer tests ranged from about 700 to 2,300 ft 2 /d (65 to 214 m 2 /d). Results of chemical analyses of water from isolated intervals or monitoring wells open to short sections of the aquifer show vertical differences in concentrations; chloride and silica concentrations generally were greater in shallow intervals than in deeper intervals. Chloride concentrations greater than 100 milligrams per liter (mg/L), combined with distinctive chloride/bromide ratios, indicate a different source of chloride in the western part of North Penn Area 7 than elsewhere in the site. Groundwater flow at a regional scale under steady-state conditions was simulated by use of a numerical model (MODFLOW-2000) for North Penn Area 7 with different layers representing saprolite/highly weathered rock near the surface and unweathered competent bedrock. The sedimentary formations that underlie the study area were modeled using dipping model layers for intermediate and deep zones of unweathered, fractured rock. Horizontal cell model size was 100 meters (m) by 100 meters (328 ft by 328 ft), and model layer thickness ranged from 6 m (19.7 ft) representing shallow weathered rock and saprolite up to 200 m (656 ft) representing deeper dipping bedrock. The model did not include detailed structure to account for local-scale differences in hydraulic properties, with the result that local-scale groundwater flow may not be well simulated. Additional detailed multi-well aquifer tests would be needed to establish the extent of interconnection between intervals at the local scale to address remediation of contamination at each source area. This regional groundwater-flow model was calibrated against measured groundwater levels (1996, 2000, and 2005) and base flow estimated from selected streamflow measurements by use of nonlinear-regression parameter-estimation algorithms to determine hydraulic conductivity and anisotropy of hydraulic conductivity, streambed hydraulic conductivity, and recharge during calibration periods. Results of the simulation using the calibrated regional model indicate that the aquifer appears to be anisotropic where hydraulic conductivity is greatest parallel to the orientation of bedding of the formations underlying the area and least in the cross-bed direction. The maximum hydraulic conductivity is aligned with the average regional strike of the formations, which is “subhorizontal” in the model because the altitudes of the beds and model cells vary in the strike, as well as dip, direction. Estimated subhorizontal hydraulic conductivities (in strike direction parallel to dipping beds) range from 0.001 to 1.67 meters per day (0.0032 to 5.5 feet per day). The ratio of minimum (dip direction) to maximum (strike direction) subhorizontal hydraulic conductivity ranges from 1/3.1 to 1/8.6, and the ratio of vertical to horizontal hydraulic conductivity ranges from 1/1 to 1/478. However, limited available field data precluded rigorous calibration of vertical anisotropy in the model. Estimated recharge rates corresponding to calibration periods in 1996, 2000, and 2005 are 150, 109, and 124 millimeters per year (5.9, 4.3, and 4.9 inches per year), respectively. The calibrated groundwater-flow model was used to simulate groundwater flow under steady-state conditions during periods of relatively high withdrawals (pumpage) (1990) and relatively low withdrawals (2000 and 2005). Groundwater-flow paths originating from recharge areas near known areas of soil contamination (sources) were simulated. Pumped industrial and production wells captured more groundwater from several of these sources during 1990 than after 1990 when pumping declined or ceased and greater amounts of contaminated groundwater moved away from North Penn Area 7 Superfund site to surrounding areas. Uncertainty in simulated groundwater-flow paths from contaminant sources and contributing areas, resulting from uncertainty in estimated hydraulic properties of the model, was illustrated through Monte Carlo simulations. The effect of uncertainty in the vertical anisotropy was not included in the Monte Carlo simulations. Contributing areas indicating the general configuration of groundwater flow towards production well MG-202 (L-22) in the study area also were simulated for the different time periods; as simulated, the flow paths do not pass through any identified contaminant source in North Penn Area 7. However, contributing areas to wells, such as MG-202, located near many pumped wells are particularly complex and, in some cases, include areas that contribute flow to streams that subsequently recharge the aquifer through stream loss. In these cases, water-quality constituents, including contaminants that are present in surface water may be drawn into the aquifer to nearby pumped wells. Results of a simulated shutdown of well MG-202 under steady-state 2005 conditions showed that the area contributing recharge for nearby production well MG-76 (L-17), when MG-202 is not pumping, shifts downstream and is similar to the area contributing recharge for MG-202 when both wells are pumping. Concentrations of constituents in groundwater samples collected in fall 2005 or spring 2006 were compared to simulated groundwater-flow paths for the year 2005 to provide a qualitative assessment of model results. The observed spatial distribution of selected constituents, including TCE, CFC-11, and CFC-113 in groundwater in 2005 and the chloride/bromide mass ratios in 2006, generally were consistent with the model results of the simulated 2005 groundwater-flow paths at North Penn Area 7, indicating the presence of several separate sources of contaminants within North Penn Area 7.

Pennsylvania↗
USGS2013

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

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

Iowa↗
USGS2014

Methods for estimating the magnitude and frequency of floods for urban and small, rural streams in Georgia, South Carolina, and North Carolina, 2011

Reliable estimates of the magnitude and frequency of floods are essential for the design of transportation and water-conveyance structures, flood-insurance studies, and flood-plain management. Such estimates are particularly important in densely populated urban areas. In order to increase the number of streamflow-gaging stations (streamgages) available for analysis, expand the geographical coverage that would allow for application of regional regression equations across State boundaries, and build on a previous flood-frequency investigation of rural U.S Geological Survey streamgages in the Southeast United States, a multistate approach was used to update methods for determining the magnitude and frequency of floods in urban and small, rural streams that are not substantially affected by regulation or tidal fluctuations in Georgia, South Carolina, and North Carolina. The at-site flood-frequency analysis of annual peak-flow data for urban and small, rural streams (through September 30, 2011) included 116 urban streamgages and 32 small, rural streamgages, defined in this report as basins draining less than 1 square mile. The regional regression analysis included annual peak-flow data from an additional 338 rural streamgages previously included in U.S. Geological Survey flood-frequency reports and 2 additional rural streamgages in North Carolina that were not included in the previous Southeast rural flood-frequency investigation for a total of 488 streamgages included in the urban and small, rural regression analysis. The at-site flood-frequency analyses for the urban and small, rural streamgages included the expected moments algorithm, which is a modification of the Bulletin 17B log-Pearson type III method for fitting the statistical distribution to the logarithms of the annual peak flows. Where applicable, the flood-frequency analysis also included low-outlier and historic information. Additionally, the application of a generalized Grubbs-Becks test allowed for the detection of multiple potentially influential low outliers. Streamgage basin characteristics were determined using geographical information system techniques. Initial ordinary least squares regression simulations reduced the number of basin characteristics on the basis of such factors as statistical significance, coefficient of determination, Mallow’s Cp statistic, and ease of measurement of the explanatory variable. Application of generalized least squares regression techniques produced final predictive (regression) equations for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probability flows for urban and small, rural ungaged basins for three hydrologic regions (HR1, Piedmont–Ridge and Valley; HR3, Sand Hills; and HR4, Coastal Plain), which previously had been defined from exploratory regression analysis in the Southeast rural flood-frequency investigation. Because of the limited availability of urban streamgages in the Coastal Plain of Georgia, South Carolina, and North Carolina, additional urban streamgages in Florida and New Jersey were used in the regression analysis for this region. Including the urban streamgages in New Jersey allowed for the expansion of the applicability of the predictive equations in the Coastal Plain from 3.5 to 53.5 square miles. Average standard error of prediction for the predictive equations, which is a measure of the average accuracy of the regression equations when predicting flood estimates for ungaged sites, range from 25.0 percent for the 10-percent annual exceedance probability regression equation for the Piedmont–Ridge and Valley region to 73.3 percent for the 0.2-percent annual exceedance probability regression equation for the Sand Hills region.

Georgia, North Carolina, South Carolina↗
USGS2014

Estimation of flood discharges at selected annual exceedance probabilities for unregulated, rural streams in Vermont, with a section on Vermont regional skew regression

This report provides estimates of flood discharges at selected annual exceedance probabilities (AEPs) for streamgages in and adjacent to Vermont and equations for estimating flood discharges at AEPs of 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent (recurrence intervals of 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-years, respectively) for ungaged, unregulated, rural streams in Vermont. The equations were developed using generalized least-squares regression. Flood-frequency and drainage-basin characteristics from 145 streamgages were used in developing the equations. The drainage-basin characteristics used as explanatory variables in the regression equations include drainage area, percentage of wetland area, and the basin-wide mean of the average annual precipitation. The average standard errors of prediction for estimating the flood discharges at the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent AEP with these equations are 34.9, 36.0, 38.7, 42.4, 44.9, 47.3, 50.7, and 55.1 percent, respectively. Flood discharges at selected AEPs for streamgages were computed by using the Expected Moments Algorithm. To improve estimates of the flood discharges for given exceedance probabilities at streamgages in Vermont, a new generalized skew coefficient was developed. The new generalized skew for the region is a constant, 0.44. The mean square error of the generalized skew coefficient is 0.078. This report describes a technique for using results from the regression equations to adjust an AEP discharge computed from a streamgage record. This report also describes a technique for using a drainage-area adjustment to estimate flood discharge at a selected AEP for an ungaged site upstream or downstream from a streamgage. The final regression equations and the flood-discharge frequency data used in this study will be available in StreamStats. StreamStats is a World Wide Web application providing automated regression-equation solutions for user-selected sites on streams.

Vermont↗
USGS2014

Monitoring recharge in areas of seasonally frozen ground in the Columbia Plateau and Snake River Plain, Idaho, Oregon, and Washington

Seasonally frozen ground occurs over approximately one‑third of the contiguous United States, causing increased winter runoff. Frozen ground generally rejects potential groundwater recharge. Nearly all recharge from precipitation in semi-arid regions such as the Columbia Plateau and the Snake River Plain in Idaho, Oregon, and Washington, occurs between October and March, when precipitation is most abundant and seasonally frozen ground is commonplace. The temporal and spatial distribution of frozen ground is expected to change as the climate warms. It is difficult to predict the distribution of frozen ground, however, because of the complex ways ground freezes and the way that snow cover thermally insulates soil, by keeping it frozen longer than it would be if it was not snow covered or, more commonly, keeping the soil thawed during freezing weather. A combination of satellite remote sensing and ground truth measurements was used with some success to investigate seasonally frozen ground at local to regional scales. The frozen-ground/snow-cover algorithm from the National Snow and Ice Data Center, combined with the 21-year record of passive microwave observations from the Special Sensor Microwave Imager onboard a Defense Meteorological Satellite Program satellite, provided a unique time series of frozen ground. Periodically repeating this methodology and analyzing for trends can be a means to monitor possible regional changes to frozen ground that could occur with a warming climate. The Precipitation-Runoff Modeling System watershed model constructed for the upper Crab Creek Basin in the Columbia Plateau and Reynolds Creek basin on the eastern side of the Snake River Plain simulated recharge and frozen ground for several future climate scenarios. Frozen ground was simulated with the Continuous Frozen Ground Index, which is influenced by air temperature and snow cover. Model simulation results showed a decreased occurrence of frozen ground that coincided with increased temperatures in the future climate scenarios. Snow cover decreased in the future climate scenarios coincident with the temperature increases. Although annual precipitation was greater in future climate scenarios, thereby increasing the amount of water available for recharge over current (baseline) simulations, actual evapotranspiration also increased and reduced the amount of water available for recharge over baseline simulations. The upper Crab Creek model shows no significant trend in the rates of recharge in future scenarios. In these scenarios, annual precipitation is greater than the baseline averages, offsetting the effects of greater evapotranspiration in future scenarios. In the Reynolds Creek Basin simulations, precipitation was held constant in future scenarios and recharge was reduced by 1.0 percent for simulations representing average conditions in 2040 and reduced by 4.3 percent for simulations representing average conditions in 2080. The focus of the results of future scenarios for the Reynolds Creek Basin was the spatial components of selected hydrologic variables for this 92 square mile mountainous basin with 3,600 feet of relief. Simulation results from the watershed model using the Continuous Frozen Ground Index provided a relative measure of change in frozen ground, but could not identify the within-soil processes that allow or reject available water to recharge aquifers. The model provided a means to estimate what might occur in the future under prescribed climate scenarios, but more detailed energy-balance models of frozen-ground hydrology are needed to accurately simulate recharge under seasonally frozen ground and provide a better understanding of how changes in climate may alter infiltration.

Idaho;Oregon;Washington↗
USGS2014

Methods for estimating magnitude and frequency of 1-, 3-, 7-, 15-, and 30-day flood-duration flows in Arizona

Large floods have historically caused extensive damage in Arizona. Although peak-flow frequency estimates are required for managing the risk posed by floods, estimates of the frequency of sustained flood flow (flood-duration flow) are also useful for planning and assessing the adequacy of retention and conveyance structures and for water-resource planning. This report presents a flood-duration flow frequency analysis for selected durations (1 day, 3 day, 7 day, 15 day, and 30 day) at 173 streamgaging stations throughout Arizona and in western New Mexico. For each n -day duration, a log-Pearson type III distribution was fitted to the annual series of n -day flood-duration flows using the expected moments algorithm with a multiple Grubbs-Beck low-outlier test. Regional skews were developed independently for each n -day duration using a hybrid weighted least squares/generalized least squares method. No basin characteristics were found to adequately explain variation in skew among stations and a constant statewide skew model was used for all n -day durations. The regional skewness coefficient is negative for all n -day durations and becomes increasingly negative for longer n -day durations. Uncertainty associated with the skewness coefficient is estimated using a Bayesian generalized least squares technique. Regression equations, which allow predictions of n -day flood-duration flows for selected annual exceedance probabilities at ungaged sites, were developed using generalized least-squares regression and flood-duration flow frequency estimates at 56 streamgaging stations within a single, relatively uniform physiographic region in the central part of Arizona, between the Colorado Plateau and Basin and Range Province, called the Transition Zone. Drainage area explained most of the variation in the n -day flood-duration annual exceedance probabilities, but mean annual precipitation and mean elevation were also significant variables in the regression models. Standard error of prediction for the regression equations varies from 28 to 53 percent and generally decreases with increasing n -day duration. Outside the Transition Zone there are insufficient streamgaging stations to develop regression equations, but flood-duration flow frequency estimates are presented at select streamgaging stations.

Arizona↗
USGS2014

Evaluation of the magnitude and frequency of floods in urban watersheds in Phoenix and Tucson, Arizona

Flooding in urban areas routinely causes severe damage to property and often results in loss of life. To investigate the effect of urbanization on the magnitude and frequency of flood peaks, a flood frequency analysis was carried out using data from urbanized streamgaging stations in Phoenix and Tucson, Arizona. Flood peaks at each station were predicted using the log-Pearson Type III distribution, fitted using the expected moments algorithm and the multiple Grubbs-Beck low outlier test. The station estimates were then compared to flood peaks estimated by rural-regression equations for Arizona, and to flood peaks adjusted for urbanization using a previously developed procedure for adjusting U.S. Geological Survey rural regression peak discharges in an urban setting. Only smaller, more common flood peaks at the 50-, 20-, 10-, and 4-percent annual exceedance probabilities (AEPs) demonstrate any increase in magnitude as a result of urbanization; the 1-, 0.5-, and 0.2-percent AEP flood estimates are predicted without bias by the rural-regression equations. Percent imperviousness was determined not to account for the difference in estimated flood peaks between stations, either when adjusting the rural-regression equations or when deriving urban-regression equations to predict flood peaks directly from basin characteristics. Comparison with urban adjustment equations indicates that flood peaks are systematically overestimated if the rural-regression-estimated flood peaks are adjusted upward to account for urbanization. At nearly every streamgaging station in the analysis, adjusted rural-regression estimates were greater than the estimates derived using station data. One likely reason for the lack of increase in flood peaks with urbanization is the presence of significant stormwater retention and detention structures within the watershed used in the study.

Arizona↗
USGS2014

Methods for estimating annual exceedance-probability discharges and largest recorded floods for unregulated streams in rural Missouri

Regression analysis techniques were used to develop a set of equations for rural ungaged stream sites for estimating discharges with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. Basin and climatic characteristics were computed using geographic information software and digital geospatial data. A total of 35 characteristics were computed for use in preliminary statewide and regional regression analyses. Annual exceedance-probability discharge estimates were computed for 278 streamgages by using the expected moments algorithm to fit a log-Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data from water year 1844 to 2012. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized multiple Grubbs-Beck test was used to detect potentially influential low floods. Annual peak flows less than a minimum recordable discharge at a streamgage were incorporated into the at-site station analyses. An updated regional skew coefficient was determined for the State of Missouri using Bayesian weighted least-squares/generalized least squares regression analyses. At-site skew estimates for 108 long-term streamgages with 30 or more years of record and the 35 basin characteristics defined for this study were used to estimate the regional variability in skew. However, a constant generalized-skew value of -0.30 and a mean square error of 0.14 were determined in this study. Previous flood studies indicated that the distinct physical features of the three physiographic provinces have a pronounced effect on the magnitude of flood peaks. Trends in the magnitudes of the residuals from preliminary statewide regression analyses from previous studies confirmed that regional analyses in this study were similar and related to three primary physiographic provinces. The final regional regression analyses resulted in three sets of equations. For Regions 1 and 2, the basin characteristics of drainage area and basin shape factor were statistically significant. For Region 3, because of the small amount of data from streamgages, only drainage area was statistically significant. Average standard errors of prediction ranged from 28.7 to 38.4 percent for flood region 1, 24.1 to 43.5 percent for flood region 2, and 25.8 to 30.5 percent for region 3. The regional regression equations are only applicable to stream sites in Missouri with flows not significantly affected by regulation, channelization, backwater, diversion, or urbanization. Basins with about 5 percent or less impervious area were considered to be rural. Applicability of the equations are limited to the basin characteristic values that range from 0.11 to 8,212.38 square miles (mi 2 ) and basin shape from 2.25 to 26.59 for Region 1, 0.17 to 4,008.92 mi 2 and basin shape 2.04 to 26.89 for Region 2, and 2.12 to 2,177.58 mi 2 for Region 3. Annual peak data from streamgages were used to qualitatively assess the largest floods recorded at streamgages in Missouri since the 1915 water year. Based on existing streamgage data, the 1983 flood event was the largest flood event on record since 1915. The next five largest flood events, in descending order, took place in 1993, 1973, 2008, 1994 and 1915. Since 1915, five of six of the largest floods on record occurred from 1973 to 2012.

Missouri↗