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At least 757 records · Page 42Linked to original sources
USGS2018

Hydrologic assessment and numerical simulation of groundwater flow, San Juan Mine, San Juan County, New Mexico, 2010–13

Coal combustion byproducts (CCBs), which are composed of fly ash, bottom ash, and flue gas desulfurization material, produced at the coal-fired San Juan Generating Station (SJGS), located in San Juan County, New Mexico, have been buried in former surface-mine pits at the San Juan Mine, also referred to as the San Juan Coal Mine, since operations began in the early 1970s. This report, prepared by the U.S. Geological Survey in cooperation with the Mining and Minerals Division of the New Mexico Energy, Minerals and Natural Resources Department, describes results of a hydrogeologic assessment, including numerical groundwater modeling, to identify the timing of groundwater recovery and potential pathways for groundwater transport of metals that may be leached from stored CCBs and reach hydrologic receptors after operations cease. Data collected for the hydrologic assessment indicate that groundwater in at least one centrally located reclaimed surface-mining pit has already begun to recover. The U.S. Geological Survey numerical modeling package MODFLOW–NWT was used with MODPATH particle-tracking software to identify advective flow paths from CCB storage areas toward potential hydrologic receptors. Results indicate that groundwater at CCB storage areas will recover to the former steady state, or in some locations, groundwater may recover to a new steady state in 6,600 to 10,600 years at variable rates depending on the proximity to a residual cone-of-groundwater depression caused by mine dewatering and regional oil and gas pumping as well as on actual, rather than estimated, groundwater recharge and evapotranspirational losses. Advective particle-track modeling indicates that the number of particles and rates of advective transport will vary depending on hydraulic properties of the mine spoil, particularly hydraulic conductivity and porosity. Modeling results from the most conservative scenario indicate that particles can migrate from CCB repositories to either the Shumway Arroyo alluvium after 1,320 years and from there to the San Juan River alluvium after 1,520 years or from southernmost CCB repositories directly to the San Juan River alluvium after 2,400 years after the cessation of mining.

New Mexico↗
USGS2026

Thickness and other characteristics of overbank sediment deposited during an extreme flood in May 1978 along the Powder River, Montana

An extreme flood on the Powder River in southeastern Montana in May 1978 inundated its valley and deposited sediment on the floodplains and terraces at multiple heights. The recurrence interval for this flood was less than 1 percent in the reach between Moorhead and Broadus, Montana. Peak discharges at the U.S. Geological Survey streamgages at Moorhead and Broadus were 779 and 711 cubic meters per second (m 3 /s), respectively, the difference reflecting the water and sediment stored on the valley surfaces. Bankfull discharge depended on the height of the bank at the start of the valley transect and varied from 243 to 713 m 3 /s. Sediment-thickness and particle-size data were collected and analyzed in the autumn of 1978 by U.S. Geological Survey scientists at about 900 sites along 20 valley transects between Moorhead and Broadus, Mont. These transects were approximately orthogonal to the floodflow across the floodplain from near the edge of the channel to the high-water mark. Estimated maximum flood depths along these transects ranged from 0.9 to 4.2 meters. Contrary to theory and controlled laboratory experiments, the distribution of sediment thickness and particle sizes along valley transects did not decrease systematically with distance from the main channel but were affected by the distribution of vegetation. Additionally, some water and sediment—primarily muds and silts—were conveyed by subsidiary channels (often connected to the main channel downriver from the valley transect) during the early stages of the flood before water overtopped the banks at the start of the valley transect. The vegetation created natural sediment traps in the recirculation and wake zones in the lee of trees and shrubs. Sediment that accumulated in these traps formed dunes and thus an undulating surface with many local maximums and minimums in sediment thicknesses. Sediment in the traps are referred to as lee dunes, which recorded flow conditions and a predominance of coarsening-upward sequence of particle sizes (mud to silt to sands) starting at the preflood surface. These sequences were associated with the rising limb of the hydrograph, and later as the flood began to recede, the lee dunes recorded a fining-upward sequence associated with the falling limb of the hydrograph.

Montana↗
USGS2015

Model averaging and muddled multimodel inferences

Three flawed practices associated with model averaging coefficients for predictor variables in regression models commonly occur when making multimodel inferences in analyses of ecological data. Model-averaged regression coefficients based on Akaike information criterion (AIC) weights have been recommended for addressing model uncertainty but they are not valid, interpretable estimates of partial effects for individual predictors when there is multicollinearity among the predictor variables. Multicollinearity implies that the scaling of units in the denominators of the regression coefficients may change across models such that neither the parameters nor their estimates have common scales, therefore averaging them makes no sense. The associated sums of AIC model weights recommended to assess relative importance of individual predictors are really a measure of relative importance of models, with little information about contributions by individual predictors compared to other measures of relative importance based on effects size or variance reduction. Sometimes the model-averaged regression coefficients for predictor variables are incorrectly used to make model-averaged predictions of the response variable when the models are not linear in the parameters. I demonstrate the issues with the first two practices using the college grade point average example extensively analyzed by Burnham and Anderson. I show how partial standard deviations of the predictor variables can be used to detect changing scales of their estimates with multicollinearity. Standardizing estimates based on partial standard deviations for their variables can be used to make the scaling of the estimates commensurate across models, a necessary but not sufficient condition for model averaging of the estimates to be sensible. A unimodal distribution of estimates and valid interpretation of individual parameters are additional requisite conditions. The standardized estimates or equivalently the t statistics on unstandardized estimates also can be used to provide more informative measures of relative importance than sums of AIC weights. Finally, I illustrate how seriously compromised statistical interpretations and predictions can be for all three of these flawed practices by critiquing their use in a recent species distribution modeling technique developed for predicting Greater Sage-Grouse ( Centrocercus urophasianus ) distribution in Colorado, USA. These model averaging issues are common in other ecological literature and ought to be discontinued if we are to make effective scientific contributions to ecological knowledge and conservation of natural resources.

Ecology↗
USGS2013

Identification of metrics to monitor salt marsh integrity on National Wildlife Refuges in relation to conservation and management objectives

Executive Summary Most salt marshes in the US have been degraded by human activities, and threats from physical alterations, surrounding land-use, species invasions, and global climate change persist. Salt marshes are unique and highly productive ecosystems with high intrinsic value to wildlife, and many National Wildlife Refuges (NWRs) have been established in coastal areas to protect large tracts of salt marsh and wetland-dependent species. Various management practices are employed routinely on coastal NWRs to restore and enhance marsh integrity and ensure ecosystem sustainability. Prioritizing NWR salt marshes for application of management actions and choosing among multiple management options requires scientifically-based methods for assessing marsh condition. Monitoring is integral to structured decision-making (SDM), a formal process for decomposing a decision into its essential elements. Within a natural resource context, SDM involves identifying management objectives, alternative management actions, and expected management outcomes. The core of SDM is a set of criteria for measuring system performance and evaluating management responses. Therefore, use of SDM to frame natural resource decisions leads to logical selection of monitoring attributes that are linked explicitly to management needs. We used SDM to guide selection of variables for monitoring the ecological integrity of salt marshes within the National Wildlife Refuge System (NWRS). Our objectives were to identify indicators of salt marsh integrity that are effective across large geographic regions, responsive to a wide range of threats, and feasible to implement within funding and staffing constraints of the NWRS. In April, 2008, we engaged interdisciplinary experts in a week-long rapid prototyping SDM workshop to define the essential elements of salt marsh management decisions on refuges throughout the northeastern, southwestern, and northwestern US, corresponding to respective Regions 5, 2, and 1 of the US Fish and Wildlife Service (FWS). Through this process we identified measurable attributes for monitoring salt marsh ecosystems that are integrated into conservation practice and target management objectives. The following salt marsh attributes were identified through the SDM process either for describing state condition to determine management needs or for evaluating the achievement of management objectives: historical condition and geomorphic setting; ditch density; surrounding land use; ratio of open water area to vegetation area; rate of pesticide application; environmental contaminant concentration; change in marsh surface elevation relative to sea level rise; tidal range and groundwater level; surface topography; salinity; and species composition and abundance of vegetation, invasive species, invertebrates, nekton, and breeding and wintering birds. The identified attributes were too broadly defined to serve as operational monitoring variables. Therefore, we tested specific metrics for quantifying most of these attributes in summers of 2008 and 2009. The first four attributes in the above list can be characterized by office-based analysis of existing GIS data layers. The remaining attributes require field-based methods for assessment. We were forced to exclude a small number of attributes from field tests due to inconsistent data (pesticide application rate, environmental contaminant concentrations) or requirements that exceeded the scope of this project (change in marsh surface elevation; surface topography; benthic invertebrates; wintering birds). We evaluated potential metrics for evaluating all remaining field attributes. In partnership with NWRS biologists, we tested rapid versus intensive metrics for monitoring field attributes (tidal range and groundwater level; marsh surface elevation; salinity; and species composition and abundance of vegetation, invasive species, nekton, and breeding birds) at coastal refuges throughout FWS Region 5. Seven refuges participated in metric testing in 2008: Rachel Carson (ME), Parker River (MA), Wertheim (NY), E. B. Forsythe (NJ), Bombay Hook (DE), Prime Hook (DE), and Eastern Shore of Virginia Complex (VA). These seven and two additional refuges participated in metric testing in 2009: Rhode Island Complex (RI) and Stewart B. McKinney (CT). We based all field metrics on existing protocols for salt marsh assessment. Sampling locations were determined randomly within delineated marsh study units (MSUs) at each refuge. Detailed field methods are provided in appendices to this report. Measurements for individual metrics were averaged across samples within MSUs during each year of sampling. Each year, correlation or regression analysis was conducted on average measurements across MSUs within each attribute set to identify redundant metrics. Statistical redundancy between a pair of metrics within an attribute set (i.e., correlation or regression slopes with p-values < 0.05) was considered justification for eliminating one of the pair from the regional set of monitoring metrics. Decisions regarding metric elimination versus retention were based on feasibility of monitoring, considering such factors as sampling time, resources required, and potential for regional standardization in implementation. The result of these tests is a reduced suite of monitoring metrics that targets NWRS management decisions and is practicable for implementing on a regional scale. Based on these tests, we recommend the following list of metrics for monitoring integrity of NWRS salt marshes (marsh attribute category is in parentheses): (historical condition and geomorphic setting) position of marsh in the landscape, marsh shape, degree of fill and/or fragmentation, degree of tidal flushing, amount of aquatic edge; (ditch density) ranking of ditch density from none to severe; (surrounding land use) relative proportion of agricultural land in a 150-m buffer around the marsh, relative proportion of natural land in a 150-m buffer around the marsh, relative proportion of natural land in a 1-km buffer around the marsh; (ratio of open water area to vegetation area) ratio of open water to emergent herbaceous wetlands within the marsh; (marsh surface elevation) elevation referenced to NAVD88 in a representative area of the marsh; (tidal range and groundwater level) percent of time the marsh surface is flooded during deployment of a continuous water-level monitor at a representative marsh location, mean depth of surface flooding as measured by a continuous water-level monitor at a representative location; (salinity) salinity measured in surface water; (vegetation community) vegetation species richness using the point-intercept method in 100-m diameter survey plots, percent cover of various marsh community types within 100-m diameter survey plots; (invasive species abundance) percent cover of invasive plant species measured using the point-intercept method in 100-m diameter survey plots; (nekton community) nekton density, nekton species richness, length of Fundulus heteroclitus ; (breeding bird community) abundance of Willets counted per point during standard call-broadcast surveys, summed abundance of tidal marsh obligate species (Clapper Rail, Willet, Saltmarsh Sparrow, Seaside Sparrow) counted per point during standard call-broadcast surveys. Metrics describing the historical condition, geomorphic setting, and broad landscape features can be assessed using existing GIS databases. Our results support use of rapid methods to assess the majority of field metrics; only those used to describe the nekton community must be measured using intensive methods (throw traps or ditch nets, dependant on habitat configuration). Implementation of these metrics for quantitative assessment of NWRS salt marsh integrity in FWS Region 5 requires developing sampling designs for each refuge. Additionally, it is important to determine how the monitoring information will be used within a management context. SDM should be used to complete the analysis of salt marsh management decisions. The next steps would involve 1) prioritizing and weighting the management objectives; 2) predicting responses to individual management actions in terms of objectives and metrics; 3) using multiattribute utility theory to convert all measurable attributes to a common utility scale; 4) determining the total management benefit of each action by summing utilities across objectives; and 5) maximizing the total management benefits within cost constraints for each refuge. This process would allow the optimum management decisions for NWRS salt marshes to be selected and implemented based directly on monitoring data and current understanding of marsh responses to management actions. Monitoring the outcome of management actions would then allow new monitoring data to be incorporated into subsequent decisions.

Connecticut, Delaware, Maine, Massachusetts, New J↗
USGS2008

Estimating the Effects of Conversion of Agricultural Land to Urban Land on Deep Percolation of Irrigation Water in the Grand Valley, Western Colorado

The conversion of agricultural land to urban residential land is associated with rapid population growth in the Grand Valley of western Colorado. Information regarding the effects of this land-use conversion on deep percolation, irrigation-water application, and associated salt loading to the Colorado River is needed to support water-resource planning and conservation efforts. The Natural Resources Conservation Service (NRCS) assessed deep percolation and estimated salt loading derived from irrigated agricultural lands in the Grand Valley in a 1985 to 2002 monitoring and evaluation study (NRCS M&E). The U.S. Geological Survey (USGS), in cooperation with the Colorado River Salinity Control Forum and the Mesa Conservation District, quantified the current (2005-2006) deep percolation and irrigation-water application characteristics of 1/4-acre residential lots and 5-acre estates, urban parks, and urban orchard grass fields in the Grand Valley, and compared the results to NRCS M&E results from alfalfa-crop sites. In addition, pond seepage from three irrigation-water holding ponds was estimated. Salt loading was estimated for the urban study results and the NRCS M&E results by using standard salt-loading factors. A daily soil-moisture balance calculation technique was used at all urban study irrigated sites. Deep percolation was defined as any water infiltrating below the top 12 inches of soil. Deep percolation occurred when the soil-moisture balance in the first 12 inches of soil exceeded the field capacity for the soil type at each site. Results were reported separately for urban study bluegrass-only sites and for all-vegetation type (bluegrass, native plants, and orchard grass) sites. Deep percolation and irrigation-water application also were estimated for a complete irrigation season at three subdivisions by using mean site data from each subdivision. It was estimated that for the three subdivisions, 37 percent of the developed acreage was irrigated (the balance being impermeable surfaces).

Scientific Investigations Report↗
USGS2014

Low-flow characteristics of streams in the Lahaina District, West Maui, Hawai'i

The purpose of this study was to characterize streamflow availability under natural low-flow conditions for streams in the Lahaina District, west Maui, Hawaiʻi. The study-area streams included Honolua Stream and tributary Pāpua Gulch, Honokahua Stream and tributary Mokupeʻa Gulch, Kahana Stream, Honokōwai Stream and tributaries Amalu and Kapāloa Streams, Wahikuli Gulch and tributary Hāhākea Gulch, Kahoma Stream and tributary Kanahā Stream, Kauaʻula Stream, Launiupoko Stream, Olowalu Stream, and Ukumehame Gulch. The results of this study can be used to assist in the determination of technically defensible instream-flow standards for the study-area streams. Low-flow characteristics for natural (unregulated) streamflow conditions were represented by flow-duration discharges that are equaled or exceeded between 50 and 95 percent of the time. Partial-record sites were established on 10 main streams and 5 tributary streams, mainly upstream from existing surface-water diversions. Flow characteristics were determined using historical and current streamflow data from continuous-record streamflow-gaging stations and miscellaneous sites, and additional data collected as part of this study. Based on strategically scheduled observations, six of the study-area streams were ephemeral streams that were observed to remain dry at least 50 percent of the time: Pāpua Gulch, Honokahua Stream and its tributary Mokupeʻa Gulch, Kahana Stream, and Wahikuli Gulch and its tributary Hāhākea Gulch. For the remaining streams with measurable flow, Honolua, Honokōwai, Kahoma, Kanahā, Kauaʻula, Launiupoko, and Olowalu Streams, and Ukumehame Gulch, flow-duration discharges were computed for the 30-year base period (water years 1984–2013), using two record-augmentation techniques. The 95-percent flow-duration discharges ranged from 0 to 4.8 cubic feet per second (ft 3 /s). The 50-percent flow-duration discharges ranged from 0.47 to 9.5 ft 3 /s. This study also estimated the streamflow gains and losses downstream of surface-water diversions using seepage-run measurements. A majority of the streams lost flow downstream from diversions. Measured seepage-loss rates ranged between 0.045 and 1.6 ft3/s per mile of stream reach. Seepage gains mostly occurred upstream from diversions and the measured seepage-gain rates generally ranged between 0.75 and 5.1 ft3/s per mile of stream reach. Under natural-flow conditions, Honolua Stream is estimated to flow to the ocean less than 80 percent of the time and Honokōwai Stream is estimated to flow to the ocean less than 50 percent of the time. Kahoma Stream, Kauaʻula Stream, Olowalu Stream, and Ukumehame Gulch are estimated to flow to the ocean at least 95 percent of the time.

Hawai'i↗
USGS2015

Evaluation of mean-monthly streamflow-regression equations for Colorado, 2014

The U.S. Geological Survey, in cooperation with the Colorado Water Conservation Board, evaluated the predictive uncertainty of mean-monthly streamflow-regression equations representative of natural streamflow conditions in Colorado. This study evaluates the predictive uncertainty of mean-monthly streamflow-regression equations developed in a 2009 U.S. Geological Survey study using streamflow data collected over the entire period of record at each streamgage through calendar year 2013. The study area for this report is limited to the Mountain, Northwest, Rio Grande, and Southwest hydrologic regions of Colorado. Data collected from the beginning of the period of record through calendar year 2013 were used to evaluate the mean-monthly streamflow equations using the same basin characteristics as in the 2009 study. U.S. Geological Survey and Colorado Division of Water Resources streamgages with at least 10 years of streamflow record and identified as representative of natural streamflow conditions were selected for this study. During the streamgage selection process, a total of 432 streamgages, composed of 278 from the 2009 study and 154 new streamgages, were identified. The updated standard error of prediction and adjusted coefficient of determination values that correspond to the mean-monthly streamflow equations developed in the 2009 study are in close agreement with the results of this study. The old streamgages performed slightly better than the new streamgages, with approximately 88 and 85 percent of the data within the prediction intervals, respectively. This result was expected because the streamgages used to develop the regression equations should yield a better performance than the new streamgages. For all hydrologic regions, approximately 87 percent of the data are within the 95-percent prediction intervals. The explanation for why fewer than 95 percent of the data are within the prediction intervals is that the data do not conform perfectly to the regression assumptions required to accurately estimate performance metrics. The equations for the Rio Grande hydrologic region had the best fit with the parametric prediction-interval assumptions, with approximately 91.8 percent of the data within the prediction interval (average 12 months). The Mountain, Northwest, and Southwest hydrologic regions had 87.8, 84.9, and 83.5 percent of the data contained within the prediction interval, respectively. Monthly adjusted coefficient of determination values were computed and have the same general pattern for all four hydrologic regions. The largest values usually occur in March or April, and the lowest values usually occur in August or September. Only the Rio Grande hydrologic region deviates from this seasonal pattern, exhibiting a decrease in adjusted coefficient of determination values in August and September, with the lowest values occurring in the winter months (December, January, and February). Generally, the adjusted coefficient of determination values for this report are just slightly less (0.76 compared to 0.79) than the values computed in the 2009 study. The similarity of values, even when tested with data not used to originally develop the mean-monthly streamflow-regression equations, provides confidence that the predictive uncertainty of mean-monthly regression equations in the 2009 study are accurate. The fact that the results for the two datasets are very similar provides assurance that when these equations are applied to locations not used to develop the equations, the standard error of prediction and adjusted-coefficient of determination error metrics should be similar to those established in the 2009 study for locations with natural streamflow. The median absolute differences between the observed and computed mean-monthly streamflow for Mountain, Northwest, and Southwest hydrologic regions are fairly uniform throughout the year, with the exception of late summer and early fall (July, August, and September), when each hydrologic region exhibits a substantial increase in median absolute percent difference. The greatest difference occurs in the Northwest hydrologic region, and the smallest difference occurs in the Mountain hydrologic region. The Rio Grande hydrologic region shows seasonal variation in median absolute percent difference with March, April, August, and September having a median absolute difference near or below 40 percent, and the remaining months of the year having a median absolute difference near or above 50 percent. In the Mountain, Northwest, and Southwest hydrologic regions, the mean-monthly streamflow equations perform the best during spring (March, April, and May). However, in the Rio Grande hydrologic region, the mean-monthly streamflow equations perform the best during late summer and early fall (August and September).

Arizona, Colorado, New Mexico, Utah, Wyoming↗
USGS2014

Nearshore bathymetric mapping along a 7-mile reach of Lake Sharpe shoreline near Lower Brule, South Dakota, 2013

Shoreline erosion rates along Lake Sharpe, a Missouri River reservoir, near the community of Lower Brule, South Dakota, were studied previously during 2011–12 by the U.S. Geological Survey, the Lower Brule Sioux Tribe, and Oglala Lakota College. The rapid shoreline retreat has caused many detrimental effects along the shoreline of Lake Sharpe, including losses of cultural sites, recreation access points, wildlife habitat, irrigated cropland, and landmass. The Lower Brule Sioux Tribe is considering options to reduce or stop erosion. One such option for consideration is the placement of discontinuous rock breakwater structures in shallow water to reduce wave action at shore. Information on the depth of water and stability characteristics of bottom material in nearshore areas of Lake Sharpe is needed by the Lower Brule Sioux Tribe to develop structural mitigation alternatives. To help address this need, a bathymetric survey of nearshore areas of Lake Sharpe near Lower Brule, South Dakota, was completed in 2013 by the U.S. Geological Survey in cooperation with the Lower Brule Sioux Tribe. HYPACK® hydrographic survey software was used to plan data collection transects for a 7-mile reach of Lake Sharpe shoreline near Lower Brule, South Dakota. Regular data collection transects and oblique transects were planned to allow for quality-assurance/quality-control comparisons. Two methods of data collection were used in the bathymetric survey: (1) measurement from a boat using bathymetric instrumentation where water was more than 2 feet deep, and (2) wading using Real-Time Kinematic Global Navigation Satellite System equipment on shore and where water was shallower than 2 feet deep. A dual frequency, 24- or 200-kilohertz narrow beam, depth transducer was used in conjunction with a Teledyne Odom CV100 dual frequency echosounder for boat-based data collection. In water too shallow for boat navigation, the elevation and nature of the reservoir bottom were mapped using Real-Time Kinematic Global Navigation Satellite System equipment. Once the data collection effort was completed, data editing was performed in HYPACK® to remove erroneous data points and to apply water-surface elevations. Maps were developed separately for water depth and bottom elevation for the study area. Lines of equal water depth for 2, 3, 3.5, 4, and 5 feet from the water surface to the lake bottom were mapped in nearshore areas of Lake Sharpe. Overall, water depths stay shallow for quite a distance from shore. In the 288 transects that crossed a 2 foot depth line, this depth occurred an average of 88 feet from shore. Similarly, in the 317 transects that crossed a 3 foot depth line, this did not occur until an average of 343 feet from shore. Elevation contours of the lake bottom were mapped primarily for elevations ranging from 1,419 to 1,416 feet above North American Vertical Datum of 1988. Horizontal errors of the Real-Time Kinematic Global Navigation Satellite System equipment for the study area are essentially inconsequential because water depth and bottom elevation were determined to change relatively slowly. The estimated vertical error associated with the Real-Time Kinematic Global Navigation Satellite System equipment for the study area ranges from 0.6 to 0.9 inch. This vertical error is small relative to the accuracy of the bathymetric data. Accuracy assessments of the data collected for this study were computed according to the National Standard for Spatial Data Accuracy. The maps showing the lines of equal water depth and elevation contours of the lake bottom are able to support a 1-foot contour interval at National Standards for Spatial Data Accuracy vertical accuracy standards, which require a vertical root mean squared error of 0.30 foot or better and a fundamental vertical accuracy calculated at the 95-percent confidence level of 0.60 foot or better.

South Dakota↗
USGS2007

Effects of Withdrawals on Ground-Water Levels in Southern Maryland and the Adjacent Eastern Shore, 1980-2005

Ground water is the primary source of water supply in most areas of Maryland?s Atlantic Coastal Plain, including Southern Maryland. The counties in this area are experiencing some of the most rapid growth and development in the State, resulting in an increased demand for ground-water production. The cooperative, basic water-data program of the U.S. Geological Survey and the Maryland Geological Survey has collected long-term observations of ground-water levels in Southern Maryland and parts of the Eastern Shore for many decades. Additional water-level observations were made by both agencies beginning in the 1970s, under the Power Plant Research Program of the Maryland Department of Natural Resources. These long-term water levels commonly show significant declines over several decades, which are attributed to ground-water withdrawals. Ground-water-level trends since 1980 in major Coastal Plain aquifers such as the Piney Point-Nanjemoy, Aquia, Magothy, upper Patapsco, lower Patapsco, and Patuxent were compared to water use and withdrawal data. Potentiometric surface maps show that most of the declines in ground-water levels can be directly related to effects from major pumping centers. There is also evidence that deep drawdowns in some pumped aquifers may be causing declines in adjacent, unpumped aquifers. Water-level hydrographs of many wells in Southern Maryland show linear declines in levels year after year, instead of the gradual leveling-off that would be expected as the aquifers equilibrate with pumping. A continual increase in the volumes of water being withdrawn from the aquifers is one explanation for why they are not reaching equilibrium. Although reported ground-water production in Southern Maryland has increased somewhat over the past several decades, the reported increases are often not large enough to account for the observed water-level declines. Numerical modeling simulations indicate that a steady, annual increase in the number of small wells could account for the observed aquifer behavior. Such wells, being pumped at rates below the minimum legal reporting threshold of 10,000 gallons per day, might be the source of the additional withdrawals. More detailed water-use data, especially from domestic wells, central-pivot irrigation wells, and other small users not currently reporting withdrawals to the State, may help to determine the cause of the aquifer declines.

Scientific Investigations Report↗
USGS2022

Use of high-resolution topobathymetry to assess shoreline topography and potential future development of a slack water harbor near Dardanelle, Arkansas, October 2021

The U.S. Army Corps of Engineers (USACE), Southwestern Division, Little Rock District Civil Works program has a mission to maintain cohesion between physical and naturally developed environments. The USACE authorized the development of an off-channel harbor (hereinafter referred to as the “proposed slack water harbor”) along the McClellan-Kerr Arkansas River Navigation System at river mile 202.6, and an initial evaluation of shoreline stability and adjacent land near the proposed harbor was considered essential in establishing a baseline for potential effects and future monitoring. In October 2021, the U.S. Geological Survey, in cooperation with the USACE, completed high-resolution bathymetric (underwater elevation) and topographic surveys of the Arkansas River and a quarry at the location of the proposed slack water harbor near Dardanelle, Arkansas, using a combination of multibeam sound navigation and ranging (sonar) and high-resolution, low-altitude aerial light detection and ranging (lidar) data to provide data and analysis needed for as-built information and future monitoring of river shoreline and floodplain management and maintenance. Bathymetric data were collected using a high-resolution multibeam mapping system, which consists of a multibeam echosounder and an inertial navigation system mounted on a marine survey vessel. Data were collected as the vessel traversed the river and quarry along overlapping survey lines distributed throughout the areas. Topographic data were collected as a lidar point cloud using an unmanned aircraft system (UAS) with a YellowScan Vx20–100 lidar payload, which consists of the lidar scanner and an inertial navigation system. The lidar point cloud data were collected as the UAS followed two sets of parallel transect lines, oriented perpendicular to each other (nominally north to south and east to west) on separate flights. The bathymetric and UAS topographic datasets were combined with topographic data extracted from publicly available aerial lidar data collected in 2014 to create a multisource point cloud classified as “ground” (code 2) according to the American Society for Photogrammetry and Remote Sensing standard lidar point classes in the proposed harbor area and surroundings, from which topographic contours were derived.

Arkansas↗
USGS2009

Regional Curves of Bankfull Channel Geometry for Non-Urban Streams in the Piedmont Physiographic Province, Virginia

Natural-channel design involves constructing a stream channel with the dimensions, slope, and plan-view pattern that would be expected to transport water and sediment and yet maintain habitat and aesthetics consistent with unimpaired stream segments, or reaches. Regression relations for bankfull stream characteristics based on drainage area, referred to as 'regional curves,' are used in natural stream channel design to verify field determinations of bankfull discharge and stream channel characteristics. One-variable, ordinary least-squares regressions relating bankfull discharge, bankfull cross-sectional area, bankfull width, bankfull mean depth, and bankfull slope to drainage area were developed on the basis of data collected at 17 streamflow-gaging stations in rural areas with less than 20 percent urban land cover within the basin area (non-urban areas) of the Piedmont Physiographic Province in Virginia. These regional curves can be used to estimate the bankfull discharge and bankfull channel geometry when the drainage area of a watershed is known. Data collected included bankfull cross-sectional geometry, flood-plain geometry, and longitudinal profile data. In addition, particle-size distributions of streambed material were determined, and data on basin characteristics were compiled for each reach. Field data were analyzed to determine bankfull cross-sectional area, bankfull width, bankfull mean depth, bankfull discharge, bankfull channel slope, and D50 and D84 particle sizes at each site. The bankfull geometry from the 17 sites surveyed during this study represents the average of two riffle cross sections for each site. Regional curves developed for the 17 sites had coefficient of determination (R2) values of 0.950 for bankfull cross-sectional area, 0.913 for bankfull width, 0.915 for bankfull mean depth, 0.949 for bankfull discharge, and 0.497 for bankfull channel slope. The regional curves represent conditions for streams with defined channels and bankfull features in the Piedmont Physiographic Province in Virginia with drainage areas ranging from 0.29 to 111 square miles. All sites included in the development of the regional curves were located on streams with current or historical U.S. Geological Survey streamflow-gaging stations. These curves can be used to verify bankfull features identified in the field and bankfull stage for ungaged streams in non-urban areas.

Scientific Investigations Report↗
USGS2012

Changes in water budgets and sediment yields from a hypothetical agricultural field as a function of landscape and management characteristics--A unit field modeling approach

Crop agriculture occupies 13 percent of the conterminous United States. Agricultural management practices, such as crop and tillage types, affect the hydrologic flow paths through the landscape. Some agricultural practices, such as drainage and irrigation, create entirely new hydrologic flow paths upon the landscapes where they are implemented. These hydrologic changes can affect the magnitude and partitioning of water budgets and sediment erosion. Given the wide degree of variability amongst agricultural settings, changes in the magnitudes of hydrologic flow paths and sediment erosion induced by agricultural management practices commonly are difficult to characterize, quantify, and compare using only field observations. The Water Erosion Prediction Project (WEPP) model was used to simulate two landscape characteristics (slope and soil texture) and three agricultural management practices (land cover/crop type, tillage type, and selected agricultural land management practices) to evaluate their effects on the water budgets of and sediment yield from agricultural lands. An array of sixty-eight 60-year simulations were run, each representing a distinct natural or agricultural scenario with various slopes, soil textures, crop or land cover types, tillage types, and select agricultural management practices on an isolated 16.2-hectare field. Simulations were made to represent two common agricultural climate regimes: arid with sprinkler irrigation and humid. These climate regimes were constructed with actual climate and irrigation data. The results of these simulations demonstrate the magnitudes of potential changes in water budgets and sediment yields from lands as a result of landscape characteristics and agricultural practices adopted on them. These simulations showed that variations in landscape characteristics, such as slope and soil type, had appreciable effects on water budgets and sediment yields. As slopes increased, sediment yields increased in both the arid and humid environments. However, runoff did not increase with slope in the arid environment as was observed in the humid environment. In both environments, clayey soils exhibited the greatest amount of runoff and sediment yields while sandy soils had greater recharge and lessor runoff and sediment yield. Scenarios simulating the effects of the timing and type of tillage practice showed that no-till, conservation, and contouring tillages reduced sediment yields and, with the exception of no-till, runoff in both environments. Changes in land cover and crop type simulated the changes between the evapotransporative potential and surface roughness imparted by specific vegetations. Substantial differences in water budgets and sediment yields were observed between most agricultural crops and the natural covers selected for each environment: scrub and prairie grass for the arid environment and forest and prairie grass for the humid environment. Finally, a group of simulations was performed to model selected agricultural management practices. Among the selected practices subsurface drainage and strip cropping exhibited the largest shifts in water budgets and sediment yields. The practice of crop rotation (corn/soybean) and cover cropping (corn/rye) were predicted to increase sediment yields from a field planted as conventional corn.

Scientific Investigations Report↗
USGS2024

Streamflow characteristics and trends in New Jersey, water years 1903–2017

As New Jersey’s population density remains high, so does its requirements for water management. Understanding the streamflow conditions throughout the state and how they may have changed over time is an important part of managing the water resources within the state. The New Jersey Department of Environmental Protection has many responsibilities related to protecting the environment and natural resources and among them is protecting the waters in the lakes, rivers, and streams of New Jersey for current and future use. To support this mission, the U.S. Geological Survey updated high- and low-streamflow statistics for 97 continuous-record streamgages and low-streamflow statistics for 719 partial-record streamgages throughout the state. The continuous-record streamgages included in the study had a minimum of 20 years of record, spanning from 1903 to 2017. This study is an update to previous studies that documented the high- and low-streamflow statistics for New Jersey streams in the 1970s and in 2005. The 1982 report by Gillespie and Schopp documented low-flow characteristics and flow duration for about 400 continuous and partial-record streamgages. The U.S. Geological Survey computed streamflow statistics including, but not limited to, maximum, minimum, and means for period of record, flow durations, nonexceedance high- and low-flow frequencies, base flow, runoff, peak-to-mean flow ratios, and September median streamflow. Overall, both high and low flows are generally increasing in New Jersey, though the results are not uniform across the State. Streamflow trends and changes to duration and frequency statistics can be influenced by local water use, in addition to climate variables. The resulting computations at some streamgages indicated considerable positive change while others showed considerable negative change. Water managers and regulators can use the data provided here and in the companion data release to assess individual stream reaches and watershed management areas to evaluate the available resources and changes, which may have developed during the periods for which streamflow statistics are available.

New Jersey↗
USGS2013

Application of the Precipitation-Runoff Modeling System (PRMS) in the Apalachicola-Chattahoochee-Flint River Basin in the southeastern United States

A hydrologic model of the Apalachicola–Chattahoochee–Flint River Basin (ACFB) has been developed as part of a U.S. Geological Survey (USGS) National Climate Change and Wildlife Science Center effort to provide integrated science that helps resource managers understand the effect of climate change on a range of ecosystem responses. The hydrologic model was developed as part of the Southeast Regional Assessment Project using the Precipitation Runoff Modeling System (PRMS), a deterministic, distributed-parameter, process-based system that simulates the effects of precipitation, temperature, and land use on basin hydrology. The ACFB PRMS model simulates streamflow throughout the approximately 50,700 square-kilometer basin on a daily time step for the period 1950–99 using gridded climate forcings of air temperature and precipitation, and parameters derived from spatial data layers of altitude, land cover, soils, surficial geology, depression storage (small water bodies), and data from 56 USGS streamgages. Measured streamflow data from 35 of the 56 USGS streamgages were used to calibrate and evaluate simulated basin streamflow; the remaining gage locations were used for model delineation only. The model matched measured daily streamflow at 31 of the 35 calibration gages with Nash-Sutcliffe Model Efficiency Index (NS) greater than 0.6. Streamflow data for some calibration gages were augmented for regulation and water use effects to represent more natural flow volumes. Time-static parameters describing land cover limited the ability of the simulation to match historical runoff in the more developed subbasins. Overall, the PRMS simulation of the ACFB provides a good representation of basin hydrology on annual and monthly time steps. Calibration subbasins were analyzed by separating the 35 subbasins into five classes based on physiography, land use, and stream type (tributary or mainstem). The lowest NS values were rarely below 0.6, whereas the median NS for all five classes was within 0.74 to 0.96 for annual mean streamflow, 0.89 to 0.98 for mean monthly streamflow, and 0.82 to 0.98 for monthly mean streamflow. The median bias for all five classes was within –4.3 to 0.8 percent for annual mean streamflow, –6.3 to 0.5 percent for mean monthly streamflow, and –9.3 to 1.3 percent for monthly mean streamflow. The NS results combined with the percent bias results indicated a good to very good streamflow volume simulation for all subbasins. This simulation of the ACFB provides a foundation for future modeling and interpretive studies. Streamflow and other components of the hydrologic cycle simulated by PRMS can be used to inform other types of simulations; water-temperature, hydrodynamic, and ecosystem-dynamics simulations are three examples. In addition, possible future hydrologic conditions could be studied using this model in combination with land cover projections and downscaled general circulation model results.

Alabama, Florida, Georgia↗
USGS2009

Spatially referenced statistical assessment of dissolved-solids load sources and transport in streams of the Upper Colorado River Basin

The Upper Colorado River Basin (UCRB) discharges more than 6 million tons of dissolved solids annually, about 40 to 45 percent of which are attributed to agricultural activities. The U.S. Department of the Interior estimates economic damages related to salinity in excess of $330 million annually in the Colorado River Basin. Salinity in the UCRB, as measured by dissolved-solids load and concentration, has been studied extensively during the past century. Over this period, a solid conceptual understanding of the sources and transport mechanisms of dissolved solids in the basin has been developed. This conceptual understanding was incorporated into the U.S. Geological Survey Spatially Referenced Regressions on Watershed Attributes (SPARROW) surface-water quality model to examine statistically the dissolved-solids supply and transport within the UCRB. Geologic and agricultural sources of dissolved solids in the UCRB were defined and represented in the model. On the basis of climatic and hydrologic conditions along with data availability, water year 1991 was selected for examination with SPARROW. Dissolved-solids loads for 218 monitoring sites were used to calibrate a dissolved-solids SPARROW model for the UCRB. The calibrated model generally captures the transport mechanisms that deliver dissolved solids to streams of the UCRB as evidenced by R2 and yield R2 values of 0.98 and 0.71, respectively. Model prediction error is approximated at 51 percent. Model results indicate that of the seven geologic source groups, the high-yield sedimentary Mesozoic rocks have the largest yield of dissolved solids, about 41.9 tons per square mile (tons/mi2). Irrigated sedimentary-clastic Mesozoic lands have an estimated yield of 1,180 tons/mi2, and irrigated sedimentary-clastic Tertiary lands have an estimated yield of 662 tons/mi2. Coefficients estimated for the seven landscape transport characteristics seem to agree well with the conceptual understanding of the role they play in the delivery of dissolved solids to streams in the UCRB. Predictions of dissolved-solids loads were generated for more than 10,000 stream reaches of the stream network defined in the UCRB. From these estimates, the downstream accumulation of dissolved solids, including natural and agricultural components, were examined in selected rivers. Contributions from each of the 11 dissolved-solids sources were also examined at select locations in the Grand, Green, and San Juan Divisions of the UCRB. At the downstream boundary of the UCRB, the Colorado River at Lees Ferry, Arizona, monitoring site, the dissolved-solids contribution of irrigated agricultural lands and natural sources were about 45 and 57 percent, respectively. Finally, model predictions, including the contributions of natural and agricultural sources for selected locations in the UCRB, were compared with results from two previous studies.

Arizona, Colorado, Idaho, New Mexico, Utah, Wyomin↗
USGS2025

Using satellite imagery and soil data to understand occurrences and migration of soil conditions harmful to archaeological sites on Jamestown Island, Virginia

Many know Jamestown Island, Virginia, hereafter referred to as “the Island,” located near the mouth of the James River into the Chesapeake Bay, as the home of the first permanent English settlement in North America. However, the Island is home to 15,000 years’ worth of cultural artifacts and archaeological sites. In addition to its rich history, the Island is home to a variety of native plants and animals, including many rare, threatened, and endangered species. Preserving historical and natural resources is part of Colonial National Historic Park’s (COLO) enabling legislation. To this end, COLO has been seeking data to inform management decisions on how to prioritize resources to preserve archaeological sites and anticipate changes to natural systems from sea-level rise and other effects of climate change. The U.S. Geological Survey (USGS), in partnership with COLO, collected and analyzed data to help determine soil conditions detrimental to archaeological sites across the Island using a combination of soil samples and assessments of vegetative health as a proxy for soil conditions. This study combined normalized difference vegetative index raster grids spanning 8 years, 2010 to 2018, and soil data from 50 sites sampled in dry (June 2021) and wet months (March 2022) at two different soil horizons to investigate potential hazards to plant health and corrosive conditions in the unsaturated subsurface. The data suggest that access to the James River drives soil pH and soil conductivity. Areas of the Island that are subject to frequent inundation were observed to have both higher soil conductivity (as high as 4,845 millisiemens per meter [mS/m]) and lower pH (as low as 3.84). Higher soil conductivity, or salinity, and more acidity create corrosive environment, which can destroy buried artifacts and are detrimental to vegetative health. These conditions were not limited to the edges of the Island, like Black Point. Inland locations, such as the Pitch and Tar Swamp, were observed to have some of the highest conductivity values, which were likely caused by from a combination of inflow of James River water along Back Creek into the Pitch and Tar Swamp and proximity to the Visitor Center and other high-traffic areas of the Island. A difference of normalized difference vegetative index values from 2010 to 2018 raster grid appears to support this, showing an apparent loss of vegetative health in marsh grass in the Pitch and Tar Swamp. These data may inform COLO about areas of the Island that are currently most threatened by corrosive conditions and how those conditions are likely to migrate in the future.

Virginia↗
USGS2025

Modeling seawater intrusion along the Alabama coastline using physical and machine learning models to evaluate the effects of multiscale natural and anthropogenic stresses

Seawater intrusion threatens groundwater resources in coastal regions, including southern Baldwin County, Alabama, where the freshwater-saltwater interface dynamics remain poorly understood. To address this gap, this study uses combined physics-based and machine-learning models to quantify seawater intrusion caused by natural (storm surges) and anthropogenic (human activities) perturbations. The long short-term memory network and wavelet analysis were used to assess vertical aquifer vulnerabilities, revealing that the shallow part of the Coastal lowlands aquifer system (CL1) in the southern Baldwin County region is more susceptible to sea level rise and groundwater extraction than deeper aquifers. Based on these findings, a cross-sectional numerical model (physics approach) for the CL1 aquifer was developed to evaluate tidal and storm surge effects, using Tropical Storm Claudette (June 2021) as a case study. Results showed that tidal fluctuations had a minimal impact on the saltwater-freshwater interface location, whereas storm surges caused substantial inland movement, with effects lasting for nine months. The steady-state version of the three-dimensional (3D) physical model predicted seawater intrusion across the entire area, and convolutional neural network-based modeling further validated the model results. The 3D physical model was also applied to a smaller area to assess human impact on the saltwater interface due to two groundwater pumping scenarios (± 50% of the baseline pumping rate). Results revealed that a 50% increase in groundwater withdrawals caused seawater to advance ~ 320 m inland, whereas a 50% reduction led to a ~ 270-meter retreat. This study highlights the vulnerability of Alabama’s shallow coastal aquifers to seawater intrusion due to storm surges and human activities, and demonstrates that combining physics-based models with machine learning approaches can improve groundwater predictions, though its accuracy depends on the availability of site-specific data.

Alabama↗
USGS2008

Variation in biotic assemblages and stream-habitat data with sampling strategy and method in tidal segments of Highland and Marchand Bayous, Galveston County, Texas, 2007

The U.S. Geological Survey, in cooperation with the Houston-Galveston Area Council and the Galveston Bay Estuary Program under the authority of the Texas Commission on Environmental Quality, did a study in 2007 to assess the variation in biotic assemblages (benthic macroinvertebrate and fish communities) and stream-habitat data with sampling strategy and method in tidal segments of Highland Bayou and Marchand Bayou in Galveston County. Data were collected once in spring and once in summer 2007 from four stream sites (reaches) (short names Hitchcock, Fairwood, Bayou Dr, and Texas City) of Highland Bayou and from one reach (short name Marchand) in Marchand Bayou. Only stream-habitat data from summer 2007 samples were used for this report. Additional samples were collected at the Hitchcock, Fairwood, and Bayou Dr reaches (multisample reaches) during summer 2007 to evaluate variation resulting from sampling intensity and location. Graphical analysis of benthic macroinvertebrate community data using a multidimensional scaling technique indicates there are taxonomic differences between the spring and summer samples. Seasonal differences in communities primarily were related to decreases in the abundance of chironomids and polychaetes in summer samples. Multivariate Analysis of Similarities tests of additional summer 2007 benthic macroinvertebrate samples from Hitchcock, Fairwood, and Bayou Dr indicated significant taxonomic differences between the sampling locations at all three reaches. In general, the deepwater samples had the smallest numbers for benthic macroinvertebrate taxa richness and abundance. Graphical analysis of species-level fish data indicates no consistent seasonal difference in fish taxa across reaches. Increased seining intensity at the multisample reaches did not result in a statistically significant difference in fish communities. Increased seining resulted in some changes in taxa richness and community diversity metrics. Diversity increases associated with increased electrofishing intensity were relatively consistent across the two multisample electrofishing reaches (Hitchcock and Fairwood). Differences in the physical characteristics of the Highland and Marchand Bayou reaches are largely the result of the differences in channel gradient and position in the drainage network or watershed of each reach. No trees were observed on the bank adjacent to the five transects at either the Bayou Dr or Texas City reaches. Riparian vegetation at the more downstream Fairwood, Bayou Dr, and Texas City reaches was dominated by less-woody and more-herbaceous shrubs, and grasses and forbs, than at the more upstream Hitchcock and Marchand reaches. The width of the vegetation buffer was variable among all reaches and appeared to be more related to the extent of anthropogenic development in the riparian zone rather than to natural changes in the riparian buffer. Four additional transects per reach were sampled for habitat variables at Hitchcock, Fairwood, and Bayou Dr. Medians of most stream-habitat variables changed with increased sampling intensity (addition of two and four transects to the standard five transects), although none of the differences in medians were statistically significant. All habitat quality index values for the five reaches scored in the intermediate category. Increasing sampling intensity did not change the habitat quality index score for any of the reaches.

Scientific Investigations Report↗