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At least 613 records · Page 34Linked to original sources

Water pressure and ground vibrations induced by water guns near Brandon Road Lock and Dam and Lemont, Illinois

Multiple geophysical sensors were used to characterize the underwater pressure field and ground vibrations of a seismic water gun and its suitability to deter the movement of Asian carps (particularly the silver [ Hypophthalmichthys molitrix ] and bighead [ Hypophthalmichthys nobilis ] carps) while ensuring the integrity of surrounding structures. The sensors used to collect this information were blast-rated hydrophones, surface- and borehole-mounted geophones, and fixed accelerometers. Results from two separate studies are discussed in this report. The Brandon Road study took place in May 2014, in the Des Plaines River, in a concrete-walled channel downstream of the Brandon Road Lock and Dam near Joliet, Illinois. The Lemont study took place in June 2014, in a segment of the dolomite setblock-lined Chicago Sanitary and Ship Canal near Lemont, Illinois. Two criteria were evaluated to assess the potential deterrence to carp migration, and to minimize the expected effect on nearby structures from discharge of the seismic water gun. The first criterion was a 5-pound-per-square-inch (lb/in 2 ) limit for dynamic underwater pressure variations. The second criterion was a maximum velocity and acceleration disturbance of 0.75 inch per second (in/s) for sensitive machinery (such as the lock gates and pumps) and 2.0 in/s adjacent to canal walls, respectively. The criteria were based on previous studies of fish responses to dynamic pressure variations, and effects of vibrations on the structural integrity of concrete walls. The Brandon Road study evaluated the magnitude and extent of the pressure field created by two water gun configurations in the concrete-walled channel downstream of the lock where channel depths ranged from 11 to 14 feet (ft). Data from a single 80-cubic-inch (in³) water gun set at 6 ft below water surface (bws) produced a roughly cylindrical 5-lb/in 2 pressure field 20 ft in radius, oriented vertically, with the radius decreasing to less than 15 ft at the water surface. A combination of two 80-in 3 water guns set at 6 and 8 ft, respectively, produced a similarly shaped 5 lb/in 2 pressure field 30 ft in radius. Neither of the water gun configurations exceeded the given threshold of 5 lb/in 2 above the static pressure along the walls of the canal at the 700 lb/in 2 water gun input pressure. Velocity and acceleration data were collected simultaneously with the underwater pressure data to understand the response of adjacent canal walls to the water gun firings. Maximum velocity and acceleration were 0.239 in/s and 0.0188 feet per second squared (ft/s 2 ), respectively. The Lemont study replicated and expanded upon work done in 2011. The pressure field created by the water gun was evaluated in a deeper environment (about 25 ft of water depth) than that of the Brandon Road study. To replicate the 2011 study, data were collected with the same water gun placements and input pressure, but static underwater pressure monitoring was added. Two 80-in 3 water guns were suspended below a platform at depths of 4 and 14 ft bws. Pressure was lower when the gun suspended at 4 ft bws was fired as compared to firing the single gun suspended at 14 ft bws. Firing both guns simultaneously produced similar pressures to the single gun suspended at 14 ft bws. Data were collected to assess the pressure field produced by two 80-in 3 water guns separated by 80 ft and suspended at a depth of 14 ft bws. The spatial extent of the 5-lb/in 2 threshold varied substantially with gun input air pressure. Firing the water gun with an air pressure of 2,000 lb/in 2 generated a pressure field greater than the threshold at all but one location in the measured region. Additionally, the water gun with an air pressure of 1,000 lb/in 2 did not reach the threshold anywhere in the measured region. Maximum velocity and acceleration were 0.304 in/s and 0.015 ft/s 2 , respectively.

Illinois↗

Simulation of groundwater flow, 1895–2010, and effects of additional groundwater withdrawals on future stream base flow in the Elkhorn and Loup River Basins, central Nebraska—Phase three

The U.S. Geological Survey, in cooperation with the Lewis and Clark, Lower Elkhorn, Lower Loup, Lower Platte North, Lower Niobrara, Middle Niobrara, Upper Elkhorn, and the Upper Loup Natural Resources Districts, designed a study to refine the spatial and temporal discretization of a previously modeled area. This updated study focused on a 30,000-square-mile area of the High Plains aquifer and constructed regional groundwater-flow models to evaluate the effects of groundwater withdrawal on stream base flow in the Elkhorn and Loup River Basins, Nebraska. The model was calibrated to match groundwater-level and base-flow data from the stream-aquifer system from pre-1940 through 2010 (including predevelopment [pre-1895], early development [1895–1940], and historical development [1940 through 2010] conditions) using an automated parameter-estimation method. The calibrated model then was used to simulate hypothetical development conditions (2011 through 2060). Predicted changes to stream base flow based on simulated changes to groundwater withdrawal will aid in developing strategies for management of hydrologically connected water supplies. Additional wells were simulated throughout the model domain and pumped for 50 years to assess the effect of wells on aquifer depletions, including stream base flow. The percentage of withdrawal for each well after 50 years, which was compensated by aquifer reductions to stream base flow, storage, or evapotranspiration, was computed and mapped. These depletions are influenced by aquifer properties, time, and distance from the well. Stream base-flow depletion results showed that the closer the added well was to a stream, the greatest the effect on the stream base flow. Areas of stream base-flow depletion percentages greater than 80 percent were generally within 1 mile (mi) from the stream. The distance increased to 6 mi near the confluence of the Dismal and Middle Loup Rivers, and the North Loup and Calamus Rivers. The percentage of stream base-flow depletion decreased as the distance from the stream increased. Areas more than 10 mi from the stream generally had a stream base-flow depletion of 10 percent or less. Evapotranspiration depletion was largest in areas closest to streams, specifically in the Elkhorn River watershed. It was also larger in areas of interdunal wetlands within the Sand Hills. Evapotranspiration depletion was negligible in areas greater than 5 mi from a stream, with the exception of interdunal areas in Cherry, Grant, and Arthur Counties. The storage depletion percentage increased as the distance from a stream increased. Storage depletion was largest in areas between streams. Areas experiencing the smallest amount of storage depletion were adjacent to streams. Calibrated model outputs and streamflow depletion analysis are publicly available online. Accuracy of the simulations is affected by input data limitations, system simplifications, assumptions, and resources available at the time of the simulation construction and calibration. Most of the important limitations relate either to data used as simulation inputs or to data used to estimate simulation inputs. Development of the regional simulations focused on generalized hydrogeologic characteristics within the study area and did not attempt to describe variations important to local-scale conditions. These simulations are most appropriate for analyzing groundwater-management scenarios for large areas and during long periods and are not suitable for analysis of small areas or short periods.

Nebraska↗

Water-balance modeling of selected lakes for evaluating viability as long-term fisheries in Kidder, Logan, and Stutsman Counties, North Dakota

Water levels in lakes and wetlands in the central North Dakota Missouri Coteau region that were either dry or only sporadically held water since before the 1930s have been rising since the early 1990s in response to an extended wet period. The lakes have remained full since the mid-1990s, which has provided benefits to migratory waterfowl, fisheries, and wildlife. A small shift in climate conditions, either to drier or wetter conditions, can have a large effect on the lake levels of these water bodies. The North Dakota Game and Fish Department identified five lakes as candidates for sustaining long-term fisheries. The lakes are in Kidder, Stutsman, and Logan Counties, and some lakes might receive inflow from mostly freshwater aquifers, such as the Central Dakota and Streeter aquifers, and were mostly dry during the early 1990s. After about 1995, the lakes had filled up and were deep enough to sustain populations of game fish such as walleye, perch, and northern pike. Before investing in development of permanent fisheries and associated infrastructure, such as campgrounds and boat ramps, fisheries biologists needed to know if the lake levels are likely to remain high in coming decades. The U.S. Geological Survey, in cooperation with the North Dakota Game and Fish Department, developed a water-balance model to determine the effects of precipitation, evapotranspiration, and groundwater interaction on lake volumes. The model was developed using climate input data and lake volumes for the calibration period 1992 through 2016, during which historical lake volumes could be estimated using land surface elevation data and Landsat images. Long-term (1940–2018) climate input data were used with the water-balance model to reconstruct historical lake volumes prior to the calibration period, and block-bootstrapping was used to simulate potential future climate input data and lake volumes for 2017 through 2067. The simulated future lake volumes were used to estimate the likelihood of annual lake volumes remaining consistent, increasing, or decreasing through the year 2067. Of the five lakes, Sibley Lake was the most likely to sustain a long-term fishery for a period longer than 50 years. The simulated lake volumes for Alkaline Lake, Big Mallard Marsh, and Remmick Lake indicated the lakes have a 50-percent chance to fall below 75 percent of their 2016 volume by about 2030, 2067, and 2025, respectively. Simulation results for Marvin Miller Lake were substantially different compared to the other four lakes and indicated the lake has a 50-percent chance to fall below 75 percent of its 2016 volume prior to 2025.

North Dakota↗

Pecos River Basin salinity assessment, Santa Rosa Lake, New Mexico, to the confluence of the Pecos River and the Rio Grande, Texas, 2015

The elevated salinity of the Pecos River throughout much of its length is of paramount concern to water users and water managers. Dissolved-solids concentrations in the Pecos River exceed 3,000 milligrams per liter in many of its reaches in the study area, from Santa Rosa Lake, New Mexico, to the confluence of the Pecos River with the Rio Grande, Texas. The salinity of the Pecos River increases downstream and affects the availability of useable water in the Pecos River Basin. In this report, “salinity” and “dissolved-solids concentration” are considered synonymous; both terms are used to refer to the total ionic concentration of dissolved minerals in water. The sources of salinity in the Pecos River Basin are natural (geologic) and anthropogenic, including but not limited to groundwater discharge, springs, and irrigation return flows. Previous studies in the Pecos River Basin were project specific and designed to address salinity issues in specific parts of the basin; therefore, in 2015, the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers, New Mexico Interstate Stream Commission, Texas Commission on Environmental Quality, and Texas Water Development Board assessed the major sources of salinity throughout the extent of the basin where elevated salinity in the Pecos River is well documented (that is, in the drainage area of the Pecos River from Santa Rosa Lake to the confluence of the Pecos River and the Rio Grande). The goal was to gain a better understanding of how specific areas might be contributing to the elevated salinity in the Pecos River and how salinity of the Pecos River has changed over time. This assessment includes a literature review and compilation of previously published salinity-related data, which guided the collection of additional water-quality samples and streamflow gain-loss measurements. Differences in water quality of surface-water and groundwater samples, streamflow measurements, and geophysical data were assessed to gain new insights regarding sources of salinity in the Pecos River Basin and a more detailed assessment of potential areas of elevated salinity in the basin. The datasets compiled for this assessment are available in a companion data release. The literature review identified several potential sources of salinity inputs to the Pecos River in New Mexico and Texas. In New Mexico, sources of salinity inputs included sinkhole springs discharging into El Rito Creek, the Bitter Lake National Wildlife Refuge inflow to the Pecos River, inflow from the Rio Hondo, including the main channel and a restored channel at the Bitter Lake National Wildlife Refuge referred to as the “Rio Hondo spring channel,” the outflow from Lea Lake at Bottomless Lakes State Park, and the Malaga Bend region of the Pecos River. In Texas, sources of salinity inputs included Salt Creek downstream from Red Bluff Reservoir and the area near the Horsehead Crossing ford on the Pecos River. The compilation of historical water-quality data revealed a lack of consistent sampling of the same constituents at the same sites along the main stem of the Pecos River, which results in data gaps that hinder the ability to effectively analyze long-term changes in water quality that may help with the understanding of how salinity in the Pecos River has changed over time and identifying the sources of salinity in the Pecos River Basin. To help fill these data gaps, water-quality and streamflow data were collected in the study area in February 2015 by the U.S. Geological Survey. Historical water-quality data and newly collected data from February 2015 were evaluated for selected major-ion concentrations, dissolved-solids concentrations, and deuterium, oxygen, and strontium isotopes. Analysis of the data indicated several areas of increasing salinity in the Pecos River. Most notable increases were in two subreaches of the river, between Acme, N. Mex., and Artesia, N. Mex., and between Orla, Tex., and Grandfalls, Tex. Increasing sodium and chloride concentrations from Acme to Artesia coincided with changes in isotopic ratios within the Pecos River Basin. Changes in isotopic ratios in this reach indicate a likely inflow from an isotopically different source of water compared to the water in the main stem of the Pecos River, such as groundwater inflow, inflow from surface-water features distinct from the main stem of the Pecos River, or both. In the subreach between Orla and Grandfalls, an increase in dissolved-solids concentrations was observed along with a shift in isotope values, indicating that neither evaporative processes in Red Bluff Reservoir nor inflow from Salt Creek likely solely influences the salinity of the Pecos River in this subreach. The highest dissolved-solids concentrations in the Pecos River Basin were measured downstream from Grandfalls, where dissolved-solids concentrations are greater than 16,000 milligrams per liter near Iraan, Tex. Changes in isotopic values (deuterium, oxygen, and strontium) indicate mixing of different waters at several areas along the main stem of the Pecos River. The spatial distribution of the areas of interest from the literature review and the water-quality data are available in the companion data release.

Texas, New Mexico↗

Spatially referenced models of streamflow and nitrogen, phosphorus, and suspended-sediment loads in the southeastern United States

Spatially Referenced Regression On Watershed attributes (SPARROW) models were applied to describe and estimate mean-annual streamflow and transport of total nitrogen (TN), total phosphorus (TP), and suspended sediment (SS) in streams and delivered to coastal waters of the southeastern United States on the basis of inputs and management practices centered near 2012, the base year of the model. Previously published TN and TP models for 2002 served as a starting point and reference for comparison. The datasets developed for the 2012 models not only represent updates of previous conditions but also incorporate new approaches for characterizing sources and transport processes that were not available for previous models. Variability in streamflow across the southeastern United States was explained as a function of precipitation adjusted for evapotranspiration, spring discharge, and municipal and domestic wastewater discharges to streams. Results from the streamflow model were used as input to the water-quality SPARROW models, and areas with large streamflow prediction errors—urban areas and karst areas—were used to provide guidance on where additional data are needed to improve routing of flow. Variability in TN transport in Southeast streams was explained by the following five sources in order of decreasing mass contribution to streams: atmospheric deposition, agricultural fertilizer, municipal wastewater, manure from livestock, and urban land. Variable rates of TN delivery from source to stream were attributed to variation among catchments in climate, soil texture, and vegetative cover, including the extent of cover crops in the watershed. Variability in TP transport in Southeast streams was explained by the following six sources in order of decreasing mass contribution to streams: parent-rock minerals, urban land, manure from livestock, municipal wastewater, agricultural fertilizer, and phosphate mining. Varying rates of TP delivery were attributed to variation in climate, soil erodibility, depth to water table, and the extent of conservation tillage practices in the watershed. Variability in SS transport in Southeast streams was explained by variable sediment export rates for different combinations of land cover and geologic setting (for upland sources of sediment) and by gains in stream power caused by longitudinal changes in channel hydraulics (for channel sources of sediment). Sediment yields for the transitional land cover (shrub, scrub, herbaceous, and barren) varied widely depending on geologic setting and on agricultural land cover. Varying rates of SS delivery, like those for TP, were attributed to variation in climate, soil erodibility, and the extent of conservation tillage practices in the watershed, as well as to areal extent of canopy land cover in the 100-meter buffer along the channel. Relatively large uncertainty, compared to the other three models, for almost all the SS source coefficients indicates the need for caution when interpreting the results from the sediment model. TN, TP, and SS inputs to streams from sources were balanced in the models with losses from physical processes in streams and reservoirs and with water withdrawals. The losses in streams and reservoirs along with withdrawals removed 35, 44, and 65 percent of the TN, TP, and SS load, respectively, that entered streams before reaching coastal waters.

Scientific Investigations Report↗

Assessment of water availability in the Osage Nation using an integrated hydrologic-flow model

The Osage Nation of northeastern Oklahoma, conterminous with Osage County, covers about 2,900 square miles. The area is primarily rural with 62 percent of the land being native prairie grass, and much of the area is used for cattle ranching and extraction of petroleum and natural gas. Protection of water rights are important to the Osage Nation because of its reliance on cattle ranching and the potential for impairment of water quality by petroleum extraction. Additionally, the potential for future population increases, demands for water from neighboring areas such as the Tulsa metropolitan area, and expansion of petroleum and natural-gas extraction on water resources of this area further the need for the Osage Nation to better understand its water availability. Therefore, the U.S. Geological Survey, in cooperation with the Osage Nation, completed a hydrologic investigation to assess the status and availability of surface-water and groundwater resources in the Osage Nation. A transient integrated hydrologic-flow model was constructed using the U.S. Geological Survey fully integrated hydrologic-flow model called the MODFLOW One-Water Hydrologic Model. The integrated hydrologic-flow model, called the Osage Nation Integrated Hydrologic Model (ONIHM), was constructed and uses an orthogonal grid of 276 rows and 289 columns, and each grid cell measures 1,312.34 feet (ft; 400 meters) per side, with eight variably thick vertical layers that represented the alluvial and bedrock aquifers within the study area, including the alluvial aquifer, the Vamoosa-Ada aquifer, and the minor Pennsylvanian bedrock aquifers, and the confining units. Landscape and groundwater-flow processes were simulated for two periods: (1) the 1950–2014 period from January 1950 through September 2014 and (2) the forecast period from October 2014 through December 2099. The 1950–2014 period ONIHM simulated past conditions using measured or estimated inputs, and the forecast-period ONIHM simulated three separate potential forecast conditions under constant dry, average, or wet climate conditions using calibrated input values from the 1950–2014 period ONIHM. The 1950–2014 period ONIHM was calibrated by linking the Parameter Estimation software (PEST) with the MODFLOW One-Water Hydrologic Model. PEST uses statistical parameter estimation techniques to identify the best set of parameter values to minimize the difference between measured or estimated calibration targets and their simulated equivalent values (residuals). Tikhonov regularization and singular-value decomposition-assist features of PEST were used during the calibration process. The 1950–2014 period ONIHM was calibrated to 713 measured groundwater levels at 195 wells; 95,636 estimated monthly mean groundwater levels at 124 wells; 5,307 measured streamflows at 13 streamgages; and 8,679 simulated mean monthly streamflows at 10 streamgages extracted from a surface-water model by adjusting 231 parameters. The estimated groundwater-level observations and streamflows were included as observations to improve the spatial and temporal density of observation targets during calibration. The best set of parameter values obtained during the calibration process of the 1950–2014 model was then used as the input parameter values for the forecast model simulations. A comparison of the calibration targets to their corresponding simulated values indicated that the model adequately reproduced streamflows and groundwater levels for some streamgages and wells and underestimated streamflows and groundwater levels at other locations. Measured and simulated streamflows correlated adequately with a coefficient of determination of 0.938, as did water levels with a coefficient of determination of 0.795. The 1950–2014 period ONIHM underestimated certain groundwater levels and streamflows, but generally measured or estimated calibration targets correlated well with simulated equivalents, which indicated that the model can adequately simulate the response of the hydrologic system to stresses in the 1950–2014 and forecast periods. In the 1950–2014 period ONIHM, the calibrated mean horizontal hydraulic conductivity for layer 1 alluvial aquifer was 30.7 feet per day, and the seven lower layers had a calibrated mean horizontal hydraulic conductivity of less than 3.3 feet per day. The mean calibrated groundwater-level residual was 16.6 ft, and the mean calibrated streamflow residual of the Arkansas River at Ralston, Oklahoma, streamgage (U.S. Geological Survey station 07152500) was within 6 percent (373 cubic feet per second) of mean measured streamflow for the 1950–2014 period ONIHM. The ONIHM simulated landscape fluxes of precipitation; groundwater applied by irrigation wells; evapotranspiration from precipitation, groundwater, and irrigation; runoff from precipitation; and deep percolation from precipitation. The largest loss of water from the landscape was evapotranspiration from precipitation with a calibrated mean annual outflow of 32 inches (in.): mean annual precipitation was about 36 in. Calibrated mean annual runoff and deep percolation (recharge to the water table) rates were 4.7 inches per year (in/yr) and 0.70 in/yr, respectively, for the 1950–2014 period ONIHM. The calibrated 1950–2014 period ONIHM groundwater fluxes included net farm net recharge (calculated as the difference between the inflow of recharge to the water table and the outflow of evapotranspiration from the water table such that negative values indicate that evapotranspiration from the water table was greater than deep percolation [recharge to the water table] and vice versa). Net farm net recharge was the largest flux from the groundwater system with a mean annual net outflow of 153.4 cubic feet per second. Stream leakage was the largest flux to the groundwater system with a mean annual net inflow of 152.5 cubic feet per second, indicating that, on average, the groundwater/surface-water interaction was a “losing” system where stream water leaked into the subsurface and recharged the water table. Simulated monthly trends demonstrated that net stream leakage was the largest inflow to the groundwater-flow system for 10 of the 12 months; for the other 2 months (January and March), farm net recharge (January) and net storage (March) were the largest inflow to the groundwater-flow system. A saline groundwater interface map was created for the study and compared to the water levels from the final stress period of the 1950–2014 model to identify the presence of fresh/marginal groundwater throughout the study area. Fresh/marginal groundwater was characterized as groundwater with less than 1,500 milligrams per liter of total dissolved solids. Fresh/marginal groundwater thickness ranged from 0 to 438.2 ft within the study area. The thickest regions of fresh/marginal groundwater were in the eastern part of the study area near Sand Creek, Bird Creek, and Hominy Creek and in the Arkansas River alluvial aquifer in the region downstream from the Arkansas River at Ralston, Okla. Like the 1950–2014 model, forecast model results for the landscape indicated that transpiration from precipitation was the largest flux out of the landscape for all three forecasts, constituting 77, 73, and 58 percent of precipitation for the dry, average, and wet forecasts, respectively. The dry and average forecast landscape fluxes demonstrated similar trends and magnitudes, whereas the wet forecast landscape fluxes indicated the largest changes compared to the average forecast fluxes. Most notably, runoff increased from a mean of 1.1 and 1.6 in/yr for the dry and average forecasts, respectively, to 10 in/yr for the wet forecast. Similar changes occurred for the other wet forecast landscape fluxes. The calibrated 1950–2014 period ONIHM simulated three forecasts to assess the effects of potential climatic changes on the hydrologic system from October 2014 to December 2099. The three forecasts simulated theoretical dry, average, and wet conditions using precipitation and potential evapotranspiration datasets from selected years in the calibrated 1950–2014 period ONIHM. Annual precipitation amounts were 26.89, 35.47, and 50.73 in. for the dry, average, and wet forecasts, respectively. Groundwater-flow component forecast results indicated that stream leakage is always a net inflow to the groundwater-flow system for dry, average, and wet conditions, meaning the study area stream network is always predominantly a “losing” regime where stream water infiltrates into the underlying aquifer. Storage was only a net outflow from the groundwater-flow system and indicated a replenishment to groundwater storage that resulted in an increase in groundwater levels only during the wet forecast. Further, these gains in groundwater storage for the wet forecast occurred only during February through June. Mean fresh/marginal groundwater saturated thicknesses were 125 and 126 ft for the dry and average forecast conditions, respectively, and wet forecast average thickness was 145 ft and ranged from 0 to 443 ft. The spatial extents of fresh/marginal groundwater at the end of the dry, average, and wet forecast model periods (December 2099) did not change substantially from the end of the 1950–2014 model period (September 2014).

Kansas, Oklahoma↗

Simulation of flow and eutrophication in the central Salem River, New Jersey

The central Salem River in New Jersey is subject to periods of water-quality impairment, marked by elevated concentrations of phosphorus and chlorophyll- a , and low concentrations of and large diurnal swings in concentrations of dissolved oxygen. These seasonal eutrophic conditions are controlling factors for water quality in lower reaches, where the river is more lacustrine than in upper reaches, as a result of downstream damming. This biological productivity is supported by nutrient wash-off from agricultural areas in the surrounding watershed. To investigate this impairment, flow measurement and water-quality sampling were conducted during 2007–08 in support of development of a one-dimensional surface-water-quality model that simulates nutrient cycling and transformation processes. The U.S. Geological Survey, in cooperation with the New Jersey Department of Environmental Protection, used the U.S. Environmental Protection Agency Water Quality Analysis Simulation Program (WASP) to develop a receiving-water-quality model of the central Salem River between Woodstown and Deepwater, New Jersey, from April 2007 to October 2008. The main-stem river and largest tributary were simulated. In the flow model, kinematic wave flow is used to simulate flow in upper reaches and ponded weir flow is used to simulate flow in lower reaches. The water-quality model makes use of a mass-balance equation to simulate the fate and transport of nutrients, phytoplankton chlorophyll- a , dissolved oxygen, and oxygen demands (an indicator rather than a substance) in the river. Model input included channel characteristics, boundary conditions for flow and water quality, environmental parameters, vertical dispersion coefficients, settling rates, and kinetic constants. Inputs were estimated where field data were lacking, notably for tributary flows and nutrient loads. The model was calibrated to observed flow variables and concentrations of dissolved oxygen, chlorophyll- a , and nutrients at sampling locations, with emphasis on growing-season conditions. Calibration was achieved through graphical and statistical comparison of simulated results to observed data. Sensitivity analyses were performed, and model limitations and applicability were evaluated. Simulated results closely matched observed data in most cases, although some were overpredicted slightly. The most important causes of overprediction were estimated tributary flows for the flow model and estimated tributary watershed loads for the water-quality model. Calibration of dissolved-oxygen concentrations was closer, and predicted diurnal variations were consistent with high algal photosynthesis/respiration, although lack of continuous dissolved-oxygen data precluded verifying these predictions. A similar caveat applies to predicted diurnal variations in chlorophyll- a . Simulated limitations on algal growth were consistent with those based on observed data and indicated phosphorus was the main limiting nutrient, except during certain periods when nitrogen was limiting. Two water-quality management scenarios were simulated with the model to assess the effect of point- and nonpoint-source nutrient reductions on water-quality conditions in the river. Scenarios involved (1) a return of watershed land use to predevelopment natural conditions and (2) an extreme reduction in nutrient input. Although the extreme-nutrient-reduction scenario yielded improvements in water quality, the natural-conditions scenario yielded the largest improvements as indicated by minimal violations of surface-water-quality standards or thresholds. However, years may be needed to attain the full benefit of these management scenarios as a result of accumulation of phosphorus and organic carbon in riverbed sediments in lacustrine reaches. The results of this study indicate that the quality of water in the central Salem River will improve if management policies that mitigate the effects of nutrient-loading practices in the watershed, particularly those related to agriculture, are implemented.

New Jersey↗

Effect of uncertainty of discharge data on uncertainty of discharge simulation for the Lake Michigan Diversion, northeastern Illinois and northwestern Indiana

Simulation models of watershed hydrology (also referred to as “rainfall-runoff models”) are calibrated to the best available streamflow data, which are typically published discharge time series at the outlet of the watershed. Even after calibration, the model generally cannot replicate the published discharges because of simplifications of the physical system embedded in the model structure and uncertainties of the input data and of the estimated model parameters, which, although optimized for the given calibration data, remain uncertain. The input data errors are caused by uncertainties in the forcing data, such as precipitation and other climatological data, and in the published discharges used for calibration. In the numerical algorithms used for calibration, the published discharges are often assumed to be without error, but they are themselves uncertain, typically having been computed using ratings, which are models fitted to uncertain discharge measurements. In this study, uncertainty of published daily discharge data and how the discharge uncertainty is transmitted to the parameter values of the Hydrological Simulation Program–FORTRAN (HSPF) rainfall-runoff model and to the simulated discharge at both calibration and prediction locations were investigated for the Lake Michigan diversion in northeastern Illinois and northwestern Indiana. The HSPF model used in this study is used by the U.S. Army Corps of Engineers as part of quantifying the diversion of water from Lake Michigan by the State of Illinois. In this study, the model is calibrated jointly at two watersheds in the study area; the resulting model is considered the base model in this study. Seven other gaged watersheds in the study area are used for testing predictive simulations. A Bayesian rating curve estimation (BaRatin) approach, the BaRatin stage-period-discharge (SPD) method, was used to estimate the uncertainty of the published discharge from the calibration watersheds. To characterize the effect of the discharge uncertainty on parameter values, the HSPF model parameters were recalibrated to 17 nonrandomly selected pairs of discharge series from the BaRatin SPD analysis. To provide an indicator of the effect of parameter uncertainty to compare to the effect of discharge uncertainty, 1,000 parameter sets also were randomly generated from the estimated parameter covariance matrix of the base model. The recalibrated and random parameter sets were then used in HSPF simulations of discharge at the two calibration watersheds and at the seven prediction watersheds. Selected discharge summary statistics—the period-of-study (POS, water years 1997 to 2015) mean discharge, selected flow-duration curve (FDC) quantiles, and water year mean discharges—are used to characterize the variability between simulated and published discharge. A normalized variability index ( V N ) is used as a measure of the uncertainty of flow statistics arising from the uncertainty of the sources considered in this study. When this index is at least 1, the variability of the simulations is large enough to explain the median error between simulated and published values, although offsetting errors from other sources are also likely. When the index is appreciably less than 1, the variability of the simulations is clearly insufficient to explain the median error between simulated and published values. At the two calibration watersheds and for results of the two simulation sets considered together, the V N values ranged from 0.2 to 0.8 for POS mean discharge, from 0.3 to 0.6 in the median for a set of FDC quantiles, and from 0.1 to 0.2 in the median for water year mean discharges. These values indicate that substantial uncertainty remains unexplained. Even though two watersheds were used in calibration, that calibration was highly constrained because it was applied to the watersheds simultaneously and was subject to parameter regularization that constrained the adjustment of the parameters from their initial values. These constraints were applied to avoid overfitting to the calibration watersheds and thus to increase the likelihood that the resulting parameters would give accurate results at watersheds not used in the calibration, but they created a parameter transfer error in the calibration watershed results shown by the balancing of errors between the two watersheds. Additional remaining error sources include model structural error and meteorological forcing error to the degree that the calibration was unable to adjust the parameters to account for these errors. At the prediction watersheds, the corresponding V N values were almost always substantially lower than those values at the calibration watersheds. This result is expected because the prediction watersheds have additional uncertainty, including parameter transfer error. The work described in this report provides preliminary estimates of a limited range of sources of error in predicted discharge uncertainty. Future work would be beneficial to obtain a better statistical characterization of the effect of the uncertainty of calibration discharge series and to address additional sources of uncertainty, such as from precipitation input data used in calibration and prediction and from structural (model) errors.

Illinois, Indiana↗

Simulated mean monthly groundwater-transported nitrogen loads in watersheds on the north shore of Long Island Sound, 1993–2022

Elevated nitrogen loads are pervasive in the Long Island Sound, an estuary that receives freshwater and nutrients from both surface-water and groundwater discharge. Surface-water nitrogen loads to the Long Island Sound are relatively well characterized, but less is known about groundwater-transported nitrogen loads. Prior work on the northern shore of Long Island Sound (Connecticut and areas of New York and Rhode Island) suggested that groundwater travel times are relatively short (median less than 2 years) and that decade-long nutrient legacies are not widespread. Because the travel times are short, groundwater flow and nutrient loads likely vary substantially between months. In the current study, the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency’s Long Island Sound Study and the Connecticut Department of Energy and Environmental Protection, developed a set of models to better characterize spatial and temporal patterns of groundwater-transported nitrogen loading from atmospheric deposition, septic systems, and fertilizers within the study area. The models provide an estimate, with uncertainty, of groundwater-transported nitrogen loads in the study area, filling a key gap in the nitrogen budget for Long Island Sound. The models also highlight the spatial and temporal variation in nitrogen loading throughout the study area. The modeling workflow involved four models. (1) A soil-water-balance model was developed by using the Soil-Water-Balance software to simulate groundwater recharge across the study area for water years 2005 through 2022. The simulated mean monthly recharge from the soil-water-balance model was used as input into a groundwater-flow model. (2) The groundwater-flow model was developed by using the MODFLOW 6 software and data for water years 1993 through 2022 and simulates average monthly hydrologic conditions. The groundwater-flow model was calibrated by using the Iterative Ensemble Smoother method within the PEST++ software. The Iterative Ensemble Smoother method generates an ensemble of sets of parameter values, with each set producing reasonable simulated hydrologic parameter values. (3) An ensemble of MODPATH particle-tracking simulations were run to generate particle flow paths and travel times, with each simulation using a different set of the flow model parameters. (4) A nitrogen load model uses the MODPATH simulation outputs to track nitrogen from the land surface through multiple attenuation zones until it discharges into fresh or saline surface water. As with the groundwater-flow model, the nitrogen model simulated average monthly groundwater-transported nitrogen loads for water years 1993 through 2022. One novel aspect of the nitrogen load model is that the nitrogen attenuation parameters were calibrated to observed nitrogen loads. Across the ensemble of simulated nitrogen loads, the median study-area-wide monthly simulated nitrogen loads from the aquifer to Long Island Sound throughout the year ranged from 900 to 18,600 kilograms of nitrogen per day, with a median load of 5,100 kilograms of nitrogen per day. The simulated loads were based on average monthly conditions for water years 1993 through 2022. Loads were highest during the winter and early spring and lowest during the late summer. However, simulated travel times for groundwater and nitrogen loads discharged to Long Island Sound during summer were longer than travel times for groundwater and loads discharged during the winter, indicating that, on average, groundwater discharged during summer traveled along different, and longer, flow paths, than groundwater discharged during winter. This indicates that summer loads would respond more slowly to changes in nitrogen inputs at the water table than winter loads. Over the entire study area, approximately 15 percent of the simulated load is from atmospheric deposition sources, 30 to 40 percent is from fertilizer, and 50 to 60 percent is from septic systems. The final analysis of the study involved simulating the change in groundwater-transported nitrogen load in response to upgrading septic systems or reducing fertilizing inputs to areas of turf grass. Both management interventions reduced the groundwater-transported nitrogen load, and reductions were greater in areas with greater loads from septic systems or turf-grass fertilizers. The delay between management actions and substantial reductions in groundwater-transported nitrogen loads varied seasonally; loads during the late summer months remained elevated longer than the winter loads.

Connecticut, Rhode Island↗

Assessing spatial variability of nutrients, phytoplankton, and related water-quality constituents in the California Sacramento–San Joaquin Delta at the landscape scale—Comparison of four (2018, 2020, 2021, 2022) spring high-resolution mapping surveys

Executive Summary This report summarizes results from boat-based, high-resolution water-quality mapping surveys completed before, during, and after upgrades to the EchoWater Resource Recovery Facility (EchoWater Facility), the regional wastewater facility for the City of Sacramento and surrounding areas, near Elk Grove, California. Surveys were completed in the tidal aquatic environments of the Sacramento–San Joaquin Delta (Delta) in spring (May or June) 2018, 2020, 2021, and 2022. In each survey, a suite of in situ sensors were used to continuously (one measurement per second) measure water-quality conditions, nutrients, phytoplankton abundance, and species composition. In addition to in situ data collection, discrete water samples were collected about every 2 miles while underway for determination of phosphate, ammonium, and nitrate concentration. The boat stopped at about 30 locations to collect discrete samples for a suite of additional analytes, including phytoplankton enumeration. The four surveys represent snapshots in time across different phases of the EchoWater Facility Biological Nutrient Reduction (BNR) upgrade. The May 2018 survey represents conditions before the upgrade. The second survey (June 2020) represents conditions after implementation of the Nitrifying Sidestream Treatment. The third survey (May 2021) was completed immediately after the completion of the BNR upgrade and represents a transitional period, and the final survey (May 2022) represents post-upgrade conditions. Relevant hydrologic and climatic context such as water-year type, X 2 position (the distance from the Golden Gate Bridge to the point upstream where bottom salinity is 2 parts per thousand; Jassby and others, 1995), water export to import ratio, and management actions like the Delta Cross Channel gate operations are presented for each survey so they may be considered in comparisons among surveys. Differences in water-quality parameters, like turbidity, temperature, salinity, pH, and dissolved oxygen (DO) improve understanding of nutrient cycling and phytoplankton dynamics. Because the Delta is a complex system, we divided the study area into hydrologic zones to better examine general trends and obtain a broadscale view of differences among the 4 study years. Results are presented for each survey and parameter using box plots to compare the different hydrologic zones. We also present each parameter using contour maps by survey to display gradients across the system. The most evident change to water quality in the Delta across surveys is related to the EchoWater Facility BNR upgrade, which included nitrification and denitrification processes. Through this upgrade, effluent ammonium (NH 4 + ) concentrations were reduced by more than 95 percent (from about 2,000 micromolars [μM] to below the reporting limit of 35 μM), and nitrate (NO 3 − ) concentrations increased from near zero to about 500 μM; therefore, the concentration of dissolved inorganic nitrogen (DIN; the sum of NH 4 + and NO 3 − ) in the effluent was reduced by about 75 percent between May 2018 and May 2022. The BNR upgrade resulted in a reduction in NH 4 + concentrations in aquatic habitats immediately below the facility, designated as the “north Delta tidal transition zone” (Bergamaschi and others, 2024), from about 30 μM pre-upgrade to near zero during the 2022 spring survey, whereas effluent NO 3 − increased from median concentrations of about 7 μM to about 15 μM. Because of the reduced effluent nitrogen loads and variability in Sacramento River nitrogen loads from upstream sources, DIN concentrations in the north Delta tidal transition zone decreased from a median of 53.3 μM in 2018 to 35.3 μM in 2020, 20.7 μM in 2021, and 11.3 μM in 2022 during the spring surveys. The changes in DIN concentration and form observed in the north Delta tidal transition zone after the EchoWater Facility upgrade extended downstream but were rapidly altered by hydrologic mixing, biogeochemical processes, and other nutrient source inputs. Most of the Delta indicated near-zero concentrations of NH 4 + 1 year after the completion of the EchoWater Facility upgrades represented by the 2022 survey. Exceptions to this finding were observed in the San Joaquin River near Stockton and in Suisun Bay, indicating there are NH 4 + inputs to these locations from other sources (for example, Stockton Regional Wastewater Control Facility and Central Contra Costs Sanitary District wastewater treatment plants or agricultural and urban runoff). Although there was an increase in NO 3 − concentrations in the north Delta tidal transition zone after the upgrade, increases in NO 3 − in other zones were not apparent, presumably because nitrification of effluent derived ammonium was no longer a source of NO 3 − . Concentrations of DIN in many Delta zones were lower in 2022 compared to 2018 and 2020, with concentrations near or below what is considered potentially nitrogen limiting conditions for phytoplankton growth in the North Delta tidal transition zone and the Cache Slough complex channel system. Unrelated to the EchoWater Facility upgrade, NO 3 − and therefore DIN concentrations increased in the San Joaquin River near Stockton and in adjacent water bodies by survey date (likely associated with increasing drought conditions). The Mokelumne River had low DIN concentrations, except in 2018 when the Delta Cross Channel was open, which allowed nutrient-rich Sacramento River water to flow into this section of the river. Data from these surveys also support the hypothesis that nutrient drawdown during phytoplankton blooms may create localized nitrogen limiting conditions. The BNR upgrade resulted in lower effluent phosphate (PO 4 3− ) concentrations, which lowered PO 4 3− concentrations in some zones of the Delta during the four spring surveys; however, PO 4 3− concentrations throughout the Delta remained above 0.3 μM, indicating that primary productivity was not limited by phosphorous availability. DIN and PO 4 3− decreased after the upgrade in many areas of the Delta, and the DIN to dissolved inorganic phosphorus (DIN:DIP) ratio remained similar to pre-upgrade conditions and was often below the Redfield Ratio of 16, indicating nitrogen is more likely to limit phytoplankton growth than phosphorous. Inputs of dissolved organic carbon (DOC) from the EchoWater Facility are a minor source of this constituent to the Delta, so the upgrade had little to no effect on DOC concentrations across the Delta. Because phytoplankton abundance and species composition in the Delta are shaped by multiple factors other than nutrients (for example, light availability, temperature, salinity, and predation), it is important to consider these factors (as well as long-term monitoring) in addition to the EchoWater Facility upgrade. Although phytoplankton populations were low across much of the Delta during the spring surveys, several localized phytoplankton blooms (defined here as greater than 15 micrograms per liter [μg/L] of chlorophyll) provide insight into conditions that may favor the growth of beneficial and harmful species.

Callifornia↗

A probabilistic assessment methodology for the evaluation of geologic energy storage capacity—Natural gas storage in depleted hydrocarbon reservoirs

The need for energy storage, particularly underground, where capacity and duration may far exceed battery storage technologies, is especially relevant given the increasing demands for reliable power alongside the development of intermittent renewable electricity sources. Geologic energy storage facilities already exist, and expanded use would enable storing gases such as methane and hydrogen. In 2018, a National Academies of Sciences, Engineering, and Medicine report, “Future Directions for the U.S. Geological Survey's Energy Resources Program,” recommended that the U.S. Geological Survey (USGS) prioritize assessing underground energy storage in geologic formations in the United States. The U.S. Geological Survey has since developed a methodology for assessing natural gas storage capacities in depleted hydrocarbon reservoirs on a national scale. The methodology introduced in this report prescribes three approaches for calculating gas storage capacity. This methodology relies on the availability of input data, including cumulative hydrocarbon production records, reservoir petrophysical properties, and reservoir pressure data. Assessment inputs can be obtained from public, State-level databases and propriety national-scale databases, although the use of analogs could be warranted for estimating input parameters. Probabilistic assessment results are aggregated to play, petroleum province, regional, and national scales. The steps defined in this report are demonstrated on the Michigan Basin Province, which includes the Mississippian Sandstone Gas Play and the Clinton Structural Play. This methodology could be used to systematically and consistently assess hydrocarbon plays and provinces for natural gas storage capacity across the United States.

Michigan↗

Estimating Prediction Uncertainty from Geographical Information System Raster Processing: A User's Manual for the Raster Error Propagation Tool (REPTool)

The U.S. Geological Survey Raster Error Propagation Tool (REPTool) is a custom tool for use with the Environmental System Research Institute (ESRI) ArcGIS Desktop application to estimate error propagation and prediction uncertainty in raster processing operations and geospatial modeling. REPTool is designed to introduce concepts of error and uncertainty in geospatial data and modeling and provide users of ArcGIS Desktop a geoprocessing tool and methodology to consider how error affects geospatial model output. Similar to other geoprocessing tools available in ArcGIS Desktop, REPTool can be run from a dialog window, from the ArcMap command line, or from a Python script. REPTool consists of public-domain, Python-based packages that implement Latin Hypercube Sampling within a probabilistic framework to track error propagation in geospatial models and quantitatively estimate the uncertainty of the model output. Users may specify error for each input raster or model coefficient represented in the geospatial model. The error for the input rasters may be specified as either spatially invariant or spatially variable across the spatial domain. Users may specify model output as a distribution of uncertainty for each raster cell. REPTool uses the Relative Variance Contribution method to quantify the relative error contribution from the two primary components in the geospatial model - errors in the model input data and coefficients of the model variables. REPTool is appropriate for many types of geospatial processing operations, modeling applications, and related research questions, including applications that consider spatially invariant or spatially variable error in geospatial data.

Techniques and Methods↗

Kendall-Theil Robust Line (KTRLine--version 1.0)-A Visual Basic Program for Calculating and Graphing Robust Nonparametric Estimates of Linear-Regression Coefficients Between Two Continuous Variables

The Kendall-Theil Robust Line software (KTRLine-version 1.0) is a Visual Basic program that may be used with the Microsoft Windows operating system to calculate parameters for robust, nonparametric estimates of linear-regression coefficients between two continuous variables. The KTRLine software was developed by the U.S. Geological Survey, in cooperation with the Federal Highway Administration, for use in stochastic data modeling with local, regional, and national hydrologic data sets to develop planning-level estimates of potential effects of highway runoff on the quality of receiving waters. The Kendall-Theil robust line was selected because this robust nonparametric method is resistant to the effects of outliers and nonnormality in residuals that commonly characterize hydrologic data sets. The slope of the line is calculated as the median of all possible pairwise slopes between points. The intercept is calculated so that the line will run through the median of input data. A single-line model or a multisegment model may be specified. The program was developed to provide regression equations with an error component for stochastic data generation because nonparametric multisegment regression tools are not available with the software that is commonly used to develop regression models. The Kendall-Theil robust line is a median line and, therefore, may underestimate total mass, volume, or loads unless the error component or a bias correction factor is incorporated into the estimate. Regression statistics such as the median error, the median absolute deviation, the prediction error sum of squares, the root mean square error, the confidence interval for the slope, and the bias correction factor for median estimates are calculated by use of nonparametric methods. These statistics, however, may be used to formulate estimates of mass, volume, or total loads. The program is used to read a two- or three-column tab-delimited input file with variable names in the first row and data in subsequent rows. The user may choose the columns that contain the independent (X) and dependent (Y) variable. A third column, if present, may contain metadata such as the sample-collection location and date. The program screens the input files and plots the data. The KTRLine software is a graphical tool that facilitates development of regression models by use of graphs of the regression line with data, the regression residuals (with X or Y), and percentile plots of the cumulative frequency of the X variable, Y variable, and the regression residuals. The user may individually transform the independent and dependent variables to reduce heteroscedasticity and to linearize data. The program plots the data and the regression line. The program also prints model specifications and regression statistics to the screen. The user may save and print the regression results. The program can accept data sets that contain up to about 15,000 XY data points, but because the program must sort the array of all pairwise slopes, the program may be perceptibly slow with data sets that contain more than about 1,000 points.

Techniques and Methods↗

User Guide for HUFPrint, A Tabulation and Visualization Utility for the Hydrogeologic-Unit Flow (HUF) Package of MODFLOW

This report documents HUFPrint, a computer program that extracts and displays information about model structure and hydraulic properties from the input data for a model built using the Hydrogeologic-Unit Flow (HUF) Package of the U.S. Geological Survey's MODFLOW program for modeling ground-water flow. HUFPrint reads the HUF Package and other MODFLOW input files, processes the data by hydrogeologic unit and by model layer, and generates text and graphics files useful for visualizing the data or for further processing. For hydrogeologic units, HUFPrint outputs such hydraulic properties as horizontal hydraulic conductivity along rows, horizontal hydraulic conductivity along columns, horizontal anisotropy, vertical hydraulic conductivity or anisotropy, specific storage, specific yield, and hydraulic-conductivity depth-dependence coefficient. For model layers, HUFPrint outputs such effective hydraulic properties as horizontal hydraulic conductivity along rows, horizontal hydraulic conductivity along columns, horizontal anisotropy, specific storage, primary direction of anisotropy, and vertical conductance. Text files tabulating hydraulic properties by hydrogeologic unit, by model layer, or in a specified vertical section may be generated. Graphics showing two-dimensional cross sections and one-dimensional vertical sections at specified locations also may be generated. HUFPrint reads input files designed for MODFLOW-2000 or MODFLOW-2005.

Techniques and Methods↗

ModelMuse - A Graphical User Interface for MODFLOW-2005 and PHAST

ModelMuse is a graphical user interface (GUI) for the U.S. Geological Survey (USGS) models MODFLOW-2005 and PHAST. This software package provides a GUI for creating the flow and transport input file for PHAST and the input files for MODFLOW-2005. In ModelMuse, the spatial data for the model is independent of the grid, and the temporal data is independent of the stress periods. Being able to input these data independently allows the user to redefine the spatial and temporal discretization at will. This report describes the basic concepts required to work with ModelMuse. These basic concepts include the model grid, data sets, formulas, objects, the method used to assign values to data sets, and model features. The ModelMuse main window has a top, front, and side view of the model that can be used for editing the model, and a 3-D view of the model that can be used to display properties of the model. ModelMuse has tools to generate and edit the model grid. It also has a variety of interpolation methods and geographic functions that can be used to help define the spatial variability of the model. ModelMuse can be used to execute both MODFLOW-2005 and PHAST and can also display the results of MODFLOW-2005 models. An example of using ModelMuse with MODFLOW-2005 is included in this report. Several additional examples are described in the help system for ModelMuse, which can be accessed from the Help menu.

Techniques and Methods↗

SWB Version 2.0—A soil-water-balance code for estimating net infiltration and other water-budget components

The U.S. Geological Survey’s Soil-Water-Balance (SWB) code was developed as a tool to estimate distribution and timing of net infiltration out of the root zone by means of an approach that uses readily available data and minimizes user effort required to begin a SWB application. SWB calculates other components of the water balance, including soil moisture, reference and actual evapotranspiration, snowfall, snowmelt, canopy interception, and crop-water demand. SWB is based on a modified Thornthwaite-Mather soil-water-balance approach, with components of the soil-water balance calculated at a daily time step. Net-infiltration calculations are computed by means of a rectangular grid of computational elements, which allows the calculated infiltration rates to be imported into grid-based regional groundwater-flow models. SWB makes use of gridded datasets, including datasets describing hydrologic soil groups, moisture-retaining capacity, flow direction, and land use. Climate data may be supplied in gridded or tabular form. The SWB 2.0 code described in this report extends capabilities of the original SWB version 1.0 model by adding new options for representing physical processes and additional data input and output capabilities. New methods included in SWB 2.0 allow for direct gridded input of externally calculated water-budget components (fog, septic, and storm-sewer leakage), simulation of canopy interception by several alternative processes, and a crop-water demand method for estimating irrigation amounts. New input and output capabilities allow for grids with differing spatial extents and projections to be combined without requiring the user to resample and resize the grids before use.

Techniques and Methods↗

Section 1. Simulation of surface-water integrated flow and transport in two-dimensions: SWIFT2D user's manual

A numerical model for simulation of surface-water integrated flow and transport in two (horizontal-space) dimensions is documented. The model solves vertically integrated forms of the equations of mass and momentum conservation and solute transport equations for heat, salt, and constituent fluxes. An equation of state for salt balance directly couples solution of the hydrodynamic and transport equations to account for the horizontal density gradient effects of salt concentrations on flow. The model can be used to simulate the hydrodynamics, transport, and water quality of well-mixed bodies of water, such as estuaries, coastal seas, harbors, lakes, rivers, and inland waterways. The finite-difference model can be applied to geographical areas bounded by any combination of closed land or open water boundaries. The simulation program accounts for sources of internal discharges (such as tributary rivers or hydraulic outfalls), tidal flats, islands, dams, and movable flow barriers or sluices. Water-quality computations can treat reactive and (or) conservative constituents simultaneously. Input requirements include bathymetric and topographic data defining land-surface elevations, time-varying water level or flow conditions at open boundaries, and hydraulic coefficients. Optional input includes the geometry of hydraulic barriers and constituent concentrations at open boundaries. Time-dependent water level, flow, and constituent-concentration data are required for model calibration and verification. Model output consists of printed reports and digital files of numerical results in forms suitable for postprocessing by graphical software programs and (or) scientific visualization packages. The model is compatible with most mainframe, workstation, mini- and micro-computer operating systems and FORTRAN compilers. This report defines the mathematical formulation and computational features of the model, explains the solution technique and related model constraints, describes the model framework, documents the type and format of inputs required, and identifies the type and format of output available.

Techniques and Methods↗

User’s guide for Assessment Tract Aggregation GUI (ATA GUI)—A graphical user interface for the AggtEx.fn R script

The U.S. Geological Survey three-part method for mineral resource assessments estimates numbers of undiscovered mineral deposits as probability distributions in geologically defined regions termed “permissive tracts.” This report describes a graphical user interface (GUI) script developed in open-source statistical software (R) that aggregates estimated undiscovered deposits of a given type from two or more permissive tracts using the AggtEx.fn R script. The AggtEx.fn R script aggregates undiscovered deposit estimates assuming independence, total dependence, or some degree of correlation among aggregated areas, given a user-specified correlation matrix. The script outputs three sets of aggregated estimates based on those three assumptions. The GUI script described in this report, Assessment Tract Aggregation GUI (ATA GUI), provides an easy-to-use tool that supports implementation of the AggtEx.fn R script, installation of the R packages needed to run the application, and creation of a combined input file from individual files generated by the MapMark4GUI software. Users can also use EMINERS output information by creating a file of output values following the MapMark4GUI output file format. The probabilistic estimates of aggregated undiscovered deposits produced by ATA GUI can be used as input for MapMark4GUI to estimate contained resources for the aggregated tracts. MapMark4GUI uses Monte Carlo simulation to combine undiscovered deposit estimates with tonnage and grade models to simulate undiscovered mineral resources for a region of interest. This simulation includes the amounts of commodities and rock that could be present within a permissive tract. This report includes instructions on installing and running the ATA GUI script and describes the input and output files used and created during the aggregation process.

Techniques and Methods↗