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At least 91 records · Page 5Linked to original sources
USGS1984

Ground-water models as a management tool in Florida

Highly sophisticated computer models provide powerful tools for analyzing historic data and for simulating future water levels, water movement, and water chemistry under stressed conditions throughout the ground-water system in Florida. Models that simulate the movement of heat and subsidence of land in response to aquifer pumping also have potential for application to hydrologic problems in the State. Florida, with 20 ground-water modeling studies reported since 1972, has applied computer modeling techniques to a variety of water-resources problems. Models in Florida generally have been used to provide insight to problems of water supply, contamination, and impact on the environment. The model applications range from site-specific studies, such as estimating contamination by wastewater injection at St. Petersburg, to a regional model of the entire State that may be used to assess broad-scale environmental impact of water-resources development. Recently, groundwater models have been used as management tools by the State regulatory authority to permit or deny development of water resources. As modeling precision, knowledge, and confidence increase, the use of ground-water models will shift more and more toward regulation of development and enforcement of environmental laws. (USGS)

Water-Resources Investigations Report↗
USGS2020

Time-series model, statistical methods, and software documentation for R–QWTREND—An R package for analyzing trends in stream-water quality

As part of a U.S. Geological Survey water-quality study started in 2018, in cooperation with the International Joint Commission, North Dakota Department of Environmental Quality, and Minnesota Pollution Control Agency, a publicly available software package called R–QWTREND was developed for analyzing trends in stream-water quality. The R–QWTREND package is a collection of functions written in R, an open source language and a general environment for statistical computing and graphics. The package uses a parametric time-series model to express logarithmically transformed concentration in terms of flow-related variability, trend, and serially correlated model errors. Flow-related variability captures natural variability in concentration on the basis of concurrent and antecedent streamflow. The trend identifies systematic changes in concentration in terms of potential step trends, piecewise monotonic trends, or user-specified trends. Maximum likelihood estimation is used to estimate model parameters and determine the best-fit trend model. This report describes the time-series model and statistical methodology behind R–QWTREND and provides formal documentation for installing and using the package.

Open-File Report↗
USGS1976

Lakes Marion-Moultrie stream system investigation, South Carolina : Part II-Simulation Studies

A stream-reservoir model was developed to simulate the operation of the Lakes Marion-Moultrie, South Carolina, reservoir system. The reservoir system is operated under the assumption of a 3-day prior knowledge of inflows. This information is attainable from the ooperational reservoir-inflow forecasting model developed in the Part I report. The model, developed for this part of the study, incorporates an inflow component, a diversion-canal component, and a reservoir system component and is capable of evaluating the performance of the reservoir systemem for a variety of operating rule conditions. All model components were verified using observed reservoir input and output data for a 6-year (1967-72 water years) period. In addition, a long-term 31-year simulation under present rule of operation was performed and the results summarized statistically. The model may be used for simulating other rule curves of operation for planning studies of reservoir system performance. (See also W75-05646) (Woodard-USGS)

South Carolina↗
USGS2013

Refinement of regression models to estimate real-time concentrations of contaminants in the Menomonee River drainage basin, southeast Wisconsin, 2008-11

In 2008, the U.S. Geological Survey and the Milwaukee Metropolitan Sewerage District initiated a study to develop regression models to estimate real-time concentrations and loads of chloride, suspended solids, phosphorus, and bacteria in streams near Milwaukee, Wisconsin. To collect monitoring data for calibration of models, water-quality sensors and automated samplers were installed at six sites in the Menomonee River drainage basin. The sensors continuously measured four potential explanatory variables: water temperature, specific conductance, dissolved oxygen, and turbidity. Discrete water-quality samples were collected and analyzed for five response variables: chloride, total suspended solids, total phosphorus, Escherichia coli bacteria, and fecal coliform bacteria. Using the first year of data, regression models were developed to continuously estimate the response variables on the basis of the continuously measured explanatory variables. Those models were published in a previous report. In this report, those models are refined using 2 years of additional data, and the relative improvement in model predictability is discussed. In addition, a set of regression models is presented for a new site in the Menomonee River Basin, Underwood Creek at Wauwatosa. The refined models use the same explanatory variables as the original models. The chloride models all used specific conductance as the explanatory variable, except for the model for the Little Menomonee River near Freistadt, which used both specific conductance and turbidity. Total suspended solids and total phosphorus models used turbidity as the only explanatory variable, and bacteria models used water temperature and turbidity as explanatory variables. An analysis of covariance (ANCOVA), used to compare the coefficients in the original models to those in the refined models calibrated using all of the data, showed that only 3 of the 25 original models changed significantly. Root-mean-squared errors (RMSEs) calculated for both the original and refined models using the entire dataset showed a median improvement in RMSE of 2.1 percent, with a range of 0.0–13.9 percent. Therefore most of the original models did almost as well at estimating concentrations during the validation period (October 2009–September 2011) as the refined models, which were calibrated using those data. Application of these refined models can produce continuously estimated concentrations of chloride, total suspended solids, total phosphorus, E. coli bacteria, and fecal coliform bacteria that may assist managers in quantifying the effects of land-use changes and improvement projects, establish total maximum daily loads, and enable better informed decision making in the future.

Wisconsin↗
USGS2014

The future of nearshore processes research

The nearshore is the transition region between land and the continental shelf including (from onshore to offshore) coastal plains, wetlands, estuaries, coastal cliffs, dunes, beaches, surf zones (regions of wave breaking), and the inner shelf (Figure ES-1). Nearshore regions are vital to the national economy, security, commerce, and recreation. The nearshore is dynamically evolving, is often densely populated, and is under increasing threat from sea level rise, long-term erosion, extreme storms, and anthropogenic influences. Worldwide, almost one billion people live at elevations within 10 m of present sea level. Long-term erosion threatens communities, infrastructure, ecosystems, and habitat. Extreme storms can cause billions of dollars of damage. Degraded water quality impacts ecosystem and human health. Nearshore processes, the complex interactions between water, sediment, biota, and humans, must be understood and predicted to manage this often highly developed yet vulnerable nearshore environment. Over the past three decades, the understanding of nearshore processes has improved. However, societal needs are growing with increased coastal urbanization and threats of future climate change, and significant scientific challenges remain. To address these challenges, members of academia, industry, and federal agencies (USGS, USACE, NPS, NOAA, FEMA, ONR) met at the “The Past and Future of Nearshore Processes Research: Reflections on the Sallenger Years and a New Vision for the Future” workshop to develop a nearshore processes research vision where societal needs and science challenges intersect. The resulting vision is comprised of three broad research themes: Long-term coastal evolution due to natural and anthropogenic processes: As global climate change alters the rates of sea level rise and potentially storm patterns and coastal urbanization increases over the coming decades, an understanding of coastal evolution is critical. Improved knowledge of long-term morphological, ecological, and societal processes and their interactions will result in an improved ability to simulate coastal change. This will enable proactive solutions for resilient coasts and better guidance for reducing coastal vulnerability. Extreme Events: Flooding, erosion, and the subsequent recovery: Hurricane Sandy caused flooding and erosion along hundreds of miles of shoreline, flooded New York City, and impacted communities and infrastructure. Overall U.S. coastal extreme event related economic losses have increased substantially. Furthermore, climate change may cause an increase in coastal extreme events and rising sea levels could increase the occurrence of extreme events. Addressing this research theme will result in an improved understanding of the physical processes during extreme events, leading to improved models of flooding, erosion, and recovery. The resulting societal benefit will be more resilient coastal communities. The physical, biological and chemical processes impacting human and ecosystem health: Nearshore regions are used for recreation, tourism, and human habitation, and provide habitat and valuable ecosystem services. These areas must be sustained for future generations, however overall coastal water quality is declining due to microbial pathogens, fertilizers, pesticides, and heavy metal contamination, threatening ecosystem and human health. To ensure sustainable nearshore regions, predictive real-time water- and sediment-based based pollutant modeling capabilities must be developed, which requires expanding our knowledge of the physics, chemistry, and biology of the nearshore. The resulting societal benefits will include better beach safety, healthier ecosystems, and improved mitigation and regulatory policies. The scientists and engineers of the U.S. nearshore community are poised to make significant progress on these research themes, which have significant societal impact. The U.S. nearshore community, including academic, government, and industry colleagues, recommends multi-agency investment into a coordinated development of observational and modeling research infrastructure to address these themes, as discussed in the whitepaper. The observational infrastructure should include development of new sensors and methods, focused observational programs, and expanded nearshore observing systems. The modeling infrastructure should include improved process representation, better model coupling, incorporation of data assimilation techniques, and testing of real-time models. The observations will provide test beds to compare and improve models.

Report↗
USGS2026

Updates to the Lake Washington Ship Canal and Ballard Locks model, Seattle, Washington, 2016–20

The Hiram M. Chittenden Locks (Ballard Locks or Locks) and Lake Washington Ship Canal connect freshwater Lake Washington with saline Shilshole Bay of Puget Sound. The Locks are operated by the U.S. Army Corps of Engineers (USACE) and serve commercial and recreational vessels. Anadromous salmonids migrate through the canal by making use of a fish ladder at the Locks. To help understand canal hydrodynamics, water temperature, and salinity, a two-dimensional model (CE-QUAL-W2) of the Locks and Lake Washington Ship Canal was constructed by WEST Consultants, Inc. In cooperation with USACE, the U.S. Geological Survey reviewed and updated this model and documentation. The review, published previously, recognized the strengths of the model and suggested some modifications and updates. This report documents these modifications, reports on sensitivity testing, describes model recalibration, and reports model results for calendar years 2016–20. Modeled water velocity was less than 0.2 meter per second at most sites and depths; velocity was greater nearer the Locks. Water age, which estimates residence time, was greatest during September and October. Water temperature was greater near-surface and cooler near the channel bottom at some times and locations. The model also simulated the inflow of lower-salinity waters from Lake Washington and the import of higher-salinity waters from the Locks.

Washington↗
USGS1993

Simulating the variable-source-area concept of streamflow generation with the watershed model TOPMODEL

This report describes TOPMODEL, which is a physically based watershed model that simulates the variable-source-area concept of streamflow generation. The report describes the theoretical background, model equations, methods to determine parameter values, Fortran computer code, and an example interactive simulation. Using TOPMODEL requires specification of soils and topographic parameters, watershed latitude, and time series of precipitation and air temperature. Model predictions include, in addition to streamflow, estimates of overland and subsurface flow, and an estimate of the spatial pattern of the depth to the water table in the watershed.

Water-Resources Investigations Report↗
USGS1978

Estuarine research: An annotated bibliography of selected literature, with emphasis on the Hudson River estuary, New York and New Jersey

Abstracts of 177 selected publications on water movement in estuaries, particularly the Hudson River estuary, are compiled for reference in Hudson River studies. Subjects represented are the hydraulic, chemical, and physical characteristics of estuarine waters, estuarine modeling techniques, and methods of water-data collection and analysis. Summaries are presented in five categories: Hudson River estuary studies; hydrodynamic-model studies; water-quality-model studies; reports on data-collection equipment and methods; and bibliographies, literature reviews, conference proceedings, and textbooks. An author index is included. Omitted are most works published before 1965, environmental-impact statements, theses and dissertations, policy or planning reports, regional or economic reports, ocean studies, studies based on physical models, and foreign studies.

New Jersey, New York↗
USGS2011

Development of a bioenergetics model for age-0 American shad

Bioenergetics modeling can be used as a tool to investigate the impact of non-native age-0 American shad ( Alosa sapidissima ) on reservoir and estuary food webs. The model can increase our understanding of how these fish influence lower trophic levels as well as predatory fish populations that feed on juvenile salmonids. Bioenergetics modeling can be used to investigate ecological processes, evaluate alternative research hypotheses, provide decision support, and quantitative prediction. Bioenergetics modeling has proven to be extremely useful in fisheries research (Ney et al. 1993,Chips and Wahl 2008, Petersen et al. 2008). If growth and diet parameters are known, the bioenergetics model can be used to quantify the relative amount of zooplankton or insects consumed by age-0 American shad. When linked with spatial and temporal information on fish abundance, model output can guide inferential hypothesis development to demonstrate where the greatest impacts of age-0 American shad might occur. Bioenergetics modeling is particularly useful when research questions involve multiple species and trophic levels (e.g. plankton communities). Bioenergetics models are mass-balance equations where the energy acquired from food is partitioned between maintenance costs, waste products, and growth (Winberg 1956). Specifically, the Wisconsin bioenergetics model (Hanson et al. 1997) is widely used in fisheries science. Researchers have extensively tested, reviewed, and improved on this modeling approach for over 30 years (Petersen et al. 2008). Development of a bioenergetics model for any species requires three key components: 1) determine physiological parameters for the model through laboratory experiments or incorporate data from a closely related species, 2) corroboration of the model with growth and consumption estimates from independent research, and 3) error analysis of model parameters. Wisconsin bioenergetics models have been parameterized for many of the salmonids and predatory fishes encountered in the lower Columbia River (Petersen and Ward 1999). The Wisconsin bioenergetics model has not been developed for American shad, however Limburg (1996) parameterized a simplified bioenergetics growth model for this species. A common application for the Wisconsin bioenergetics model is to estimate the consumption or growth of a fish population under different temperature and feeding scenarios (Ney 1993). One advantage of the bioenergetics approach is that consumption can be estimated without direct field measurements of predation rate (prey·predator -1 · day -1 ; Petersen and Ward 1999). Field estimates of fish consumption are time consuming and costly to determine, and estimates may show wide variance due to environmental and sampling variability. However, the consumption parameters used in a newly developed bioenergetics model must be verified with field and laboratory estimates of consumption (Ney 1993). The objective of this research was to parameterize a Wisconsin bioenergetics model for age-0 American shad using published physiological data on American shad and closely related alosine species. The American shad bioenergetics model will be used as a tool to explore various hypotheses about how age-0 American shad directly and indirectly affect Columbia River salmon through ecological interactions in lower Columbia River food webs. One over-arching focus of the larger research project was to identify potential interactions between age-0 American shad and juvenile salmonids, addressing potential outcomes through bioenergetics modeling scenarios. This report contains two bioenergetics modeling applications to demonstrate how these models can be used to address management questions and direct research effort. The first modeling application uses the American shad bioenergetics model described in this report to explore prey consumption by age-0 American shad (Chapter 1, this report). Dietary data on age-0 American shad and previously published reports on the diet of juvenile fall Chinook salmon (Rondorf et al. 1990, USGS unpublished data) suggested there might be considerable dietary overlap between these species in the lower Columbia River. The U.S. Geological Survey (USGS) was interested in using the American shad bioenergetics model to explore hypotheses concerning dietary overlap between age-0 American shad and emigrating fall Chinook salmon. The second modeling application uses the fall Chinook salmon bioenergetics model (Koehler et al. 2006) to explore the growth potential of juvenile fall Chinook salmon predating on age-0 American shad in the lower Columbia River. This modeling was based dietary information on a small number of age-0 fall Chinook salmon (n = 13) collected in John Day Reservoir in 1994 - 1996 (unpublished USGS data). Analysis of this dietary data found that these salmonids were feeding primarily on age-0 American shad (> 75% by weight).

Oregon↗
USGS1992

Applying the DRASTIC model: A review of county-scale maps

The potential for contamination of ground water has become an issue of great concern to citizens and government alike, especially in the last decade. Numerous methods for assessing ground water vulnerability to contamination have been proposed and used. These methods include field-scale deterministic models that predict the rate of migration and fate of specific chemicals, and regional models that attempt to show general trends of ground-water vulnerability to contamination. To address regional ground-water vulnerability, a model may focus on characteristics of the soil, the geologic materials at and above the unconfined water table, or on the larger part of the geologic framework containing aquifers. A model's focus significantly affects the characteristics and, therefore, the utility of maps produced by the model. For example, a model focusing on the soil or vadose zone cannot adequately characterize the contamination potential of confined aquifers. The most commonly-used method for regional assessment of ground-water vulnerability is called "DRASTIC," an acronym for the seven factors that comprise the model. The U.S. Environmental Protection Agency (EPA) funded the development of the DRASTIC model, and used it as an assessment tool in their National Pesticide Survey (USEPA, 1992). In that Survey and in other assessments of contamination potential from application of agricultural chemicals, the pesticide version of DRASTIC is used; it differs from the standard DRASTIC model only in the degree of weighting applied to the seven factors. The DRASTIC model was developed by a committee of technical advisors who used the consensus approach to specify the relative significance of each factor. DRASTIC was designed primarily as a regional tool for prioritization, or screening, to indicate those areas (of at least 100 acres in size) which are generally more sensitive to contamination and, therefore, in need of more detailed mapping and evaluation or monitoring. The committee also intended DRASTIC to support decisions on allocation of scarce monitoring or remediation resources, and to serve as an educational tool. A detailed user's manual for the DRASTIC model (Aller and others, 1987) provides descriptions of common hydrogeologic settings across the United States and expected values for the seven factors; with this information and a specified "weight" or multiplier applied to each factor, DRASTIC scores can be calculated for each setting, and a map of these DRASTIC scores generated. The authors of this model intended it to be sufficiently objective and straightforward that it could be effectively used by persons with but a rudimentary knowledge of hydrogeologic principles. By adjusting the factor values for actual or interpreted local conditions a more knowledgeable person should be able to produce a somewhat more realistic and, therefore, reliable map of ground water vulnerability than by using the expected values for a given hydrogeologic setting. Other models for evaluating regional ground-water vulnerability have been developed; of importance to this report are models developed by the Illinois State Geological Survey (ISGS), the Wisconsin Department of Natural Resources (WDNR), and a joint effort between the U.S. Geological Survey (USGS) and the ISGS. All of these models, as well as DRASTIC, can only estimate the relative potential for contamination, either with a numerical scheme or a hierarchy of contamination potential map units. The model developed by WDNR (Schmidt, 1987) is based on a numerical scheme. It was used to generate a statewide contamination susceptibility map of Wisconsin (Schmidt and Kessler, 1987); Schmidt (1987) defines ground water contamination susceptibility as the "ease with which water (and, presumably, accompanying contaminants) at the surface can reach the water table." The model is not limited to aquifers, but rather considers all unconfined ground water whether in sandy surface aquifers or low-permeability glacial till. Ground water in confined aquifers is not addressed. Contamination susceptibility is estimated by a factor-weighting scheme similar in concept to DRASTIC. The factors (soil texture, surficial deposits, depth to the water table, bedrock type, and glacial drift thickness) are assigned an arbitrary value based on perceived importance. These numbers are then weighted and summed to produce the contamination susceptibility score. This model is compared and contrasted with other models elsewhere in this report. In contrast, the ISGS method avoids the use of a numerical system to rate the relative potential for contamination, and instead orders the map units in a hierarchy from relatively low to relatively high contamination potential. Also in contrast to the two models described above, the ISGS model relies solely on the textural character of the geologic framework to a specified depth. For example, a statewide map (Berg and others, 1984, scale 1:500,000) addresses land burial of wastes, and shows the contamination potential of aquifers within geologic units in the upper 50 feet. Another ISGS map (Keefer and Berg, 1990) addresses the contamination of major, economically important aquifers, and therefore evaluates contamination potential to greater depths (to greater than 300 feet). In general, the ISGS contamination potential maps evaluate aquifers, and do not evaluate potential for contamination of ground water at the unconfined water table in geologic units that are not aquifers (for example, in glacial till or finegrained lake sediments). With the cooperation of the ISGS, I have developed a model (Seller and Berg, in press) for the regional assessment of aquifer contamination potential that is based on ISGS techniques, adapted to a broader map area where detailed information may be unavailable. This model was used to generate a map of aquifer contamination potential for an area encompassing parts of five states near southern Lake Michigan and Lake Erie; the model and map are currently being refined and evaluated.

Open-File Report↗
USGS2010

Approaches to highly parameterized inversion: A guide to using PEST for model-parameter and predictive-uncertainty analysis

Analysis of the uncertainty associated with parameters used by a numerical model, and with predictions that depend on those parameters, is fundamental to the use of modeling in support of decisionmaking. Unfortunately, predictive uncertainty analysis with regard to models can be very computationally demanding, due in part to complex constraints on parameters that arise from expert knowledge of system properties on the one hand (knowledge constraints) and from the necessity for the model parameters to assume values that allow the model to reproduce historical system behavior on the other hand (calibration constraints). Enforcement of knowledge and calibration constraints on parameters used by a model does not eliminate the uncertainty in those parameters. In fact, in many cases, enforcement of calibration constraints simply reduces the uncertainties associated with a number of broad-scale combinations of model parameters that collectively describe spatially averaged system properties. The uncertainties associated with other combinations of parameters, especially those that pertain to small-scale parameter heterogeneity, may not be reduced through the calibration process. To the extent that a prediction depends on system-property detail, its postcalibration variability may be reduced very little, if at all, by applying calibration constraints; knowledge constraints remain the only limits on the variability of predictions that depend on such detail. Regrettably, in many common modeling applications, these constraints are weak. Though the PEST software suite was initially developed as a tool for model calibration, recent developments have focused on the evaluation of model-parameter and predictive uncertainty. As a complement to functionality that it provides for highly parameterized inversion (calibration) by means of formal mathematical regularization techniques, the PEST suite provides utilities for linear and nonlinear error-variance and uncertainty analysis in these highly parameterized modeling contexts. Availability of these utilities is particularly important because, in many cases, a significant proportion of the uncertainty associated with model parameters-and the predictions that depend on them-arises from differences between the complex properties of the real world and the simplified representation of those properties that is expressed by the calibrated model. This report is intended to guide intermediate to advanced modelers in the use of capabilities available with the PEST suite of programs for evaluating model predictive error and uncertainty. A brief theoretical background is presented on sources of parameter and predictive uncertainty and on the means for evaluating this uncertainty. Applications of PEST tools are then discussed for overdetermined and underdetermined problems, both linear and nonlinear. PEST tools for calculating contributions to model predictive uncertainty, as well as optimization of data acquisition for reducing parameter and predictive uncertainty, are presented. The appendixes list the relevant PEST variables, files, and utilities required for the analyses described in the document.

Michigan↗
USGS2020

Hydrologic modeling for flow-ecology science in the Southeastern United States and Puerto Rico

An understanding of the applicability and utility of hydrologic models is critical to support the effective management of water resources throughout the Southeastern United States (SEUS) and Puerto Rico (PR). Hydrologic models have the capacity to provide an estimate of the quantity of available water at ungauged locations (i.e., areas of the country where a U.S. Geological Survey [USGS] continuous record gauge is not installed) and provide the baseline flow information necessary to develop the linkages between water availability and characteristics of streamflow that support ecological communities (i.e., support the development of flow-ecology response models). This report inventories and then directly examines and compares a subset of hydrologic models used to estimate streamflow at a number of gauged basins across the SEUS and PR. This effort was designed to evaluate, quantify, and compare the magnitude of error and to investigate the potential causes of error associated with predicted streamflows from seven hydrologic models of varying complexity and calibration strategy. This was accomplished by computing and then comparing classical hydrologic model fit statistics (e.g., mean bias, coefficient of determination [R2], root mean squared error [RMSE], Nash-Sutcliffe Efficiency [NSE]) and understanding the bias in the prediction in these and a subset of ecologically relevant flow metrics (ERFMs). Additionally, streamflow predictions from a larger regional-scale hydrologic model were compared to those of several fine-scale hydrologic models under a range of hypothetical climate change scenarios to determine the range of predicted streamflow responses to fixed climate perturbations. A pilot study was conducted using predicted streamflow and boosted regression trees to develop a set of predictive flow-ecology response models to assess the potential change in fish species richness in the North Carolina Piedmont under several scenarios of water availability change. This report is intended to provide a general assessment of all the tools and techniques available to support hydrologic modeling for flow-ecology science in the SEUS and PR. It is our hope that the approach used herein to understand differences in streamflow predictions among a subset of hydrologic models that have been applied in the SEUS for developing flow-ecology response models will provide water resource managers and stakeholders with an informed pathway for developing the capacity to link streamflow and ecological response and an understanding of some of the limitations associated with these type of modeling efforts.

Alabama, Florida, Georgia, Mississippi, North Caro↗
USGS2002

A three-dimensional numerical model of predevelopment conditions in the Death Valley regional ground-water flow system, Nevada and California

In the early 1990's, two numerical models of the Death Valley regional ground-water flow system were developed by the U.S. Department of Energy. In general, the two models were based on the same basic hydrogeologic data set. In 1998, the U.S. Department of Energy requested that the U.S. Geological Survey develop and maintain a ground-water flow model of the Death Valley region in support of U.S. Department of Energy programs at the Nevada Test Site. The purpose of developing this "second-generation" regional model was to enhance the knowledge an understanding of the ground-water flow system as new information and tools are developed. The U.S. Geological Survey also was encouraged by the U.S. Department of Energy to cooperate to the fullest extent with other Federal, State, and local entities in the region to take advantage of the benefits of their knowledge and expertise. The short-term objective of the Death Valley regional ground-water flow system project was to develop a steady-state representation of the predevelopment conditions of the ground-water flow system utilizing the two geologic interpretations used to develop the previous numerical models. The long-term objective of this project was to construct and calibrate a transient model that simulates the ground-water conditions of the study area over the historical record that utilizes a newly interpreted hydrogeologic conceptual model. This report describes the result of the predevelopment steady-state model construction and calibration. The Death Valley regional ground-water flow system is situated within the southern Great Basin, a subprovince of the Basin and Range physiographic province, bounded by latitudes 35 degrees north and 38 degrees 15 minutes north and by longitudes 115 and 118 degrees west. Hydrology in the region is a result of both the arid climatic conditions and the complex geology. Ground-water flow generally can be described as dominated by interbasinal flow and may be conceptualized as having two main components: a series of relatively shallow and localized flow paths that are superimposed on deeper regional flow paths. A significant component of the regional ground-water flow is through a thick Paleozoic carbonate rock sequence. Throughout the flow system, ground water flows through zones of high transmissivity that have resulted from regional faulting and fracturing. The conceptual model of the Death Valley regional ground-water flow system used for this study is adapted from the two previous ground-water modeling studies. The three-dimensional digital hydrogeologic framework model developed for the region also contains elements of both of the hydrogeologic framework models used in the previous investigations. As dictated by project scope, very little reinterpretation and refinement were made where these two framework models disagree; therefore, limitations in the hydrogeologic representation of the flow system exist. Despite limitations, the framework model provides the best representation to date of the hydrogeologic units and structures that control regional ground-water flow and serves as an important information source used to construct and calibrate the predevelopment, steady-state flow model. In addition to the hydrogeologic framework, a complex array of mechanisms accounts for flow into, through, and out of the regional ground-water flow system. Natural discharges from the regional ground-water flow system occur by evapotranspiration, springs, and subsurface outflow. In this study, evapotranspiration rates were adapted from a related investigation that developed maps of evapotranspiration areas and computed rates from micrometeorological data collected within the local area over a multiyear period. In some cases, historical spring flow records were used to derive ground-water discharge rates for isolated regional springs. For this investigation, a process-based, numerical model was developed to estimate net infiltration. This result can be used to represent recharge by assuming that water that infiltrates past the “root zone” ultimately becomes ground-water recharge. Net infiltration based on this water-balance approach, however, suggests that recharge in the region exceeds the estimated ground-water discharge for the basin by almost a factor of four. The net infiltration model contains some assumptions and was limited in regard to soil moisture, bedrock permeability, and precipitation distributions that result in these higher than expected values. Despite this limitation, the net infiltration model does provide a good starting point for estimating regional ground-water recharge in the ground-water flow model. The Death Valley regional ground-water flow system was simulated using a three-dimensional steady-state model that incorporated a nonlinear least-squares regression technique to estimate selected model parameters. The numerical modeling program MODFLOW-2000 was used in creating a finite-difference model consisting of 194 rows, 160 columns, and 15 layers. The grid cells were oriented north-south and were of uniform size, with side dimensions of 1,500 meters. The layers span thicknesses of 50 to 300 meters. The model grid encompasses about 70,000 square kilometers. The required initial model parameter values were supplied by discretization of the three-dimensional hydrogeologic framework model and digital representations of the remaining conceptual model components. The three-dimensional simulation and corresponding sensitivity analysis supported the hypothesis of interactions between a relatively shallow local and subregional flow system and a deeper dominant regional system controlled by the carbonate aquifer. During calibration of the model, techniques available in MODFLOW-2000 allowed for estimation of a series of parameters that provided a best fit to observed hydraulic heads and flows. Numerous conceptual models were evaluated to test the validity of various interpretations about the flow system. Only those conceptual model changes contributing to a significant improvement in model fit, as indicated by a reduction in the sum of squared errors, were retained in the final optimized model. The final model was evaluated to assess the likely accuracy of simulated results by comparing measured and expected quantities with simulated values. Evaluation of the model indicates that although the model is clearly an improvement on previous representations of the flow system, there is an indication of important uncertainties and model error.

California, Nevada↗
USGS2010

Reducing Uncertainty in the Distribution of Hydrogeologic Units within Volcanic Composite Units of Pahute Mesa Using High-Resolution 3-D Resistivity Methods, Nevada Test Site, Nevada

The U.S. Department of Energy (DOE) and the National Nuclear Security Administration (NNSA) at their Nevada Site Office (NSO) are addressing groundwater contamination resulting from historical underground nuclear testing through the Environmental Management program and, in particular, the Underground Test Area (UGTA) project. From 1951 to 1992, 828 underground nuclear tests were conducted at the Nevada Test Site (NTS) northwest of Las Vegas (DOE UGTA, 2003). Most of these tests were conducted hundreds of feet above the groundwater table; however, more than 200 of the tests were near, or within, the water table. This underground testing was limited to specific areas of the NTS including Pahute Mesa, Rainier Mesa/Shoshone Mountain, Frenchman Flat, and Yucca Flat. Volcanic composite units make up much of the area within the Pahute Mesa Corrective Action Unit (CAU) at the NTS, Nevada. The extent of many of these volcanic composite units extends throughout and south of the primary areas of past underground testing at Pahute and Rainier Mesas. As situated, these units likely influence the rate and direction of groundwater flow and radionuclide transport. Currently, these units are poorly resolved in terms of their hydrologic properties introducing large uncertainties into current CAU-scale flow and transport models. In 2007, the U.S. Geological Survey (USGS), in cooperation with DOE and NNSA-NSO acquired three-dimensional (3-D) tensor magnetotelluric data at the NTS in Area 20 of Pahute Mesa CAU. A total of 20 magnetotelluric recording stations were established at about 600-m spacing on a 3-D array and were tied to ER20-6 well and other nearby well control (fig. 1). The purpose of this survey was to determine if closely spaced 3-D resistivity measurements can be used to characterize the distribution of shallow (600- to 1,500-m-depth range) devitrified rhyolite lava-flow aquifers (LFA) and zeolitic tuff confining units (TCU) in areas of limited drill hole control on Pahute Mesa within the Calico Hills zeolitic volcanic composite unit (VCU), an important hydrostratigraphic unit in Area 20. The resistivity response was evaluated and compared with existing well data and hydrogeologic unit tops from the current Pahute Mesa framework model. In 2008, the USGS processed and inverted the magnetotelluric data into a 3-D resistivity model. We interpreted nine depth slices and four west-east profile cross sections of the 3-D resistivity inversion model. This report documents the geologic interpretation of the 3-D resistivity model. Expectations are that spatial variations in the electrical properties of the Calico Hills zeolitic VCU can be detected and mapped with 3-D resistivity, and that these changes correlate to differences in rock permeability. With regard to LFA and TCU, electrical resistivity and permeability are typically related. Tuff confining units will typically have low electrical resistivity and low permeability, whereas LFA will have higher electrical resistivity and zones of higher fracture-related permeability. If expectations are shown to be correct, the method can be utilized by the UGTA scientists to refine the hydrostratigraphic unit (HSU) framework in an effort to more accurately predict radionuclide transport away from test areas on Pahute and Rainier Mesas.

Nevada↗
USGS1982

Multi-event urban runoff quality model

A computer model is presented for simulating the quality of surface runoff from urban watersheds. The model can simulate impervious area, pervious area, and precipitation contributions to runoff quality as well as the effects of street sweeping and (or) detention storage. Within-storm variations of runoff quality are simulated for user-specified storm-runoff periods. Between these storms, a daily accounting of the accumulation and washoff of water-quality constituents on effective impervious areas is maintained. The time step of the within-storm simulations can range from 1 to 60 minutes. The model can be operated as a lumped-parameter model or as a distributed-parameter model. As a lumped-parameter model, no spatial variations in model parameters are accounted for, and input to the model requires flow hydrographs only at the outlet of the watershed. The outlet hydrographs can be either observed or simulated. As a distributed-parameter model, the model requires flow hydrographs at many points in the watershed, as defined by basin segmentation. These hydrographs will normally be simulated by the Distributed Routing Rainfall-Runoff Model. This report includes a presentation of the theory and limitations of the model, as well as a program listing, instructions for running the program, and example simulations.

Open-File Report↗
USGS2023

Updates to CE-QUAL-W2 models for select U.S. Army Corps of Engineers reservoirs in the Willamette Valley Project and an inter-reservoir reach of the Middle Fork Willamette River, northwestern Oregon

Mechanistic models capable of simulating hydrodynamics and water temperature in rivers and reservoirs are valuable tools for investigating thermal conditions and their relation to dam operations and streamflow in river basins where upstream water storage and management decisions have an important influence on river reaches with threatened fish populations. In particular, models allow managers to investigate how new, untried operations or hypothetical structures might influence streamflow and temperature conditions downstream. CE-QUAL-W2 is a two-dimensional (laterally averaged) hydrodynamic water-quality model that has previously been used to investigate the downstream effects of dam operations and other anthropogenic influences on stream temperature in the Willamette River Basin in northwestern Oregon, a region with two populations of fish species designated as threatened under the Endangered Species Act. By linking CE-QUAL-W2 river models to models of upstream, large Willamette Valley Project dams and reservoirs, these models can be used to investigate how dam operations at individual dams can influence streamflow and thermal conditions in downstream river reaches as an integrated system. Integrated model simulations that include the large dams and reservoirs linked to downstream river reaches can help managers develop a better understanding of tradeoffs associated with potential retrofits or operational changes across the multipurpose dams in the Willamette Valley Project, the effect of dam management on downstream tributaries and the Willamette River, and the resulting potential effect on threatened fish populations and habitat conditions. River models capable of simulating river corridors downstream from U.S. Army Corps of Engineers dams were previously updated and integrated to simulate conditions that occurred from March through October of 2011 (a cool and wet year), 2015 (a hot and dry year), and 2016 (a moderately hot and dry year) using CE-QUAL-W2 version 4.2. These river models encompass the following: Coast Fork Willamette and Middle Fork Willamette Rivers, the Row River, and Fall Creek downstream from Cottage Grove, Dexter, Dorena, and Fall Creek Dams, respectively; South Fork McKenzie River downstream from Cougar Dam; McKenzie River downstream from its confluence with the South Fork McKenzie River; South Santiam River downstream from Foster Dam; North Santiam River downstream from Big Cliff Dam; and Willamette River from its start at the confluence of the Middle Fork Willamette and Coast Fork Willamette Rivers to Willamette Falls (river mile 26.0; near West Linn, Oregon). This report documents model modifications, boundary condition data sources or estimation methods, and goodness-of-fit statistics for six CE-QUAL-W2 reservoir models and one river model upstream from the existing river models. These models simulate (1) Hills Creek Lake; (2) Lookout Point Lake and Dexter Reservoir on the Middle Fork Willamette River; (3) the Middle Fork Willamette River reach between Hills Creek Dam upstream and Lookout Point Lake downstream; (4) Cougar Reservoir on the South Fork McKenzie River; (5) Green Peter Lake on the Middle Santiam River and Foster Lake on the South Santiam River; and (6) Detroit Lake and (7) Big Cliff Reservoir on the North Santiam River. These CE-QUAL-W2 models were built by a variety of researchers to simulate a range of conditions in past years; this report documents their upgrade to U.S. Geological Survey (USGS) edition 7 of version 4.2 of CE-QUAL-W2 and updates each model to simulate conditions from January through December of 2011, 2015, and 2016. Also included in this report is an explanation of modifications to the CE-QUAL-W2 source code that constitute USGS edition 7 of CE-QUAL-W2 version 4.2. Each of the models described in this report can be run in isolation or linked to downstream models as a “system model” to simulate conditions in tributaries and (or) in the Willamette Valley Project as a whole. As part of the model updates described in this report, some model parameters were adjusted to improve stability or decrease model error, and boundary conditions including meteorological, hydrologic, and temperature inputs were developed and updated for model years 2011, 2015, and 2016, as necessary. In some cases, the data sources used to drive previous model versions were no longer available, which required the development and checking of new data sources or estimation techniques. Goodness-of-fit statistics for outflow from the dams and in simulated river reaches generally show a good model fit, with the models simulating subdaily water temperatures at most comparable locations with a mean absolute error of generally less than 1 degree Celsius (°C) and a reasonably low bias. Model simulation of the thermal vertical profiles in each reservoir also produced an overall mean absolute error of generally less than 1 °C for all 3 years, with the exception of the Hills Creek Lake Model and the Cougar Reservoir Model in years when the reservoirs did not fill (2015 and 2016). Both of these models have known calibration issues and tend to be sensitive to the choice of certain structural parameters in the model. Overall, the calibration process was focused on obtaining model settings that led to realistic water temperature predictions in all 3 years (2011, 2015, and 2016) without over-calibrating specifically to any single year. A complete investigation of model error for these reservoir submodels was beyond the scope of this investigation but could be undertaken in the future if better model performance for these two reservoirs is desired.

Oregon↗
USGS2011

Three-dimensional geologic model of the southeastern Espanola Basin, Santa Fe County, New Mexico

This multimedia model and report show and describe digital three-dimensional faulted surfaces and volumes of lithologic units that confine and constrain the basin-fill aquifers within the Espanola Basin of north-central New Mexico. These aquifers are the primary groundwater resource for the cities of Santa Fe and Espanola, six Pueblo nations, and the surrounding areas. The model presented in this report is a synthesis of geologic information that includes (1) aeromagnetic and gravity data and seismic cross sections; (2) lithologic descriptions, interpretations, and geophysical logs from selected drill holes; (3) geologic maps, geologic cross sections, and interpretations; and (4) mapped faults and interpreted faults from geophysical data. Modeled faults individually or collectively affect the continuity of the rocks that contain the basin aquifers; they also help define the form of this rift basin. Structure, trend, and dip data not previously published were added; these structures are derived from interpretations of geophysical information and recent field observations. Where possible, data were compared and validated and reflect the complex relations of structures in this part of the Rio Grande rift. This interactive geologic framework model can be used as a tool to visually explore and study geologic structures within the Espanola Basin, to show the connectivity of geologic units of high and low permeability between and across faults, and to show approximate dips of the lithologic units. The viewing software can be used to display other data and information, such as drill-hole data, within this geologic framework model in three-dimensional space.

Scientific Investigations Report↗
USGS2018

Revised groundwater-flow model of the glacial aquifer system north of Aberdeen, South Dakota, through water year 2015

The city of Aberdeen, in northeastern South Dakota, requires an expanded and sustainable supply of water to meet current and future demands. Conceptual and numerical models of the glacial aquifer system in the area north of Aberdeen were developed by the U.S. Geological Survey in cooperation with the City of Aberdeen in 2012. The U.S. Geological Survey, in cooperation with the City of Aberdeen, completed a study to revise the original numerical groundwater-flow model using data through water year (WY) 2015 to aid the City of Aberdeen in their development of plans and strategies for a sustainable water supply and to increase understanding of the glacial aquifer system and groundwater-flow system near Aberdeen. The original model was revised to improve the fit between model-simulated values and observed (measured or estimated) data, provide greater insight into surface-water interactions, and improve the usefulness of the model for water-supply planning. The revised groundwater-flow model (hereafter referred to as the “revised model”) presented in this report supersedes the original model. The purpose of this report is to describe a revised groundwater-flow model including data collection, model calibration, and model results for the glacial aquifer system including the Elm, Middle James, and Deep James aquifers north of Aberdeen, South Dakota, using updated hydrologic data through WY 2015. The original numerical model was revised in several ways. The model was modified by adding four new layers, which included a surficial layer, two intervening confining layers, and a shale bedrock layer. The revised model provides an improved understanding of the groundwater-flow system in comparison to the original model. The principal aquifers of the model area include portions of the Elm, Middle James, and Deep James aquifers. The lithologic information used to define and describe the aquifers in the model area was unaltered; however, aquifer properties and boundary conditions were reviewed and updated using geological information reported by the South Dakota Department of Environmental and Natural Resources and information obtained from geophysical investigations for this study. The horizontal extent of the Elm, Middle James, and Deep James aquifers was unaltered from the original model. The thickness of the Deep James aquifer was modified based on interpretations from the geophysical investigations. In general, groundwater in the Elm aquifer flowed from northwest to southeast and locally towards rivers and streams. Similarly, in the Middle James and Deep James aquifers, groundwater also typically flowed southeast. The revisions made to the original model include use of the following MODFLOW stress packages: Recharge, Evapotranspiration, Time-Variant Specified Head, Wells, Drains, and Stream Flow Routing, all of which were updated from the original model except for the Stream Flow Routing Package, which replaced the River Package used in the original model. Model calibration is the process of estimating model parameters to minimize the differences, or residuals, between observed data and simulated values; therefore, Parameter ESTimation (PEST) software was used to optimize model input parameters by matching model-simulated values to observed data. Calibration parameters included horizontal hydraulic conductivity, vertical hydraulic conductivity, specific yield, specific storage, and vertical streambed conductance for stream and drain cells. Multipliers were used to calibrate the recharge and evapotranspiration stresses. Evapotranspiration extinction depth also was adjusted during model calibration. Comparisons to the original model are described to highlight the changes made in the revised model. In general, the revised model adequately simulates the natural system and compares favorably with observed hydrologic data. Simulated water levels were evaluated by comparing them to single water-level observations at selected well locations. The selected wells were the same wells used in the original model. The coefficient of determination value between simulated and observed water levels for the revised model was 0.89 and included simulated and observed values from October 1, 1974 (WY 1975), through September 30, 2015 (WY 2015). The coefficient of determination value for the original model was 0.94 and included simulated and observed values from October 1, 1974, through September 30, 2009. The difference may indicate that the original model could have been overfit to hydraulic head observations because base flow was not simulated. The additional data used in the revised model included some climatically wetter, more extreme periods, such as 2011, in which annual precipitation was 30.9 inches. Average annual precipitation for the original model timeframe, which included data from WYs 1975–2009, was 20.26 inches. Additional precipitation data for WYs 2010–15, included in the revised model timeframe, resulted in an average annual precipitation for WYs 1975–2015 in the model area of 20.6 inches. The larger variability in climate data coupled with the additional water-level data could explain the lower coefficient of determination for water levels in the revised model. The revised model was used to calculate various groundwater-budget components for steady-state and transient conditions for WYs 1975–2015. The time-variant specified-head cells in the revised model had the largest change when compared to the original steady-state model for inflows and outflows. Comparing the transient budget components between the original and the revised models indicated that inflow from recharge and time-variant specified-head cells had the greatest effect on groundwater inflows, and outflow from storage had the greatest effect on groundwater outflows. The simulated potentiometric contours from the revised model were compared with (1) the observed (interpreted) potentiometric surface (layer 2) and the hydraulic head values (layers 4 and 6) and (2) the simulated contours from the original model. The simulated hydraulic gradients and general direction of groundwater flow in the Elm aquifer in the revised model generally matched the observed potentiometric contours, the simulated potentiometric contours from the original model, and general flow directions interpreted to be perpendicular to the contours. Minor discrepancies between simulated potentiometric contours from the revised model and the observed potentiometric contours may be due to the lack of observed data in the model area. The revised model was designed to reduce the limitations of the original model. The revisions were validated by comparing the results of the original model with the revised model. A primary benefit of the revised model is the inclusion of the surficial deposits and the confining units as explicit layers in the model. The addition of the surficial layer was beneficial for three primary reasons: (1) more accurate representation of recharge from precipitation, (2) more accurate representation of groundwater evapotranspiration, and (3) more accurate representation of groundwater and surface-water interactions. The groundwater model is a numeric approximation of a complex physical hydrologic system, and the revised model data were interpolated in regions with sparse data. Additionally, model discretization included averaged and interpolated values for water use, withdrawal rates, and hydraulic conductivity. The revised model provides a useful estimate for hydraulic gradients, groundwater-flow directions, and aquifer response to groundwater withdrawals.

South Dakota↗