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At least 307 records · Page 17Linked to original sources
USGS2004

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↗
USGS2020

Using information from global climate models to inform policymaking—The role of the U.S. Geological Survey

This report provides an overview of model-based climate science in a risk management context. In addition, it summarizes how the U.S. Geological Survey (USGS) will continue to follow best scientific practices and when and how the results of this research will be delivered to the U.S. Department of the Interior (DOI) and other stakeholders to inform policymaking. Climate change is a risk management challenge for society because of the uncertain consequences for natural and human systems across decades to centuries. Climate-related science activities within the USGS emphasize research on adaptation to climate change. This research helps inform adaptive management processes and planning activities within other DOI bureaus and by DOI stakeholders. Global climate models are sophisticated numerical representations of the Earth’s climate system. Research groups from around the world regularly participate in a coordinated effort to produce a suite of climate models. This global effort provides a test bed to assess model performance and analyze projections of future change under various prescribed climate scenarios. These climate scenarios describe a plausible future outcome associated with a specific set of societal actions. Because scenarios are developed in a risk-based framework with a high degree of uncertainty about future societal developments, they are usually not assigned a formal likelihood of occurrence. Examining a range of projected climate outcomes based on multiple scenarios is a recommended best practice because it allows decision makers to better consider both short- and long-term risks and opportunities. As part of its routine science practices, the USGS regularly reviews the state of knowledge of climate science, develops and maintains best practices in using global climate models to project climate change impacts, and provides data and interpretations of potential impacts to the DOI and other stakeholders. Management and policy decisions within the DOI will reflect different tolerances for risk, which has implications for what type of information should be considered and how that information should be used. It is suggested that a followup document be produced that would describe in more detail how these management decisions with differing risk tolerances can be made effectively and consistently in light of an uncertain future.

Open-File Report↗
USGS2011

Prediction and assimilation of surf-zone processes using a Bayesian network: Part II: Inverse models

A Bayesian network model has been developed to simulate a relatively simple problem of wave propagation in the surf zone (detailed in Part I). Here, we demonstrate that this Bayesian model can provide both inverse modeling and data-assimilation solutions for predicting offshore wave heights and depth estimates given limited wave-height and depth information from an onshore location. The inverse method is extended to allow data assimilation using observational inputs that are not compatible with deterministic solutions of the problem. These inputs include sand bar positions (instead of bathymetry) and estimates of the intensity of wave breaking (instead of wave-height observations). Our results indicate that wave breaking information is essential to reduce prediction errors. In many practical situations, this information could be provided from a shore-based observer or from remote-sensing systems. We show that various combinations of the assimilated inputs significantly reduce the uncertainty in the estimates of water depths and wave heights in the model domain. Application of the Bayesian network model to new field data demonstrated significant predictive skill (R 2 = 0.7) for the inverse estimate of a month-long time series of offshore wave heights. The Bayesian inverse results include uncertainty estimates that were shown to be most accurate when given uncertainty in the inputs (e.g., depth and tuning parameters). Furthermore, the inverse modeling was extended to directly estimate tuning parameters associated with the underlying wave-process model. The inverse estimates of the model parameters not only showed an offshore wave height dependence consistent with results of previous studies but the uncertainty estimates of the tuning parameters also explain previously reported variations in the model parameters.

Coastal Engineering↗
USGS2015

Real-time validation of the Dst Predictor model

The Dst Predictor model, which has been running real-time in the Space Weather Analysis and Forecast System (SWAFS), provides 1-hour and 4-hour forecasts of the Dst index. This is useful for awareness of impending geomagnetic activity, as well as driving other real-time models that use Dst as an input. In this report, we examine the performance of this forecast model in detail. When validating indices it should be noted that performance is only with respect to a reference index as they are derived quantities assumed to reflect a state of the magnetosphere that cannot be directly measured. In this case U.S. Geological Survey (USGS) Definitive Dst is the reference index (Section 3). Whether or not the model better reflects the actual activity level is nearly impossible to discern and is outside the scope of this report. We evaluate the performance of the model by computing continuous predictant skill scores against USGS Definitive Dst values as “observations” (Section 4.2). The two sets of data are not well-correlated for both 1-hour and 4-hour forecasts. The Dst Predictor Prediction Efficiency for both the 1- and 4-hour forecasts suggests poor performance versus the climatological mean. However, the skill score against a nowcast persistence model is positive, suggesting value added by the Dst Predictor model. We further examine statistics for storm times (Section 4.3) with similar results: nowcast persistence performs worse than Dst Predictor. Dst Predictor is superior to the nowcast persistence model for the metric used in this study. We recommend continued use of the DstPredictor model for 1-and4-hour Dst predictions along with active study of other Dst forecast models that do not rely on nowcast inputs (Section 6). The lack of certified requirements makes further recommendations difficult. A study of how the error in Dst translates to error in models and a better understanding of operational needs for magnetic storm warning are needed to determine such requirements. Nowcast persistence is often hard to beat for short term forecasts and specification and Dst Predictor clearly performs well against that standard (with 1-hour and 4-hour skill-scores of 0.233 and 0.485 respectively), although poor in absolute terms (with1-hourand4-hour prediction efficiencies of-64.6and-43.1, respectively).

Air Force Research Laboratory Technical Report↗
USGS1976

Simulation procedure for modeling transient water table and artesian stress and response

The series of computer programs described in this report were designed specifically to model the ground-water regime in sufficient detail to determine the effects of the imposition of various types of stress upon the system, and to display the results in a convenient manner during calibration and when presenting projected data. SUPERMOCK simulates the ground-water system and DATE and HYDROG aid in the display of computed data. During calibration, DATE is especially useful because it has the optional feature of comparing computed data with observed data. Although the programs can be run independently, experience dictates that for best results the three should be run as steps in the same job. English units of inches, feet, and days are used in each of the programs. The units for any parameters not given in the text are clearly specified in the instructions for input to the individual programs. (Woodard-USGS)

Open-File Report↗
USGS2013

Modeling for the SAFRR Tsunami Scenario-generation, propagation, inundation, and currents in ports and harbors: Chapter D in The SAFRR (Science Application for Risk Reduction) Tsunami Scenario

This U.S. Geological Survey (USGS) Open-File report presents a compilation of tsunami modeling studies for the Science Application for Risk Reduction (SAFRR) tsunami scenario. These modeling studies are based on an earthquake source specified by the SAFRR tsunami source working group (Kirby and others, 2013). The modeling studies in this report are organized into three groups. The first group relates to tsunami generation. The effects that source discretization and horizontal displacement have on tsunami initial conditions are examined in section 1 (Whitmore and others). In section 2 (Ryan and others), dynamic earthquake rupture models are explored in modeling tsunami generation. These models calculate slip distribution and vertical displacement of the seafloor as a result of realistic fault friction, physical properties of rocks surrounding the fault, and dynamic stresses resolved on the fault. The second group of papers relates to tsunami propagation and inundation modeling. Section 3 (Thio) presents a modeling study for the entire California coast that includes runup and inundation modeling where there is significant exposure and estimates of maximum velocity and momentum flux at the shoreline. In section 4 (Borrero and others), modeling of tsunami propagation and high-resolution inundation of critical locations in southern California is performed using the National Oceanic and Atmospheric Administration’s (NOAA) Method of Splitting Tsunami (MOST) model and NOAA’s Community Model Interface for Tsunamis (ComMIT) modeling tool. Adjustments to the inundation line owing to fine-scale structures such as levees are described in section 5 (Wilson). The third group of papers relates to modeling of hydrodynamics in ports and harbors. Section 6 (Nicolsky and Suleimani) presents results of the model used at the Alaska Earthquake Information Center for the Ports of Los Angeles and Long Beach, as well as synthetic time series of the modeled tsunami for other selected locales in southern California. Importantly, section 6 provides a comparison of the effect of including horizontal displacements at the source described in section 1 and differences in bottom friction on wave heights and inundation in the Ports of Los Angeles and Long Beach. Modeling described in section 7 (Lynett and Son) uses a higher order physical model to determine variations of currents during the tsunami and complex flow structures such as jets and eddies. Section 7 also uses sediment transport models to estimate scour and deposition of sediment in ports and harbors—a significant effect that was observed in southern California following the 2011 Tohoku tsunami. Together, all of the sections in this report form the basis for damage, impact, and emergency preparedness aspects of the SAFRR tsunami scenario. Three sections of this report independently calculate wave height and inundation results using the source specified by Kirby and others (2013). Refer to figure 29 in section 3, figure 52 in section 4, and figure 62 in section 6. All of these results are relative to a mean high water (MHW) vertical datum. Slight differences in the results are observed in East Basin of the Port of Los Angeles, Alamitos Bay, and the Seal Beach National Wildlife Refuge. However, given that these three modeling efforts involved different implementations of the source, different numerical wave propagation and runup models, and slight differences in the digital elevation models (DEMs), the similarity among the results is remarkable.

California↗
USGS2020

Predicting barrier island habitats and oyster and seagrass habitat suitability for various restoration measures and future conditions for Dauphin Island, Alabama

Barrier islands, such as Dauphin Island, Alabama, provide numerous invaluable ecosystem services including storm damage reduction and erosion control to the mainland, habitat for fish and wildlife, carbon sequestration in marshes, water catchment and purification, recreation, and tourism. These islands are dynamic environments that are gradually shaped by currents, waves, and tides under quiescent conditions yet can evolve in the time scale of hours to days during hurricanes and other extreme storms. The ecosystems associated with these islands also face numerous other hazards, including accelerated sea-level rise, oil spills, and anthropogenic stressors. Hurricane Katrina in 2005 and the Deepwater Horizon oil spill in 2010 are two major events that have affected habitats and natural resources on Dauphin Island, Ala. The latter event prompted a cooperative effort between the U.S. Geological Survey and the U.S. Army Corps of Engineers to investigate viable, sustainable restoration measures that reduce degradation and enhance the natural resources of Dauphin Island, Ala. In collaboration with the State of Alabama and the National Fish and Wildlife Foundation, the overarching goal of the Alabama Barrier Island Restoration Feasibility Assessment project was to document baseline conditions and forecast potential conditions under varying sea-level change and storm scenarios for a no-action alternative along with a variety of restoration measures including beach and dune restoration, marsh and back-barrier restoration, and placement of sand in the littoral zone. The modeling component of this project used decadal hydrodynamic geomorphic, water quality, and habitat modeling to better understand how the various restoration measures may influence the habitat composition, sustainability, and resiliency of Dauphin Island under potential future conditions, benchmarked against the no-action case. The report covers the habitat modeling efforts associated with the Alabama Barrier Island Restoration Feasibility Assessment project. For various potential future island configurations for Dauphin Island, we predicted coverage of habitat types (for example, beach, dune, intertidal marsh, and woody vegetation) using a spatially explicit habitat model based on landscape-position information (for example, elevation and distance from shore) extracted from the hydrodynamic geomorphic outputs. Similarly, we forecasted habitat suitability for oysters and seagrass using habitat suitability index models. Another component of the Alabama Barrier Island Restoration Feasibility Assessment project, presented separately, integrates these habitat model results into a structured decision-making framework that accounts for competing objectives. Collectively, this information provides insights to natural resource managers and planners on how a restoration measure may maintain or impede natural coastal processes and provide information critical for making future-focused decisions regarding barrier island restoration.

Alabama↗
USGS2024

Two-dimensional hydraulic model for the Chain of Lakes on the Fox River near McHenry, Illinois

Forecasts of flows entering and leaving the Chain of Lakes on the Fox River in northeastern Illinois are critical information to water-resource managers operating the Stratton Dam at McHenry, Illinois. These managers determine the optimal operation of the Stratton Dam at McHenry, Ill., to manage Chain of Lakes pool levels and to help mitigate flooding in the Chain of Lakes system. In 2020, the U.S. Geological Survey (USGS) and the Illinois Department of Natural Resources–Office of Water Resources (IDNR–OWR) began a cooperative study to develop a system to enable engineers and planners to simulate and communicate water-surface elevations and flows and to proactively prepare for runoff events forecasted for the Chain of Lakes. The hydraulic model described in this report may be helpful to the IDNR–OWR for optimizing the operation of the Stratton Dam and includes the implementation of three newly installed torque-tube crest gates that became operational in 2020. The hydraulic model for the Chain of Lakes was developed using the Hydrologic Engineering Center–River Analysis System program (version 6.5). The hydraulic model was used to simulate water-surface elevations and flows through the 18.5-mile Chain of Lakes system to 1.7 miles downstream from the Stratton Dam. Five USGS streamgages within the study area were used as reference points for model calibration and initial water-surface elevations for beginning a simulation. The hydraulic model was calibrated to three runoff events that incorporated the design specifications and observed gate operations of the Stratton Dam; furthermore, the hydraulic model simulated a validation event and a substantial flooding event during July 2017. The July 2017 event predated the torque-tube crest gate installation but nevertheless tested the performance of the model for such a substantial event. The model simulation results were a good fit to observed records at USGS streamgages with simulated peak water-surface elevations within −0.36–0.15 foot of observed events. The hydraulic model was then implemented into a forecast workflow that streamlines implementation of model inputs and documents the model outputs tailored to IDNR–OWS Stratton Dam operations and interpretations of simulated water-surface elevations and flows.

Illinois↗
USGS2000

Viability of piping plover Charadrius melodus metapopulations

The metapopulation viability analysis package, VORTEX , was used to examine viability and recovery objectives for piping plovers Charadrius melodus , an endangered shorebird that breeds in three distinct regions of North America. Baseline models indicate that while Atlantic Coast populations, under current management practices, are at little risk of near-term extinction, Great Plains and Great Lakes populations require 36% higher mean fecundity for a significant probability of persisting for the next 100 years. Metapopulation structure (i.e. the delineation of populations within the metapopulation) and interpopulation dispersal rates had varying effects on model results; however, spatially-structured metapopulations exhibited lower viability than that reported for single-population models. The models were most sensitive to variation in survivorship; hence, additional mortality data will improve their accuracy. With this information, such models become useful tools in identifying successful management objectives; and sensitivity analyses, even in the absence of some data, may indicate which options are likely to be most effective. Metapopulation viability models are best suited for developing conservation strategies for achieving recovery objectives based on maintaining an externally derived, target population size and structure.

Biological Conservation↗
USGS2005

Development of a comprehensive watershed model applied to study stream yield under drought conditions

We developed a model code to simulate a watershed's hydrology and the hydraulic response of an interconnected stream-aquifer system, and applied the model code to the Lower Republican River Basin in Kansas. The model code links two well-known computer programs: MODFLOW (modular 3-D flow model), which simulates ground water flow and stream-aquifer interaction; and SWAT (soil water assessment tool), a soil water budget simulator for an agricultural watershed. SWAT represents a basin as a collection of subbasins in terms of soil, land use, and weather data, and simulates each subbasin on a daily basis to determine runoff, percolation, evaporation, irrigation, pond seepage, and crop growth. Because SWAT applies a lumped hydrologic model to each sub-basin, spatial heterogeneities with respect to factors such as soil type and land use are not resolved geographically, but can instead be represented statistically. For the Republican River Basin model, each combination of six soil types and three land uses, referred to as a hydrologic response unit (HRU), was simulated with a separate execution of SWAT. A spatially weighted average was then taken over these results for each hydrologic flux and time step by a separate program, SWBAVG. We wrote a package for MODFLOW to associate each subbasin with a subset of aquifer grid cells and stream reaches, and to distribute the hydrologic fluxes given for each subbasin by SWAT and SWBAVG over MODFLOW's stream-aquifer grid to represent tributary flow, surface and ground water diversions, ground water recharge, and evapotranspiration from ground water. The Lower Republican River Basin model was calibrated with respect to measured ground water levels, streamflow, and reported irrigation water use. The model was used to examine the relative contributions of stream yield components and the impact on stream yield and base flow of administrative measures to restrict irrigation water use during droughts. Model results indicate that tributary flow is the dominant component of stream yield and that reduction of irrigation water use produces a corresponding increase in base flow and stream yield. However, the increase in stream yield resulting from reduced water use does not appear to be of sufficient magnitude to restore minimum desirable streamflows.

Groundwater↗
USGS2013

Model documentation for relations between continuous real-time and discrete water-quality constituents in Cheney Reservoir near Cheney, Kansas, 2001--2009

Cheney Reservoir, located in south-central Kansas, is one of the primary water supplies for the city of Wichita, Kansas. The U.S. Geological Survey has operated a continuous real-time water-quality monitoring station in Cheney Reservoir since 2001; continuously measured physicochemical properties include specific conductance, pH, water temperature, dissolved oxygen, turbidity, fluorescence (wavelength range 650 to 700 nanometers; estimate of total chlorophyll), and reservoir elevation. Discrete water-quality samples were collected during 2001 through 2009 and analyzed for sediment, nutrients, taste-and-odor compounds, cyanotoxins, phytoplankton community composition, actinomycetes bacteria, and other water-quality measures. Regression models were developed to establish relations between discretely sampled constituent concentrations and continuously measured physicochemical properties to compute concentrations of constituents that are not easily measured in real time. The water-quality information in this report is important to the city of Wichita because it allows quantification and characterization of potential constituents of concern in Cheney Reservoir. This report updates linear regression models published in 2006 that were based on data collected during 2001 through 2003. The update uses discrete and continuous data collected during May 2001 through December 2009. Updated models to compute dissolved solids, sodium, chloride, and suspended solids were similar to previously published models. However, several other updated models changed substantially from previously published models. In addition to updating relations that were previously developed, models also were developed for four new constituents, including magnesium, dissolved phosphorus, actinomycetes bacteria, and the cyanotoxin microcystin. In addition, a conversion factor of 0.74 was established to convert the Yellow Springs Instruments (YSI) model 6026 turbidity sensor measurements to the newer YSI model 6136 sensor at the Cheney Reservoir site. Because a high percentage of geosmin and microcystin data were below analytical detection thresholds (censored data), multiple logistic regression was used to develop models that best explained the probability of geosmin and microcystin concentrations exceeding relevant thresholds. The geosmin and microcystin models are particularly important because geosmin is a taste-and-odor compound and microcystin is a cyanotoxin.

Kansas↗
USGS2012

Uncertainty

Management decisions will often be directly informed by model predictions. However, we now know there can be no expectation of a single ‘true’ model; thus, model results are uncertain. Understandable reporting of underlying uncertainty provides necessary context to decision-makers, as model results are used for management decisions. This, in turn, forms a mechanism by which groundwater models inform a risk-management framework because uncertainty around a prediction provides the basis for estimating the probability or likelihood of some event occurring. Given that the consequences of management decisions vary, it follows that the extent of and resources devoted to an uncertainty analysis may depend on the consequences. For events with low impact, a qualitative, limited uncertainty analysis may be sufficient for informing a decision. For events with a high impact, on the other hand, the risks might be better assessed and associated decisions made using a more robust and comprehensive uncertainty analysis. The purpose of this chapter is to provide guidance on uncertainty analysis through discussion of concepts and approaches, which can vary from heuristic (i.e. the modeller’s assessment of prediction uncertainty based on trial and error and experience) to a comprehensive, sophisticated, statistics-based uncertainty analysis. Most of the material presented here is taken from Doherty et al. (2010) if not otherwise cited. Although the treatment here is necessarily brief, the reader can find citations for the source material and additional references within this chapter.

Book chapter↗
USGS2011

Numerical simulation of groundwater flow for the Yakima River basin aquifer system, Washington

A regional, three-dimensional, transient numerical model of groundwater flow was constructed for the Yakima River basin aquifer system to better understand the groundwater-flow system and its relation to surface-water resources. The model described in this report can be used as a tool by water-management agencies and other stakeholders to quantitatively evaluate proposed alternative management strategies that consider the interrelation between groundwater availability and surface-water resources. The model was constructed using the U.S. Geological Survey finite-difference model MODFLOW. The model uses 1,000-foot grid cells that subdivide the model domain by 600 rows and 600 columns. Forty-eight hydrogeologic units in the model are included in 24 model layers. The Yakima River, all major tributaries, and major agricultural drains are included in the model as either drain cells or streamflow-routing cells. Recharge was estimated from previous work using physical process models. Groundwater pumpage specified in the model is derived from monthly pumpage values previously estimated from another component of this study. The pumpage values include estimates for wells with standby/reserve rights that are used in drought years. The model was calibrated to the transient conditions for October 1959 to September 2001. Calibration was completed by using traditional trial-and-error methods and automated parameter-estimation techniques. The model simulates the shape and slope of the water table that generally is consistent with mapped water levels. At well observation points, the average difference between simulated and measured hydraulic heads is -49 feet with a root-mean-square error divided by the total difference in water levels of 4 percent. Simulated river streamflow was compared to measured streamflow at seven sites. Annual differences between measured and simulated streamflow for the sites ranged from 1 to 9 percent. Calibrated model output includes a 42-year estimate of a monthly water budget for the aquifer system. Five applications (scenarios) of the model were completed to obtain a better understanding of the relation between pumpage and surface-water resources and groundwater levels. For the first three scenarios, the calibrated transient model was used to simulate conditions without: (1) pumpage from all hydrogeologic units, (2) pumpage from basalt hydrogeologic units, and (3) exempt-well pumpage. The simulation results indicated potential streamflow capture by the existing pumpage from 1960 through 2001. The quantity of streamflow capture generally was inversely related to the total quantity of pumpage eliminated in the model scenarios. For the fourth scenario, the model simulated 1994 through 2001 under existing conditions with additional pumpage estimated for pending groundwater applications. The differences between the calibrated model streamflow and this scenario indicated additional decreases in streamflow of 91 cubic feet per second in the model domain. Existing conditions representing 1994 through 2001 were projected through 2025 for the fifth scenario and indicated additional streamflow decreases of 38 cubic feet per second and groundwater-level declines.

Scientific Investigations Report↗
USGS1977

Geohydrology of Muscatine Island, Muscatine County, Iowa

Muscatine Island is a wide segment of the west bank of the Mississippi River flood plain that covers about 50 square miles in Muscatine and Louisa Counties; the project area encompasses the 30 square miles in Muscatine County. The flood plain is underlain by thick, permeable alluvial deposits that comprise a water-table aquifer that is developed extensively for water supplies in the area. The aquifer consists principally of sand and gravel, interbedded with lenses of silt and clay. Its saturated thickness ranges from about 40 to 140 feet. The transmissivity and storage coefficients of the aquifer range from about 20,000 ft. 2 /day and 0.15. respectively, in the western part of the Island to about 39,500 ft.2/day and 0.24 in the eastern part. The amount of water stored in the aquifer, under normal conditions, is about 100 billion gallons. Discharge from the aquifer is principally by pumpage, which has increased from about 1 mgd (million gallons per day) in 1906 to about 37 mgd in 1970. About 2.5 mgd is normally lost to seepage and evapotranspiration along a 9-mile reach of Muscatine Slough in Muscatine County. About 0.9 mgd is discharged by evaporation from gravel pits. Recharge to the aquifer is by induced infiltration from the Mississippi River, seepage from the river during major flood events, precipitation, and seepage from the underlying limestone bedrock. Induced infiltration provides about 80 to 85 percent of the water withdrawn from the principal pumping centers along the river and also replaces about 70 to 80 percent of the water that is evaporated from the gravel pits; this amounted to about 30 mgd in 1971. Additional significant recharge from the river occurs during major floods, when prolonged high stages provide the head for considerable underflow to the aquifer. Recharge from precipitation on the Island was calculated to average about 6inches per year or about 0.3 mgd per square mile. Seepage from bedrock is significant and is attributed to the increased head differential between the alluvial and bedrock aquifers in the areas of major pumping. The chemical constituents of water from the aquifer are generally within the recommended limits established by the U. S. Public Health Service for drinking water. Stresses on the hydrologic system have affected the position and configuration of the water table and the chemical quality of the ground water. The large-scale withdrawals, which began at the principal pumping centers in 1946, have caused the water table to decline from about 1 foot in the interior of the Island to about 5 feet near the edges of the main pumping centers; the decline was more than 8 feet under the pumping centers. A slight increase in hardness of water from riverward wells in the pumping centers is attributed to the induced infiltration of slightly harder river water; a noticeable increase in hardness and iron content in water from landward wells is attributed to seepage of water from the bedrock. In the central irrigated area, which is underlain by very permeable, highly drained soils that are mulched with organic fertilizers, the nitrate content of the ground water is as high as 46 mg/l (milligrams per liter). Land-use practices have had, and probably will continue to have, an impact on the quality and quantity of water available in the system. The hydrologic system in 1971 was in dynamic equilibrium or in near-equilibrium with the stresses imposed on it to that date. This equilibrium would be disturbed by any additional stresses on the system and water levels would change until a new equilibrium was established. The effects of future stresses can be reasonably predicted by developing a digital model of the system. The data to develop such a model are available in this report. Continued and expanded monitoring of water levels would provide data for better model verification. Periodic monitoring of nitrate and other chemical constituents would permit early detection of changes in concentration before the concentrations reached excessive levels.

Iowa↗
USGS1982

Susitna Hydroelectric Project: terrestrial environmental workshop and preliminary simulation model

The technical feasibility, economic viability, and environmental impacts of a hydroelectric development project in the Susitna River Basin are being studied by Acres American, Inc. on behalf of the Alaska Power Authority. As part of these studies, Acres American recently contracted LGL Alaska Research Associates, Inc. to coordinate the terrestrial environmental studies being performed by the Alaska Department of Fish and Game and, as subcontractors to LGL, several University of Alaska research groups. LGL is responsible for further quantifying the potential impacts of the project on terrestrial wildlife and vegetation, and for developing a plan to mitigate adverse impacts on the terrestrial environment. The impact assessment and mitigation plan will be included as part of a license application to the Federal Energy Regulatory Commission (FERC) scheduled for the first quarter of 1983. The quantification of impacts, mitigation planning, and design of future research is being organized using a computer simulation modelling approach. Through a series of workshops attended by researchers, resource managers, and policy-makers, a computer model is being developed and refined for use in the quantification of impacts on terrestrial wildlife and vegetation, and for evaluating different mitigation measures such as habitat enhancement and the designation of replacement lands to be managed by wildlife habitat. This report describes the preliminary model developed at the first workshop held August 23 -27, 1982 in Anchorage.

Report↗
USGS2015

Revision and proposed modification for a total maximum daily load model for Upper Klamath Lake, Oregon

This report presents Phase 2 of the review and development of the mass balance water-quality model, originally developed in 2001, that guided establishment of the phosphorus (P) total maximum daily load (TMDL) for Upper Klamath and Agency Lakes, Oregon. The purpose of Phase 2 was to incorporate a longer (19-year) set of external phosphorus loading data into the lake TMDL model than had originally been available, and to develop a proof-of-concept method for modeling algal mortality and the consequent decrease in chlorophyll a that had not been possible with the 2001 TMDL model formulation. Using the extended 1991–2010 external phosphorus loading dataset, the lake TMDL model was recalibrated following the same procedures outlined in the Phase 1 review. The version of the model selected for further development incorporated an updated sediment initial condition, a numerical solution method for the chlorophyll a model, changes to light and phosphorus factors limiting algal growth, and a new pH-model regression, which removed Julian day dependence in order to avoid discontinuities in pH at year boundaries. This updated lake TMDL model was recalibrated using the extended dataset in order to compare calibration parameters to those obtained from a calibration with the original 7.5-year dataset. The resulting algal settling velocity calibrated from the extended dataset was more than twice the value calibrated with the original dataset, and, because the calibrated values of algal settling velocity and recycle rate are related (more rapid settling required more rapid recycling), the recycling rate also was larger than that determined with the original dataset. These changes in calibration parameters highlight the uncertainty in critical rates in the Upper Klamath Lake TMDL model and argue for their direct measurement in future data collection to increase confidence in the model predictions.

Oregon↗
USGS1984

A workshop model simulating fate and effect of drilling muds and cuttings on benthic communities

Oil and gas exploration and production at marine sites has generated concern over potential environmental impacts resulting from the discharge of spent drilling muds and cuttings. This concern has led to a broad array of publicly and privately sponsored research. This report described a cooperative modeling effort designed to focus information resulting from this research through construction of explicit equations that simulate the potential impacts of discharge drilling fluids (muds) and cuttings on marine communities. The model is the result of collaboration among more than 30 scientists. The principal cooperating organizations were the E.S. Environmental Protection Agency, the U.S. Minerals Management Service, the Offshore Operators Committee, and the Alaska Oil and Gas Association. The overall simulation model can be conceptualized as three connected submodels: Discharge and Plume Fate, Sediment Redistribution, and Benthic Community Effects. On each day of simulation, these submodels are executed in sequence, with flows of information between submodels. The Benthic Community Effects submodel can be further divided into sections that calculate mortality due to burial, mortality due to toxicity, mortality due to resuspension disturbance, and growth of the community. The model represents a series of seven discrete 1-m 2 plots at specified distances along a transect in one direction away from a discharge point. It consists of coupled difference equations for which parameter values can easily be set to evaluate different conditions or to examine the sensitivity of output to various assumptions. Sets of parameter values were developed to represent four general cases or scenarios: (1) a shallow (5 m), cold environment with ice cover during a substantial fraction of the year, such as might be encountered in the Beaufort Sea, Alaska; (2) a shallow (20 m), temperate environment, such as might be encountered in the Gulf of Mexico; (3) a deeper (80 m), temperate environment, such as might be encountered in the Gulf of Mexico; and (4) a very deep (1,000 m) environment, such as might be encountered on the Atlantic slope. The focus of the modeling effort was on the connection of a reasonable representation of physical fate to the biological responses of populations, rather than on highly detailed representations of individual processes. For example, the calculations of physical fate are not as detailed as those in the recently published model of Brandsma et al. (1983). The value of the model described herein is in the broad scope of processes that are explicitly represented and linked together. The model cannot be considered to produce reliable predictions of the quantitative impacts of discharged drilling fluids and cuttings on biological populations at a particular site. Limitations of the model in predicting integrated fate and effects can be traced to three general areas: level of refinement of the algorithms used in the model; lack of understanding of the processes determining fate and effects; and parameter and data values. Despite the limitations, several qualitative conclusions concerning both potential impacts and the importance of various remaining data gaps can be drawn from the modeling effort. These include: (1) Simple, unequivocal conclusions about fate and effects across geographical regions and drilling operations are difficult, if not misleading, due to the large amount of variability in characteristics of discharged materials (e.g., oil content and toxicity), discharge conditions (e.g., duration of drilling operations), physical environments (e.g., water depth, current direction, and sediment disturbance regimes), and biological communities (e.g., intrinsic growth rates). Different combinations of these characteristics can result in substantial differences in simulated environmental fate and biological effects. For examples, simulated recovery in some high-energy environments occurs within months after the cessation of discharge operations, even at heavily impacted sites, whereas simulated recover in some low-energy environments takes years at heavily impacted sites. <2) Considerable difficulties remain in the reliable extrapolation of results from laboratory toxicity experiments to predictions of population effects in the field. (3) The volume of material discharged and duration of operations in the production drilling operations simulated by the model are sufficient to produce substantial simulated biological impacts at some plots, both in terms of differences from a control plot during the period of discharge operations, and in terms of the recovery period following the perturbations. Evaluation of the significance of potential effects involves the following factors: • Definition of a specific spatial and temporal reference frame (e.g., What is the natural variation? Is 1 year to be considered a "long" or "short" time? Is 50 m to be considered a "large" or "trivial" distance? • Consideration of rare or unique resources and particularly sensitive biotic assemblages. • Consideration of the potential for long term, cumulative effects. Some of these aspects are clearly beyond the scope of this modeling efforts (e.g., the model does not simulate the long term fate of resuspended material). The model does, however, contain an internal "reference frame" by comparison to simulated behavior at a control plot. The model, in general, simulates substantial "natural" variation at the reference or control plots, both over time, due to sediment disturbance events in medium to high energy environments, and over space, due to geographically varying conditions, such as water depth and current regime.

Report↗
USGS2006

StreamVOC - A deterministic source-apportionment model to estimate volatile organic compound concentrations in rivers and streams

This report documents the construction and verification of the model, StreamVOC, that estimates (1) the time- and position-dependent concentrations of volatile organic compounds (VOCs) in rivers and streams as well as (2) the source apportionment (SA) of those concentrations. The model considers how different types of sources and loss processes can act together to yield a given observed VOC concentration. Reasons for interest in the relative and absolute contributions of different sources to contaminant concentrations include the need to apportion: (1) the origins for an observed contamination, and (2) the associated human and ecosystem risks. For VOCs, sources of interest include the atmosphere (by absorption), as well as point and nonpoint inflows of VOC-containing water. Loss processes of interest include volatilization to the atmosphere, degradation, and outflows of VOC-containing water from the stream to local ground water. This report presents the details of StreamVOC and compares model output with measured concentrations for eight VOCs found in the Aberjona River at Winchester, Massachusetts. Input data for the model were obtained during a synoptic study of the stream system conducted July 11-13, 2001, as part of the National Water-Quality Assessment (NAWQA) Program of the U.S. Geological Survey. The input data included a variety of basic stream characteristics (for example, flows, temperature, and VOC concentrations). The StreamVOC concentration results agreed moderately well with the measured concentration data for several VOCs and provided compound-dependent SA estimates as a function of longitudinal distance down the river. For many VOCs, the quality of the agreement between the model-simulated and measured concentrations could be improved by simple adjustments of the model input parameters. In general, this study illustrated: (1) the considerable difficulty of quantifying correctly the locations and magnitudes of ground-water-related sources of contamination in streams; and (2) that model-based estimates of stream VOC concentrations are likely to be most accurate when the major sources are point sources or tributaries where the spatial extent and magnitude of the sources are tightly constrained and easily determined.

Scientific Investigations Report↗