DLG2ISM, a Fortran program to read DLG-3 optional format digital data files into the VAX/VMS version of the interactive surface modeling software package
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Modeling of ecosystems is a part of the U.S. Environmental Protection Agency’s protocol for developing site-specific selenium guidelines for protection of aquatic life. Selenium as an environmental contaminant is known to bioaccumulate and cause reproductive effects in fish and wildlife. Here we apply a modeling methodology—ecosystem-scale selenium modeling—to understand and document the scientific basis for predicting and validating ecological protection for Lake Koocanusa, a transboundary reservoir between Montana and British Columbia. A comprehensive set of site-specific data compiled from public databases (Federal, State, and Provincial) and reports by Teck Coal Ltd., is available in a companion U.S. Geological Survey data release. The tissue guideline used within modeling here to assess protection is the U.S. Environmental Protection Agency’s national selenium guideline for whole-body fish (dry weight); however, other numeric values for a whole-body guideline or other tissue types may be assumed if applicable tissue-to-tissue conversion factors are available. We consider the report assembled here as a working document that presents a model that can effectively address and structure the needs of (1) scientific understanding in representing the lake’s ecosystem and selenium biodynamics and (2) policy and management development during a decision-making process, but it is open to modification and updating as more ecologically detailed data become available. The approach brings together the main concerns involved in selenium toxicity: likelihood of high exposure, inherent species sensitivity, and close connectivity of ecosystem characteristics and behavioral ecology of predators. Detailed site-specific modeling equations are provided to document the linked factors that determine the responses of ecosystems to selenium. A series of scenarios quantifies the implications of choices of site-specific variables including food-web species, bioavailability of particulate material, and partitioning between the dissolved and particulate phases at the base of food webs. A gradient mapping tool applied to Lake Koocanusa provides a precedent for ecosystem-scale modeling of lakes by recognizing the importance of lake strata and hydrodynamics as components of modeling. Data requirements for ecosystem modeling, including ecological and hydrological process information fundamental to the dietary biodynamics of selenium in site-specific food webs, were assessed as a precursor to model validation for Lake Koocanusa. Understanding these relationships is necessary to connect modeling outcomes to reproductive effects and establish boundaries, in the case of Lake Koocanusa, for the influences of dam operation, fish-community viability, and its Clean Water Act impaired 303(d)-listing status on ecosystem function. We find that an assemblage of conditions affects the representation of Lake Koocanusa’s ecosystem within modeling scenarios but that the constructed gradient maps, mechanistic model, and associated bioaccumulation potentials portray and quantify the variables that are determinative to protection of predator species. Ecological and hydrological sorting of compiled individual data points on a site- and species-specific basis helps identify and address model uncertainties. Sources of uncertainty include (1) the scarcity of data for some environmental media compartments across time and locations, (2) the complexity of hydrodynamic conditions that can lead to seasonal ecological disconnects such as in selenium partitioning from water into particulates, and (3) the functional status of Lake Koocanusa’s ecosystem because of cumulative effects of various environmental stresses (for example, fish-community changes, flow regime changes, parasites, gonadal dysfunction, and increasing mining input-selenium concentrations since 1984). To this last point, it is important to determine where Lake Koocanusa is in an impairment-restoration cycle so as not to base protection on survivor bias, the maintenance of a currently degraded ecosystem, or normalized toxicity. In a broader context, one of the overall consequences of revised selenium regulations is that their derivation is now dependent on being able to define and understand the status of the ecosystem on which protection is based.
The Colorado River and its tributaries supply water to more than 35 million people in the United States and 3 million people in Mexico, irrigating more than 4.5 million acres of farmland, and generating about 12 billion kilowatt hours of hydroelectric power annually. The Upper Colorado River Basin, encompassing more than 110,000 square miles (mi 2 ), contains the headwaters of the Colorado River (also known as the River) and is an important source of snowmelt runoff to the River. Groundwater discharge also is an important source of water in the River and its tributaries, with estimates ranging from 21 to 58 percent of streamflow in the upper basin. Planning for the sustainable management of the Colorado River in future climates requires an understanding of the Upper Colorado River Basin groundwater system. This report documents input datasets for a Soil-Water Balance groundwater recharge model that was developed for the Upper Colorado River Basin.
We conducted a reward band study on mallards ( Anas platyrhynchos ) to estimate and test hypotheses about sources of variation in band reporting rate. We banded 25,398 mallards with standard and 100 reward bands (3 mallards banded with standard bands for every reward-banded mallard) during preseason (Jul-Sep), 1988. We used a series of multinomial models to model the resulting 2,776 band recoveries from 1988 to 1991. Estimates of reporting rate for males shot in 10 harvest areas ranged from 0.29 to 0.46 and averaged 0.38 (SE = 0.020). We found evidence ( P < 0.01) of geographic variation in reporting rates, but not of smooth latitudinal or longitudinal gradients. There was evidence ( P = 0.07) of lower reporting rates for females than males, especially in prairie Canada and the Central Flyway. Except for young males in the northern Atlantic Flyway, estimated harvest rates were lower than historical estimates, as expected from recent restrictive hunting regulations. Patterns of geographic and agesex variation in harvest rates were similar to those obtained using historical band-recovery data.
References to more than 550 reports, articles, and maps are listed alphabetically by author and are indexed by subject. The subject index includes geographic-area terms. Citations from 69 series are included; series are listed separately. The publications listed report the results of U.S. Geological Survey research and field projects throughout the Nation concerning earth-science aspects of waste management and disposal. They include organic, inorganic, and radioactive wastes and related topics such as mathematical models of solute transport. Most of the references are to (1) Geological Survey report series such as Water-Supply Papers, Professional Papers, Bulletins, Circulars, Water-Resources Investigations, and Open-File Reports, (2) technical journals of professional organizations, or (3) reports by other Federal and State agencies.
Executive Summary This report expands the Water Science Strategy that was begun in the USGS Science Strategy, “Facing Tomorrow’s Challenges—U.S. Geological Survey Science in the Decade 2007–2017” (U.S. Geological Survey, 2007). The report looks at the relevant issues facing society and develops a strategy built around observing, understanding, predicting, and delivering water science for the next 5 to 10 years by building new capabilities, tools, and delivery systems to meet the Nation’s water-resource needs. This report begins by presenting the vision of water science for the USGS and the societal issues that are influenced by, and in turn influence, the water resources of our Nation. The essence of the Water Strategic Science Plan is built on the concept of “water availability,” defined as spatial and temporal distribution of water quantity and quality, as related to human and ecosystem needs, as affected by human and natural influences . The report also describes the core capabilities of the USGS in water science—the strengths, partnerships, and science integrity that the USGS has built over its 130-year history. Nine priority actions are presented in the report, which combine and elevate the numerous specific strategic actions listed throughout the report. Priority actions were developed as a means of providing the audience of this report with a list for focused attention, even if resources and time limit the ability of managers to address all of the strategic actions in the report. Priority actions focus on the following: Improve integrated science planning for water. Expand and enhance water-resource monitoring networks. Characterize the water cycle through development of state-of-the-art 3-D/4-D hydrogeologic framework models at multiple scales. Clarify the linkage between human water use (engineered hydrology) and the water cycle (natural hydrology). Advance ecological flow science. Provide flood-inundation science and information. Develop rapid deployment teams for water-related emergencies. Conduct integrated watershed assessment, research, and modeling. Deliver water data and analyses to the Nation. The body of the report is presented as a hierarchal set of 5 goals, 14 objectives, and 27 strategic actions that the USGS should undertake to advance water science through year 2022. The goals deal with: Providing society the information it needs regarding the amount and quality of water in all components of the water cycle at high temporal and spatial resolution, nationwide; Advancing our understanding of processes that determine water availability; Predicting changes in the quantity and quality of water resources in response to changing climate, population, land use, and management scenarios; Anticipating and responding to water-related emergencies and conflicts; and Delivering timely hydrologic data, analyses, and decision-support tools seamlessly across the Nation to support water-resource decisions. Scientific information produced on water resources would be without value if it were not communicated to society in a fashion that can inform decisions and actions. Therefore, the chapter following the goals describes how the USGS should inform, involve, and educate society about the science it produces. This includes discussions on local outreach and the use of social media for effective communication. This report concludes with a chapter devoted to the crosscutting science issues of the Water Mission Area with the other USGS Mission Areas: Climate and Land Use Change, Core Science Systems, Ecosystems, Energy and Minerals, Environmental Health Science, and Natural Hazards. Not one of these Mission Areas stands alone—all must work together and integrate their actions to fulfill the USGS science mission for the future. This final chapter identifies the important linkages that must be realized and maintained for this integration to occur.
Forecasts of flows entering and leaving the Chain of Lakes reservoir on the Fox River in northeastern Illinois are critical information to water-resource managers who determine the optimal operation of the dam at McHenry, Illinois, to help minimize damages to property and loss of life because of flooding on the Fox River. In 2014, the U.S. Geological Survey; the Illinois Department of Natural Resources, Office of Water Resources; and National Weather Service, North Central River Forecast Center began a cooperative study to develop a system to enable engineers and planners to simulate and communicate flows and to prepare proactively for precipitation events in near real time in the upper Fox River watershed. The purpose of this report is to document the development and evaluation of the Chain of Lakes reservoir model developed in this study. The reservoir model for the Chain of Lakes was developed using the Hydrologic Engineering Center–Reservoir System Simulation program. Because of the complex relation between the dam headwater and reservoir pool elevations, the reservoir model uses a linear regression model that relates dam headwater elevation to reservoir pool elevation. The linear regression model was developed using 17 U.S. Geological Survey streamflow measurements, along with the gage height in the reservoir pool and the gage height at the dam headwater. The Nash-Sutcliffe model efficiency coefficients for all three linear regression model variables ranged from 0.90 to 0.98. The reservoir model performance was evaluated by graphically comparing simulated and observed reservoir pool elevation time series during nine periods of high pool elevation. In addition, the peak elevations during these time periods were graphically compared to the closest-in-time observed pool elevation peak. The mean difference in the simulated and observed peak elevations was -0.03 feet, with a standard deviation of 0.19 feet. The Nash-Sutcliffe coefficient for peak prediction was calculated as 0.94. Evaluation of the model based on accuracy of peak prediction and the ability to simulate an elevation time series showed the performance of the model was satisfactory.