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At least 991 records · Page 55Linked to original sources
USGS2010

Simulation of Runoff and Reservoir Inflow for Use in a Flood-Analysis Model for the Delaware River, Pennsylvania, New Jersey, and New York, 2004-2006

A model was developed to simulate inflow to reservoirs and watershed runoff to streams during three high-flow events between September 2004 and June 2006 for the main-stem subbasin of the Delaware River draining to Trenton, N.J. The model software is a modified version of the U.S. Geological Survey (USGS) Precipitation-Runoff Modeling System (PRMS), a modular, physically based, distributed-parameter modeling system developed to evaluate the impacts of various combinations of precipitation, climate, and land use on surface-water runoff and general basin hydrology. The PRMS model simulates time periods associated with main-stem flooding that occurred in September 2004, April 2005, and June 2006 and uses both daily and hourly time steps. Output from the PRMS model was formatted for use as inflows to a separately documented reservoir and riverrouting model, the HEC-ResSim model, developed by the U.S. Army Corps of Engineers Hydrologic Engineering Center to evaluate flooding. The models were integrated through a graphical user interface. The study area is the 6,780 square-mile watershed of the Delaware River in the states of Pennsylvania, New Jersey, and New York that drains to Trenton, N.J. A geospatial database was created for use with a geographic information system to assist model discretization, determine land-surface characterization, and estimate model parameters. The USGS National Elevation Dataset at 100-meter resolution, a Digital Elevation Model (DEM), was used for model discretization into streams and hydrologic response units. In addition, geospatial processing was used to estimate initial model parameters from the DEM and other data layers, including land use. The model discretization represents the study area using 869 hydrologic response units and 452 stream segments. The model climate data for point stations were obtained from multiple sources. These sources included daily data for 22 National Weather Service (NWS) Cooperative Climate Station network stations, hourly data for 15 stations from the National Climatic Data Center, hourly data for 1 station from the NWS Middle Atlantic River Forecast Center records, and daily and hourly data for 7 stations operated by the New York City Department of Environmental Protection. The NWS Multisensor Precipitation Estimate data set for 2001-2007 was used for computing daily precipitation for the model and for computing hourly precipitation for storm simulation periods. Calibration of the PRMS model included regression and optimization algorithms, as well as manual adjustments of model parameters. The general goal of the calibration procedure was to minimize the difference between discharge measured at USGS streamgages and the corresponding discharge simulated by the model. Daily streamflow data from 35 USGS streamgages were used in model calibration. The streamflow data represent areas draining from 20.2 to 6,780 square miles. The PRMS model simulates reservoir inflow and watershed runoff for use as input into HECResSim for the purpose of evaluating and comparing the effects of different watershed conditions on main-stem flooding in the Delaware River watershed draining to Trenton, N.J. The PRMS model is useful as a planning tool to simulate the effects of land-use changes and different antecedent conditions on local runoff and reservoir inflow and, as input to the HEC-ResSim model, on flood flows in the main stem of the Delaware River.

Open-File Report↗
USGS2010

Evaluation of Water Year 2011 Glen Canyon Dam Flow Release Scenarios on Downstream Sand Storage along the Colorado River in Arizona

This report describes numerical modeling simulations of sand transport and sand budgets for reaches of the Colorado River below Glen Canyon Dam. Two hypothetical Water Year 2011 annual release volumes were each evaluated with six hypothetical operational scenarios. The six operational scenarios include the current operation, scenarios with modifications to the monthly distribution of releases, and scenarios with modifications to daily flow fluctuations. Uncertainties in model predictions were evaluated by conducting simulations with error estimates for tributary inputs and mainstem transport rates. The modeling results illustrate the dependence of sand transport rates and sand budgets on the annual release volumes as well as the within year operating rules. The six operational scenarios were ranked with respect to the predicted annual sand budgets for Marble Canyon and eastern Grand Canyon reaches. While the actual WY 2011 annual release volume and levels of tributary inputs are unknown, the hypothetical conditions simulated and reported herein provide reasonable comparisons between the operational scenarios, in a relative sense, that may be used by decision makers within the Glen Canyon Dam Adaptive Management Program.

Open-File Report↗
USGS2010

Estimating Monthly Water Withdrawals, Return Flow, and Consumptive Use in the Great Lakes Basin

Water-resource managers and planners require water-withdrawal, return-flow, and consumptive-use data to understand how anthropogenic (human) water use affects the hydrologic system. Water models like MODFLOW and GSFLOW use calculations and input values (including water-withdrawal and return flow data) to simulate and predict the effects of water use on aquifer and stream conditions. Accurate assessments of consumptive use, interbasin transfer, and areas that are on public supply or sewer are essential in estimating the withdrawal and return-flow data needed for the models. As the applicability of a model to real situations depends on accurate input data, limited or poor water-use data hampers the ability of modelers to simulate and predict hydrologic conditions. Substantial differences exist among the many agencies nationwide that are responsible for compiling water-use data including what data are collected, how the data are organized, how often the data are collected, quality assurance, required level of accuracy, and when data are released to the public. This poster presents water-use information and estimation methods summarized from recent U.S. Geological Survey (USGS) reports with the intent to assist water-resource managers and planners who need estimates of monthly water withdrawals, return flows, and consumptive use. This poster lists references used in Shaffer (2009) for water withdrawals, consumptive use, and return flows. Monthly percent of annual withdrawals and monthly consumptive-use coefficients are used to compute monthly water withdrawals, consumptive use, and return flow for the Great Lakes Basin.

Open-File Report↗
USGS2010

Implementation of the Next Generation Attenuation (NGA) ground-motion prediction equations in Fortran and R

This report presents two methods for implementing the earthquake ground-motion prediction equations released in 2008 as part of the Next Generation Attenuation of Ground Motions (NGA-West, or NGA) project coordinated by the Pacific Earthquake Engineering Research Center (PEER). These models were developed for predicting ground-motion parameters for shallow crustal earthquakes in active tectonic regions (such as California). Of the five ground-motion prediction equations (GMPEs) developed during the NGA project, four models are implemented: the GMPEs of Abrahamson and Silva (2008), Boore and Atkinson (2008), Campbell and Bozorgnia (2008), and Chiou and Youngs (2008a); these models are abbreviated as AS08, BA08, CB08, and CY08, respectively. Since site response is widely recognized as an important influence of ground motions, engineering applications typically require that such effects be modeled. The model of Idriss (2008) is not implemented in our programs because it does not explicitly include site response, whereas the other four models include site response and use the same variable to describe the site condition (VS30). We do not intend to discourage the use of the Idriss (2008) model, but we have chosen to implement the other four NGA models in our programs for those users who require ground-motion estimates for various site conditions. We have implemented the NGA models by using two separate programming languages: Fortran and R (R Development Core Team, 2010). Fortran, a compiled programming language, has been used in the scientific community for decades. R is an object-oriented language and environment for statistical computing that is gaining popularity in the statistical and scientific community. Derived from the S language and environment developed at Bell Laboratories, R is an open-source language that is freely available at http://www.r-project.org/ (last accessed 11 January 2011). In R, the functions for computing the NGA equations can be loaded as an add-on user-contributed code, which is referred to as a ?package? in R. The details of the nga package (Kaklamanos and Thompson, 2010) are presented in this report. In addition, differences between the R and Fortran implementations will be discussed later in this report. The NGA models have established a new baseline for seismic hazard assessments, and they have been incorporated into the most recent national seismic hazard maps published by the U.S. Geological Survey (Petersen and others, 2008). However, many of the new models are significantly more complicated than previous GMPEs and, therefore, require a substantial investment of time to implement and validate. We hope that the scientific and engineering communities find our implementations to be useful in research and practice. Our implementations may be considered as an alternate to the Microsoft Excel spreadsheet implementation available on the PEER NGA project Web site (http://peer.berkeley.edu/ngawest/, last accessed 11 January 2011). The implementations in Fortran and R are more appropriate for performing batch calculations than the implementation in Microsoft Excel. Spreadsheets and Fortran code for some of the individual models also are available on the PEER NGA project Web site; our programs implement the four GMPEs simultaneously. Our programs give the same results as the programs on the PEER NGA Web site, but we offer some additional flexibility of input, additional methods of estimating unknown input parameters, and additional options for output. Although these programs have been used by the U.S. Geological Survey (USGS), Tufts University, and others, no warranty, expressed or implied, is made by Tufts or the USGS as to the accuracy or functioning of the programs and related material, nor shall the fact of distribution constitute any such warranty, and no responsibility is assumed by Tufts or the USGS in connection therewith.

Open-File Report↗
USGS2010

Simulation of Streamflow, Evapotranspiration, and Groundwater Recharge in the Lower San Antonio River Watershed, South-Central Texas, 2000-2007

The U.S. Geological Survey (USGS), in cooperation with the San Antonio River Authority, the Evergreen Underground Water Conservation District, and the Goliad County Groundwater Conservation District, configured, calibrated, and tested a watershed model for a study area consisting of about 2,150 square miles of the lower San Antonio River watershed in Bexar, Guadalupe, Wilson, Karnes, DeWitt, Goliad, Victoria, and Refugio Counties in south-central Texas. The model simulates streamflow, evapotranspiration (ET), and groundwater recharge using rainfall, potential ET, and upstream discharge data obtained from National Weather Service meteorological stations and USGS streamflow-gaging stations. Additional time-series inputs to the model include wastewater treatment-plant discharges, withdrawals for cropland irrigation, and estimated inflows from springs. Model simulations of streamflow, ET, and groundwater recharge were done for 2000-2007. Because of the complexity of the study area, the lower San Antonio River watershed was divided into four subwatersheds; separate HSPF models were developed for each subwatershed. Simulation of the overall study area involved running simulations of the three upstream models, then running the downstream model. The surficial geology was simplified as nine contiguous water-budget zones to meet model computational limitations and also to define zones for which ET, recharge, and other water-budget information would be output by the model. The model was calibrated and tested using streamflow data from 10 streamflow-gaging stations; additionally, simulated ET was compared with measured ET from a meteorological station west of the study area. The model calibration is considered very good; streamflow volumes were calibrated to within 10 percent of measured streamflow volumes. During 2000-2007, the estimated annual mean rainfall for the water-budget zones ranged from 33.7 to 38.5 inches per year; the estimated annual mean rainfall for the entire watershed was 34.3 inches. Using the HSPF model it was estimated that for 2000-2007, less than 10 percent of the annual mean rainfall on the study watershed exited the watershed as streamflow, whereas about 82 percent, or an average of 28.2 inches per year, exited the watershed as ET. Estimated annual mean groundwater recharge for the entire study area was 3.0 inches, or about 9 percent of annual mean rainfall. Estimated annual mean recharge was largest in water-budget zone 3, the zone where the Carrizo Sand outcrops. In water-budget zone 3, the estimated annual mean recharge was 5.1 inches or about 15 percent of annual mean rainfall. Estimated annual mean recharge was smallest in water-budget zone 6, about 1.1 inches or about 3 percent of annual mean rainfall. The Cibolo Creek subwatershed and the subwatershed of the San Antonio River upstream from Cibolo Creek had the largest and smallest basin yields, about 4.8 inches and 1.2 inches, respectively. Estimated annual ET and annual recharge generally increased with increasing annual rainfall. Also, ET was larger in zones 8 and 9, the most downstream zones in the watershed. Model limitations include possible errors related to model conceptualization and parameter variability, lack of data to quantify certain model inputs, and measurement errors. Uncertainty regarding the degree to which available rainfall data represent actual rainfall is potentially the most serious source of measurement error.

Open-File Report↗
USGS2011

Summary report of responses of key resources to the 2000 Low Steady Summer Flow experiment, along the Colorado River downstream from Glen Canyon Dam, Arizona

In the spring and summer of 2000, a series of steady discharges of water from Glen Canyon Dam on the Colorado River were used to evaluate the effects of aquatic habitat stability and water temperatures on native fish growth and survival, with a special focus on the endangered humpback chub (Gila cypha), downstream from the dam in Grand Canyon. The steady releases were bracketed by peak powerplant releases in late-May and early-September. The duration and volume of releases from the dam varied between spring and summer. The intent of the experimental hydrograph was to mimic predam river discharge patterns by including a high, steady discharge in the spring and a low, steady discharge in the summer. The hydrologic experiment was called the Low Steady Summer Flow (LSSF) experiment because steady discharges of 226 m3/s dominated the hydrograph for 4 months from June through September 2000. The experimental hydrograph was developed in response to one of the U.S. Fish and Wildlife Service's Recommended and Prudent Alternatives (RPA) in its Biological Opinion of the Operation of Glen Canyon Dam Final Environmental Impact Statement. The RPA focused on the hypothesis that seasonally adjusted steady flows were dam operations that might benefit humpback chub more than the Record of Decision operations, known as Modified Low Fluctuating Flow (MLFF) operations. Condensed timelines between planning and implementation (2 months) of the experiment and the time required for logistics, purchasing, and contracting resulted in limited data collection during the high-release part of the experiment that occurred in spring. The LSSF experiment is the longest planned hydrograph that departed from the MLFF operations since Record of Decision operations began in 1996. As part of the experiment, several studies focused on the responses of physical properties related to environments that young-of-year (YOY) native fish might occupy (for example, measuring mainstem and shoreline water temperature, and quantifying useable shorelines). The part of the hydrograph that included a habitat maintenance flow (a 4-day spike at a powerplant capacity of 877 m3/s) and sustained high releases in April and May (averaging 509 m3/s) resulted in sediment export to Lake Mead, the reservoir downstream from Glen Canyon Dam, which is outside the study area. Some mid-elevation sandbar building (between 566 and 877 m3/s stage elevations) occurred from existing sediment deposits rather than from sediment inputs from tributaries during the previous winter. Low releases in the summer combined with low tributary sediment inputs resulted in minor sediment accumulation in the study area. The September habitat maintenance flow reworked accumulated sediment and resulted in increases in the area of some backwaters. The mainstem water temperatures in the reach near the Little Colorado River during the LSSF experiment varied little from previous years. Mainstem water temperatures in western Grand Canyon average 17 to 20 degrees C. During the LSSF, backwaters warmed more than other shoreline environments during the day, but most backwaters returned to mainstem water temperatures overnight. Shoreline surface water temperatures from river mile (RM) 30 to 72 varied between 9 and 28 degrees C in the middle of the day in July. These temperatures are within the optimal temperature range for humpback chub growth and spawning, which is between 15 and 24 degrees C. How surface water temperatures transfer to subsurface water temperatures is unknown. Data collection associated with the response of fish to the 2000 LSSF hydrograph focused on fish growth and abundance along the Colorado River in Grand Canyon. The target resource, humpback chub and other native fishes, did not respond in a strongly positive or strongly negative manner to the LSSF hydrograph during the sampling period, which extended from June to September 2000. In 2000, the mean total length of YOY native fishes was similar to the mean

Arizona↗
USGS2011

Simulating daily water temperatures of the Klamath River under dam removal and climate change scenarios

A one-dimensional daily averaged water temperature model was used to simulate Klamath River temperatures for two management alternatives under historical climate conditions and six future climate scenarios. The analysis was conducted for the Secretarial Determination on removal of four hydroelectric dams on the Klamath River. In 2012, the Secretary of the Interior will determine if dam removal and implementation of the Klamath Basin Restoration Agreement (KBRA) (Klamath Basin Restoration Agreement, 2010) will advance restoration of salmonid fisheries and is in the public interest. If the Secretary decides dam removal is appropriate, then the four dams are scheduled for removal in 2020. Water temperature simulations were conducted to compare the effect of two management alternatives: the no-action alternative where dams remain in place, and the action alternative where dam removal occurs in 2020 along with habitat restoration. Each management alternative was simulated under historical climate conditions (1961-2010) and six 50-year (2012-2061) climate scenarios. The model selected for the study, River Basin Model-10 (RBM10), was used to simulate water temperatures over a 253-mile reach of the Klamath River located in south-central Oregon and northern California. RBM10 uses a simple equilibrium flow model, assuming discharge in each river segment on each day is transmitted downstream instantaneously. The model uses a heat budget formulation to quantify heat flux at the air-water interface. Inputs for the heat budget were calculated from daily-mean meteorological data, including net shortwave solar radiation, net longwave atmospheric radiation, air temperature, wind speed, vapor pressure, and a psychrometric constant needed to calculate the Bowen ratio. The modeling domain was divided into nine reaches ranging in length from 10.8 to 42.4 miles, which were calibrated and validated separately with measured water temperature data collected irregularly from 1961 to 2010. Calibration root mean square errors of observed versus simulated water temperatures for the nine reaches ranged from 0.8 to 1.5 degrees C. Mean absolute errors ranged from 0.6 to 1.2 degrees C. For model validation, a k-fold cross-validation technique was used. Validation root mean square error and mean absolute error for the nine reaches ranged from 0.8 to 1.4 degrees C and 0.8 to 1.2 degrees C, respectively. Input data for the six future climate scenarios (2012-2061) were derived from historical hydrological and meteorological data and simulated meteorological output from five Global Circulation Models. Total Maximum Daily Loads or other regulatory processes that might reduce future water temperatures were not included in the simulations. Under the current climate conditions scenario, impacts of dam removal on water temperatures were greatest near Iron Gate Dam (near Yreka, California) and were attenuated in the lower reaches of the Klamath River. May and October simulated mean water temperatures increased and decreased by approximately 1-2 degrees C and 2-4 degrees C, respectively, downstream of Iron Gate Dam after dam removal. Dam removal also resulted in an earlier annual temperature cycle shift of 18 days, 5 days, and 2 days, near Iron Gate Dam, Scott River, and Trinity River, respectively. Although the magnitude of precipitation and air temperature change predicted by the five Global Circulation Models varied, all five models resulted in progressive incremental increases in water temperatures with each decade from 2012 to 2061. However, dam removal under KBRA appeared to delay the effects of climate change to some extent near Iron Gate Dam. With dam removal under KBRA, annual-mean water temperatures exceeded the 49-year historical mean temperature beginning in 2045; whereas with dams, annual-mean temperatures exceeded the historical mean beginning in 2025. Potential changes in seasonal water temperatures resulting from dam removal, with or without future climat

Open-File Report↗
USGS2011

Denitrification rates in marsh soils and hydrologic and water quality data for Northeast Creek and Bass Harbor Marsh watersheds, Mount Desert Island, Maine

Nutrient enrichment from atmospheric deposition, agricultural activities, wildlife, and domestic sources is a concern at Acadia National Park because of the potential problem of water-quality degradation and eutrophication in estuaries. Water-quality degradation has been observed at the park's Bass Harbor Marsh estuary but minimal degradation is observed in Northeast Creek estuary. Previous studies at Acadia National Park have estimated nutrient inputs to estuaries from atmospheric deposition and surface-water runoff, and have identified shallow groundwater as an additional potential nutrient source. Previous studies at Acadia National Park have assumed that a certain fraction of the nitrogen input was removed through microbial denitrification, but rates of denitrification (natural or maximum potential) in marsh soils have not been determined. The U.S. Geological Survey, in cooperation with Acadia National Park, measured in situ denitrification rates in marsh soils in Northeast Creek and Bass Harbor Marsh watersheds during the summer seasons of 2008 and 2009. Denitrification was measured under ambient conditions and following inorganic nitrogen and glucose additions. Laboratory incubations of marsh soils with and without acetylene were conducted to determine average ratios of nitrous oxide (N 2 O) to nitrogen (N 2 ) produced during denitrification. Surface water and groundwater samples were analyzed for nutrients, specific conductance, temperature, and dissolved oxygen. Water level was recorded continuously during the growing season in Fresh Meadow Marsh in the Northeast Creek Watershed.

Maine↗
USGS2012

USGS Environmental health science strategy: providing environmental health science for a changing world: Public review release

America has an abundance of natural resources. We have bountiful clean water, fertile soil, and unrivaled national parks, wildlife refuges, and public lands. These resources enrich our lives and preserve our health and wellbeing. These resources have been maintained because of our history of respect for their value and an enduring commitment to their vigilant protection. Awareness of the social, economic, and personal value of the health of our environment is increasing. The emergence of environmentally driven diseases caused by environmental exposure to contaminants and pathogens is a growing concern worldwide. New health threats and patterns of established threats are affected by both natural and anthropogenic changes to the environment. Human activities are key drivers of emerging (new and re-emerging) health threats. Societal demands for land and natural resources, a better quality of life, improved economic prosperity, and the environmental impacts associated with these demands will continue to increase. Natural earth processes, climate trends, and related climatic events will add to the environmental impact of human activities. These environmental drivers will influence exposure to disease agents, including viral, bacterial, prion, and fungal pathogens, parasites, natural earth materials, toxins and other biogenic compounds, and synthetic chemicals and substances. The U.S. Geological Survey (USGS) defines environmental health science broadly as the interdisciplinary study of relations among the quality of the physical environment, the health of the living environment, and human health. The interactions among these three spheres are driven by human activities, ecological processes, and natural earth processes; the interactions affect exposure to contaminants and pathogens and the severity of environmentally driven diseases in animals and people. This definition provides USGS with a framework for synthesizing natural science information from across the Bureau and providing it to environmental, natural resource, agricultural, and public-health managers. The USGS is a Federal science agency with a broad range of natural science expertise relevant to environmental health. USGS provides scientific information and tools as a scientific basis for management and policy decision making. USGS specializes in science at the environment-health interface, by characterizing the processes that affect the interaction among the physical environment, the living environment, and people, and the resulting factors that affect ecological and human exposure to disease agents. This report describes a 10-year strategy that encompasses the portfolio of USGS environmental health science. It summarizes national environmental health priorities that USGS is best suited to address, and will serve as a strategic framework for USGS environmental health science goals, actions, and outcomes for the next decade. Implementation of this strategy is intended to aid coordination of USGS environmental health activities and to provide a focal point for disseminating information to stakeholders. The "One Health" paradigm advocated by the World Health Organization (WHO, 2011), and the American Veterinary Medicine Association (AVMA, 2008), among others, is based on a general recognition that the health of humans, animals, and the environment are inextricably linked. Thus, successful efforts to protect that health will require increased interdisciplinary research and increased communication and collaboration among the broader scientific and health community. This strategy is built upon that paradigm. The vision, mission, and five cornerstone goals of the USGS Environmental Health Science Strategy were developed with significant input from a wide range of stakeholders. Vision - The USGS is a premier source of the environmental health science needed to safeguard the health of the environment, fish, wildlife, and people. Mission - The mission of USGS in environmental health science is to contribute scientific information to environmental, natural resource, agricultural, and public-health managers, who use that science to support sound decision making. USGS provides the science to: - Goal 1: Identify, prioritize, and detect contaminants and pathogens of emerging environmental concern. - Goal 2: Reduce the impact of contaminants on the environment, fish, wildlife, and people. - Goal 3: Reduce the impact of pathogens on the environment, fish, wildlife, and people. - Goal 4: Discover the complex interactions and combined effects of exposure to contaminants and pathogens. - Goal 5: Prepare for and respond to environmental impacts and related health threats of natural and anthropogenic disasters. Goals 1 through 4 are intended to provide science to address environmental health threats in a logical order, from informing prevention and preparedness, to supporting systematic management response to environmental health issues. Goal 4 addresses the interaction among contaminants and pathogens, an issue of emerging concern in environmental health science. Goal 5 acknowledges the fact that natural and anthropogenic disasters can cause immediate and prolonged adverse environmental health threats. This strategy proposes that USGS take the following strategic science actions to achieve each of the five goals of this strategy: Goal 1: Identify, prioritize, and detect contaminants and pathogens of emerging environmental concern. - Strategic Science Action 1. - Prioritize contaminants and pathogens of emerging concern to guide research, detection, and management activities. - Strategic Science Action 2. - Conduct surveillance and monitoring to provide early warning of emerging health threats. - Strategic Science Action 3. - Develop approaches and tools that identify vulnerable environmental settings, ecosystems, and species. Goal 2: Reduce the impact of contaminants on the environment, fish, wildlife, and people. - Strategic Science Action 1. - Systematically characterize the sources, occurrence, transport and fate of environmental contaminants to guide efforts to manage and mitigate contamination. - Strategic Science Action 2. - Evaluate the threats of contamination on the health of the environment, fish, wildlife, and people, and inform the associated management and protection efforts. - Strategic Science Action 3. - Characterize potential human exposure to support establishment of health-based standards or guidelines and contamination-reduction efforts. Goal 3: Reduce the impact of pathogens on the environment, fish, wildlife, and people. - Strategic Science Action 1. - Determine the biotic and abiotic factors that control the ecology of infectious diseases affecting natural populations of aquatic and terrestrial species and potential transmission to other animals and humans. - Strategic Science Action 2. - Establish how natural and anthropogenic environmental changes affect the distribution and severity of infectious diseases in natural populations of aquatic and terrestrial species and potential transmission to other animals and humans. - Strategic Science Action 3. - Develop surveillance systems to identify changing patterns of disease activity in priority geographic areas. Goal 4: Discover the complex interactions and combined effects of exposure to contaminants and pathogens. - Strategic Science Action 1. - Identify how exposure to one class of disease agents (contaminants or pathogens) can make an organism more susceptible to effects from exposure to the other class of disease agents. - Strategic Science Action 2. - Implement interdisciplinary studies that characterize the effects of combined exposure to pathogens and contaminants. Goal 5: Prepare for and respond to the environmental impacts and related health threats of natural and anthropogenic disasters. - Strategic Science Action 1. - Establish a formal interdisciplinary science capability to rapidly assess the environmental health risks associated with disasters. - Strategic Science Action 2. - Enhance methods to anticipate, prepare for, and identify environmental, ecological, and related health impacts of future disasters. This strategy is one of seven USGS science strategies developed concurrently: - Climate and Land Use Change - Core Science Systems - Ecosystems - Energy and Mineral Resources - Environmental Health - Natural Hazards - Water. This strategy describes how USGS will address the highest priority environmental health issues facing the Nation. The ultimate intended outcome of this science strategy is prevention and reduction of adverse impacts to the quality of the environment, the health of our living resources, and human health. Communication with, and receiving input from, partners and stakeholders regarding their science needs is essential for successful implementation of this strategy. It is incumbent on USGS to reach out to all stakeholders to ensure that USGS efforts are focused on the highest priority environmental health issues and that products are provided in the most timely and usable form to all those who can use them. USGS must reach out to the scientific community, internally and externally, to ensure that our efforts are integrated with and take full advantage of the activities of others.

Open-File Report↗
USGS2012

Potential climate-induced runoff changes and associated uncertainty in four Pacific Northwest estuaries

As part of a larger investigation into potential effects of climate change on estuarine habitats in the Pacific Northwest, we estimated changes in freshwater inputs into four estuaries: Coquille River estuary, South Slough of Coos Bay, and Yaquina Bay in Oregon, and Willapa Bay in Washington. We used the U.S. Geological Survey's Precipitation Runoff Modeling System (PRMS) to model watershed hydrological processes under current and future climatic conditions. This model allowed us to explore possible shifts in coastal hydrologic regimes at a range of spatial scales. All modeled watersheds are located in rainfall-dominated coastal areas with relatively insignificant base flow inputs, and their areas vary from 74.3 to 2,747.6 square kilometers. The watersheds also vary in mean elevation, ranging from 147 meters in the Willapa to 1,179 meters in the Coquille. The latitudes of watershed centroids range from 43.037 degrees north latitude in the Coquille River estuary to 46.629 degrees north latitude in Willapa Bay. We calibrated model parameters using historical climate grid data downscaled to one-sixteenth of a degree by the Climate Impacts Group, and historical runoff from sub-watersheds or neighboring watersheds. Nash Sutcliffe efficiency values for daily flows in calibration sub-watersheds ranged from 0.71 to 0.89. After calibration, we forced the PRMS models with four North American Regional Climate Change Assessment Program climate models: Canadian Regional Climate Model-(National Center for Atmospheric Research) Community Climate System Model version 3, Canadian Regional Climate Model-Canadian Global Climate Model version 3, Hadley Regional Model version 3-Hadley Centre Climate Model version 3, and Regional Climate Model-Canadian Global Climate Model version 3. These are global climate models (GCMs) downscaled with regional climate models that are embedded within the GCMs, and all use the A2 carbon emission scenario developed by the Intergovernmental Panel on Climate Change. With these climate-forcing outputs, we derived the mean change in flow from the period encompassing the 1980s (1971-1995) to the period encompassing the 2050s (2041-2065). Specifically, we calculated percent change in mean monthly flow rate, coefficient of variation, top 5 percent of flow, and 7-day low flow. The trends with the most agreement among climate models and among watersheds were increases in autumn mean monthly flows, especially in October and November, decreases in summer monthly mean flow, and increases in the top 5 percent of flow. We also estimated variance in PRMS outputs owing to parameter uncertainty and the selection of climate model using Latin hypercube sampling. This analysis showed that PRMS low-flow simulations are more uncertain than medium or high flow simulations, and that variation among climate models was a larger source of uncertainty than the hydrological model parameters. These results improve our understanding of how climate change may affect the saltwater-freshwater balance in Pacific Northwest estuaries, with implications for their sensitive ecosystems.

Oregon;Washington↗
USGS2013

Development of a database-driven system for simulating water temperature in the lower Yakima River main stem, Washington, for various climate scenarios

A model for simulating daily maximum and mean water temperatures was developed by linking two existing models: one developed by the U.S. Geological Survey and one developed by the Bureau of Reclamation. The study area included the lower Yakima River main stem between the Roza Dam and West Richland, Washington. To automate execution of the labor-intensive models, a database-driven model automation program was developed to decrease operation costs, to reduce user error, and to provide the capability to perform simulations quickly for multiple management and climate change scenarios. Microsoft© SQL Server 2008 R2 Integration Services packages were developed to (1) integrate climate, flow, and stream geometry data from diverse sources (such as weather stations, a hydrologic model, and field measurements) into a single relational database; (2) programmatically generate heavily formatted model input files; (3) iteratively run water temperature simulations; (4) process simulation results for export to other models; and (5) create a database-driven infrastructure that facilitated experimentation with a variety of scenarios, node permutations, weather data, and hydrologic conditions while minimizing costs of running the model with various model configurations. As a proof-of-concept exercise, water temperatures were simulated for a "Current Conditions" scenario, where local weather data from 1980 through 2005 were used as input, and for "Plus 1" and "Plus 2" climate warming scenarios, where the average annual air temperatures used in the Current Conditions scenario were increased by 1degree Celsius (°C) and by 2°C, respectively. Average monthly mean daily water temperatures simulated for the Current Conditions scenario were compared to measured values at the Bureau of Reclamation Hydromet gage at Kiona, Washington, for 2002-05. Differences ranged between 1.9° and 1.1°C for February, March, May, and June, and were less than 0.8°C for the remaining months of the year. The difference between current conditions and measured monthly values for the two warmest months (July and August) were 0.5°C and 0.2°C, respectively. The model predicted that water temperature generally becomes less sensitive to air temperature increases as the distance from the mouth of the river decreases. As a consequence, the difference between climate warming scenarios also decreased. The pattern of decreasing sensitivity is most pronounced from August to October. Interactive graphing tools were developed to explore the relative sensitivity of average monthly and mean daily water temperature to increases in air temperature for model output locations along the lower Yakima River main stem.

Washington↗
USGS2013

Estimation of missing water-level data for the Everglades Depth Estimation Network (EDEN), 2013 update

The Everglades Depth Estimation Network is an integrated network of real-time water-level gaging stations, a ground-elevation model, and a water-surface elevation model designed to provide scientists, engineers, and water-resource managers with water-level and water-depth information (1991-2013) for the entire freshwater portion of the Greater Everglades. The U.S. Geological Survey Greater Everglades Priority Ecosystems Science provides support for the Everglades Depth Estimation Network in order for the Network to provide quality-assured monitoring data for the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. In a previous study, water-level estimation equations were developed to fill in missing data to increase the accuracy of the daily water-surface elevation model. During this study, those equations were updated because of the addition and removal of water-level gaging stations, the consistent use of water-level data relative to the North American Vertical Datum of 1988, and availability of recent data (March 1, 2006, to September 30, 2011). Up to three linear regression equations were developed for each station by using three different input stations to minimize the occurrences of missing data for an input station. Of the 667 water-level estimation equations developed to fill missing data at 223 stations, more than 72 percent of the equations have coefficients of determination greater than 0.90, and 97 percent have coefficients of determination greater than 0.70.

Florida↗
USGS2014

Documentation for the 2014 update of the United States national seismic hazard maps

The national seismic hazard maps for the conterminous United States have been updated to account for new methods, models, and data that have been obtained since the 2008 maps were released (Petersen and others, 2008). The input models are improved from those implemented in 2008 by using new ground motion models that have incorporated about twice as many earthquake strong ground shaking data and by incorporating many additional scientific studies that indicate broader ranges of earthquake source and ground motion models. These time-independent maps are shown for 2-percent and 10-percent probability of exceedance in 50 years for peak horizontal ground acceleration as well as 5-hertz and 1-hertz spectral accelerations with 5-percent damping on a uniform firm rock site condition (760 meters per second shear wave velocity in the upper 30 m, V S30 ). In this report, the 2014 updated maps are compared with the 2008 version of the maps and indicate changes of plus or minus 20 percent over wide areas, with larger changes locally, caused by the modifications to the seismic source and ground motion inputs.

Open-File Report↗
USGS2014

Surface wave site characterization at 27 locations near Boston, Massachusetts, including 2 strong-motion stations

The geotechnical properties of the soils in and around Boston, Massachusetts, have been extensively studied. This is partly due to the importance of the Boston Blue Clay and the extent of landfill in the Boston area. Although New England is not a region that is typically associated with seismic hazards, there have been several historical earthquakes that have caused significant ground shaking (for example, see Street and Lacroix, 1979; Ebel, 1996; Ebel, 2006). The possibility of strong ground shaking, along with heightened vulnerability from unreinforced masonry buildings, motivates further investigation of seismic hazards throughout New England. Important studies that are pertinent to seismic hazards in New England include source-parameter studies (Somerville and others, 1987; Boore and others, 2010), wave-propagation studies (Frankel, 1991; Viegas and others, 2010), empirical ground-motion prediction equations (GMPE) for computing ground-motion intensity (Tavakoli and Pezeshk, 2005; Atkinson and Boore, 2006), site-response studies (Hayles and others, 2001; Ebel and Kim, 2006), and liquefaction studies (Brankman and Baise, 2008). The shear-wave velocity (VS) profiles collected for this report are pertinent to the GMPE, site response, and liquefaction aspects of seismic hazards in the greater Boston area. Besides the application of these data for the Boston region, the data may be applicable throughout New England, through correlations with geologic units (similar to Ebel and Kim, 2006) or correlations with topographic slope (Wald and Allen, 2007), because few VS measurements are available in stable tectonic regions. Ebel and Hart (2001) used felt earthquake reports to infer amplification patterns throughout the greater Boston region and noted spatial correspondence with the dominant period and amplification factors obtained from ambient noise (horizontal-to-vertical ratios) by Kummer (1998). Britton (2003) compiled geotechnical borings in the area and produced a microzonation map based on generalized velocity profiles, where the amplifications were computed using Shake (Schnable and others, 1972), along with an assumed input ground motion. The velocities were constrained by only a few local measurements associated with the Central Artery/Tunnel project. The additional VS measurements presented in this report provide a number of benefits. First, these measurements provide improved spatial coverage. Second, the larger sample size provides better constraints on the mean and variance of the VS distribution for each layer, which may be paired with a three-dimensional (3D) model of the stratigraphy to generate one-dimensional (1D) profiles for use in a standard site-response analysis (for example, Britton, 2003). Third, the velocity profiles may also be used, along with a 3D model of the stratigraphy, as input into a 3D simulation of the ground motion to investigate the effects of basin-generated surface waves and the potential focusing of seismic waves. This report begins with a short review of the geology of the study area and the field methods that we used to estimate the velocity profiles. The raw data, processed data, and the interpreted VS profiles are given in appendix 1. Photographs and descriptions of the sites are provided in appendix 2.

Massachusetts↗
USGS2014

Evaluating coastal landscape response to sea-level rise in the northeastern United States: approach and methods

The U.S. Geological Survey is examining effects of future sea-level rise on the coastal landscape from Maine to Virginia by producing spatially explicit, probabilistic predictions using sea-level projections, vertical land movement rates (due to isostacy), elevation data, and land-cover data. Sea-level-rise scenarios used as model inputs are generated by using multiple sources of information, including Coupled Model Intercomparison Project Phase 5 models following representative concentration pathways 4.5 and 8.5 in the Intergovernmental Panel on Climate Change Fifth Assessment Report. A Bayesian network is used to develop a predictive coastal response model that integrates the sea-level, elevation, and land-cover data with assigned probabilities that account for interactions with coastal geomorphology as well as the corresponding ecological and societal systems it supports. The effects of sea-level rise are presented as (1) level of landscape submergence and (2) coastal response type characterized as either static (that is, inundation) or dynamic (that is, landform or landscape change). Results are produced at a spatial scale of 30 meters for four decades (the 2020s, 2030s, 2050s, and 2080s). The probabilistic predictions can be applied to landscape management decisions based on sea-level-rise effects as well as on assessments of the prediction uncertainty and need for improved data or fundamental understanding. This report describes the methods used to produce predictions, including information on input datasets; the modeling approach; model outputs; data-quality-control procedures; and information on how to access the data and metadata online.

Open-File Report↗
USGS2015

Simulated runoff at many stream locations in the Methow River Basin, Washington

A collaborative Bureau of Reclamation-U.S. Geological Survey (USGS) team has been brought together to incorporate a conceptual geomorphic-habitat model with a process-based trophic model to understand the processes important to stream habitat for anadromous fish populations. The Methow River Basin was selected as a test basin for this hybrid geomorphic-habitat/trophic model, and one of the required model inputs is long-term daily runoff at reaches with potential habitat. Leveraging the existence of a watershed model that was constructed for the Methow River Basin by the USGS, the team approached the USGS at the Washington Water Science Center to resurrect the original model and to simulate runoff at many locations in the basin to test the trophic model. Thirteen new flow-routing sites were added to the model, creating a total of 61 sites in the basin where daily runoff was simulated and provided as output. The input file that contains observed meteorological data that drives the watershed model and observed runoff data for comparisons with simulated runoff was extended from water year 2001 to water year 2013 using data from 18 meteorological sites and 12 observed runoff sites. The watershed model included simulation of 16 irrigation diversions that simulated 50-percent water loss through canal seepage. Irrigation was simulated as a constant application of 0.2 inches per day to during the irrigation season, May 1–October 7. Comparisons of the simulated runoff with observed runoff at six selected long-term streamflow-gaging stations showed that the simulated annual runoff was within +15.4 to -9.6 percent of the annual observed runoff. The simulated runoff generally matched the seasonal flow patterns, with bias at some stations indicated by over-simulation of the October–November late autumn season and under-simulation of the snowmelt runoff months of May and June. Sixty-one time series of daily runoff for a 26-year period representative of the long-term runoff pattern, water years 1988–2013, were simulated and provided to the trophic modeling team.

Washington↗
USGS2015

Obtaining valid geologic models from 3-D resistivity inversion of magnetotelluric data at Pahute Mesa, Nevada

We summarize the results of a three-dimensional (3-D) resistivity inversion simulation that we conducted with the intent of characterizing the subsurface 3-D distribution of volcanic composite units of Pahute Mesa, Nevada, without any a priori information on the actual 3-D distribution of the known subsurface geology. The 3-D methodology involved using a 3-D geologic model based on drillhole data and average electrical resistivities of the key hydrostratigraphic units at Pahute Mesa to create a 3-D resistivity forward (“known”) model that depicted the subsurface resistivity structure expected for the input geologic configuration. The calculated magnetotelluric response of the modeled resistivity structure was then assumed to represent observed magnetotelluric data and was used as input into a 3-D resistivity inverse model that was allowed to iteratively estimate in 3-D without any a priori geologic information, in particular, the thickness and resistivity of the volcanic composite units. The resulting 3-D resistivity inversion simulation was compared to the “known” model and the results evaluated. The 3-D inversion was generally able to reproduce the gross resistivity structure of the “known” model, but the simulated conductive volcanic composite unit horizons were often too shallow when compared to the “known” model. Additionally, the chosen computation parameters such as station spacing appear to have resulted in computational artifacts that are difficult to interpret but could potentially be removed with further refinements of the 3-D resistivity inversion modeling technique.

Nevada↗
USGS2015

Southern Salish Sea Habitat Map Series: Admiralty Inlet

In 2010 the Environmental Protection Agency, Region 10 initiated the Puget Sound Scientific Studies and Technical Investigations Assistance Program, designed to support research in support of implementing the Puget Sound Action Agenda. The Action Agenda was created in response to Puget Sound having been designated as one of 28 estuaries of national significance under section 320 of the U.S. Clean Water Act, and its overall goal is to restore the Puget Sound Estuary's environment by 2020. The Southern Salish Sea Mapping Project was funded by the Assistance Program request for proposals process, which also supports a large number of coastal-zone- and ocean-management issues. The issues include the recommendations of the Marine Protected Areas Work Group to the Washington State Legislature (Van Cleve and others, 2009), which endorses a Puget Sound and coast-wide marine conservation needs assessment, gap analysis of existing Marine Protected Areas (MPA) and recommendations for action. This publication is the first of four U.S. Geological Survey Scientific Investigation Maps that make up the Southern Salish Sea Mapping Project. The remaining three map blocks to be published in the future, located south of Admiralty Inlet, are shown in figure 1. Puget Sound is a deep, fjord-type estuary covering an area of 2,330 km 2 in the Pacific Northwest region of the United States (fig. 1). It is connected to the ocean by the Strait of Juan de Fuca, a turbulent passage approximately 160 km in length and 22 km wide at its west end, expanding to over 40 km wide at its east end (Thomson, 1994). During the Pleistocene, the area was occupied several times by lobes of continental ice, resulting in a complex basin-fill of glacial and interglacial deposits that are locally as thick as 1100 m (Johnson and others, 2001). The last glaciation, called the Fraser glaciation, began after 28,800±740 14 C yr B.P. when ice started a slow expansion (Clague, 1981). At peak advance the westward Juan de Fuca lobe reached the edge of the continental shelf through the Juan de Fuca Strait shortly before 14,460±200 14 C yr B.P. (Herzer and Bornhold, 1982). The southward Puget lobe advanced to its terminal position in Puget Sound by around 14,150 14 C yr B.P. (Porter and Swanson, 1998). Ice retreated from its maximum to northern Whidbey Island by 13,650±350 14 C yr B.P. (Dethier and others, 1995). Retreating glaciers resulted in a thick sequence of ice-contact, glacial-marine sediment, and early post-glacial sediments (Linden and Schurrer, 1988). These deposits have experienced the effects of a marine transgression followed by regression, resulting in a sea-level several tens of meters lower than the present day (Linden and Schurrer, 1988). A second transgression brought sea level to about the present level by around 5,470±120 14 C yr B.P. (Clague and others, 1982) establishing the present oceanographic and geologic environment Puget Sound is separated into four interconnected basins; Whidbey, Central (Main), Hood Canal, and South (Thomson, 1994). The Whidbey, Central, and Hood Canal basins are the three main branches of the Puget Sound estuary and are separated from the Strait of Juan de Fuca by a double sill at Admiralty Inlet. The Admiralty Inlet map area includes the Inlet and a portion of the Whidbey Basin (fig. 1). The shallower South Basin is separated by a sill at Tacoma Narrows and is highly branched with numerous finger inlets. Flow within Puget Sound is dominated by tidal currents of as much as 1 m/s at Admiralty Inlet, reducing to approximately 0.5 m/s in the Central Basin (Lavelle and others, 1988). The lack of silt and clay-sized sediments in the Admiralty Inlet map area is likely a result of the strong currents (see Ground-Truth Studies for the Admiralty Inlet Map Area, sheet 3). The subtidal component of flow reaches approximately 0.1 m/s and is driven by density gradients arising from the contrast in salty ocean water at the entrance and freshwater inputs from stream flow (Lavelle and others, 1988). The total freshwater input to Puget Sound is approximately 3.4 x 10 6 m 3 /day, primarily from the Skagit River (Cannon, 1983). The subtidal circulation mostly consists of a two-layered flow in the basins with fresher water exiting at the surface and saltier water entering at depth (Ebbesmeyer and Cannon, 2001). In general, surface waters flow north and deeper waters flow south; variations arise from wind effects that can drive a surface current in the same direction as the wind, and a baroclinic response in the lower layer to about 100-m depth (Matsuura and Cannon, 1997). Oceanographic properties are influenced by temporal forcing parameters such as reduced stream flow during the 2000-01 drought that increased surface salinity and decreased differences between surface and bottom waters (Newton and others, 2003). On offshore seismic-reflection profiles, Pleistocene strata (excluding latest Pleistocene glacial and post-glacial deposits) form a distinct seismic unit, bounded below by pre-Tertiary or Tertiary basement and above by typically flat-lying latest Pleistocene to Holocene deposits that fill in erosional or depositional relief (Johnson and others, 2001). Cores from central Puget Sound have accumulation rates that range from 85 to 1200 mg/cm 2 /yr, or 0.12 to 2.4 cm/yr; the highest accumulation rates are near the southern end of central Puget Sound (Carpenter and others, 1985). Carpenter and others (1985) un-weighted arithmetic mean of accumulation rates for central Puget Sound deeper stations is 480±340 (± one standard deviation) mg/cm 2 /yr. Lavelle and others (1985) also found rates as high as 1200 mg/cm 2 /yr over the past approximately 70 years in cores in the Central Basin off of and north and south of Elliott Bay. Puget Sound basin rates are comparable to rates in midshelf silt deposits on the Washington coast north of the Columbia River (Nittrouer and others, 1979). The deep subtidal (in other words, below SCUBA depths) habitats of Puget Sound are relatively poorly known. A few subtidal surveys exist for several habitat types from the 1960s and 1970s (reviewed in Dethier, 1990), using grab and box core data. The Dethier (1990) review divides habitat up into Coast and Marine Ecological Classification Standard (CMECS) substrate, water column energy, and depth zones but does not attempt to map these habitats, rather it is an inventory of habitats found in the area and the flora and fauna associated with each habitat. The approach of the Southern Salish Sea Mapping project is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, and bottom-sediment sampling data. This approach is based in part on methods presented and data collection and product needs identified at the Washington State Seafloor Mapping Workshop (Washington State Seafloor Mapping Workshop Steering Committee, 2008), attended by coastal and marine managers and scientists. The map products display seafloor geomorphology and substrate, and identify potential marine benthic habitats. It is emphasized that the more interpretive habitat and geology maps rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. Oceanographic current and wave data is not included in this analysis, however, the accompanying geographic information system (GIS) data set is designed and intended to be combined with oceanographic and biologic data sets assembled by others in the future and some of the GIS data has already been incorporated in the unpublished Nature Conservancy Benthic Habitats of Puget Sound database. This publication includes four map sheets, explanatory text, and a descriptive pamphlet. Each map sheet is published as a portable document format (PDF) file. ESRI ArcGIS compatible geotiffs (for example, bathymetry) and shapefiles (for example video observation points) will be available for download in the data catalog associated with this publication (Cochrane, 2015). An ArcGIS Project File with the symbology used to generate the map sheets is also provided. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html .

Washington↗