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At least 1,099 records · Page 61Linked to original sources
USGS2008

Data to support statistical modeling of instream nutrient load based on watershed attributes, southeastern United States, 2002

This report presents and describes the digital datasets that characterize nutrient source inputs, environmental characteristics, and instream nutrient loads for the purpose of calibrating and applying a nutrient water-quality model for the southeastern United States for 2002. The model area includes all of the river basins draining to the south Atlantic and the eastern Gulf of Mexico, as well as the Tennessee River basin (referred to collectively as the SAGT area). The water-quality model SPARROW (SPAtially-Referenced Regression On Watershed attributes), developed by the U.S. Geological Survey, uses a regression equation to describe the relation between watershed attributes (predictors) and measured instream loads (response). Watershed attributes that are considered to describe nutrient input conditions and are tested in the SPARROW model for the SAGT area as source variables include atmospheric deposition, fertilizer application to farmland, manure from livestock production, permitted wastewater discharge, and land cover. Watershed and channel attributes that are considered to affect rates of nutrient transport from land to water and are tested in the SAGT SPARROW model as nutrient-transport variables include characteristics of soil, landform, climate, reach time of travel, and reservoir hydraulic loading. Datasets with estimates of each of these attributes for each individual reach or catchment in the reach-catchment network are presented in this report, along with descriptions of methods used to produce them. Measurements of nutrient water quality at stream monitoring sites from a combination of monitoring programs were used to develop observations of the response variable - mean annual nitrogen or phosphorus load - in the SPARROW regression equation. Instream load of nitrogen and phosphorus was estimated using bias-corrected log-linear regression models using the program Fluxmaster, which provides temporally detrended estimates of long-term mean load well-suited for spatial comparisons. The detrended, or normalized, estimates of load are useful for regional-scale assessments but should be used with caution for local-scale interpretations, for which use of loads estimated for actual time periods and employing more detailed regression analysis is suggested. The mean value of the nitrogen yield estimates, normalized to 2002, for 637 stations in the SAGT area is 4.7 kilograms per hectare; the mean value of nitrogen flow-weighted mean concentration is 1.2 milligrams per liter. The mean value of the phosphorus yield estimates, normalized to 2002, for the 747 stations in the SAGT area is 0.66 kilogram per hectare; the mean value of phosphorus flow-weighted mean concentration is 0.17 milligram per liter. Nutrient conditions measured in streams affected by substantial influx or outflux of water and nutrient mass across surface-water basin divides do not reflect nutrient source and transport conditions in the topographic watershed; therefore, inclusion of such streams in the SPARROW modeling approach is considered inappropriate. River basins identified with this concern include south Florida (where surface-water flow paths have been extensively altered) and the Oklawaha, Crystal, Lower Sante Fe, Lower Suwanee, St. Marks, and Chipola River basins in central and northern Florida (where flow exchange with the underlying regional aquifer may represent substantial nitrogen influx to and outflux from the surface-water basins).

Open-File Report↗
USGS2009

Computer programs for obtaining and analyzing daily mean streamflow data from the U.S. Geological Survey National Water Information System web site

Five computer programs were developed for obtaining and analyzing streamflow from the National Water Information System (NWISWeb). The programs were developed as part of a study by the U.S. Geological Survey, in cooperation with the Federal Highway Administration, to develop a stochastic empirical loading and dilution model. The programs were developed because reliable, efficient, and repeatable methods are needed to access and process streamflow information and data. The first program is designed to facilitate the downloading and reformatting of NWISWeb streamflow data. The second program is designed to facilitate graphical analysis of streamflow data. The third program is designed to facilitate streamflow-record extension and augmentation to help develop long-term statistical estimates for sites with limited data. The fourth program is designed to facilitate statistical analysis of streamflow data. The fifth program is a preprocessor to create batch input files for the U.S. Environmental Protection Agency DFLOW3 program for calculating low-flow statistics. These computer programs were developed to facilitate the analysis of daily mean streamflow data for planning-level water-quality analyses but also are useful for many other applications pertaining to streamflow data and statistics. These programs and the associated documentation are included on the CD-ROM accompanying this report. This report and the appendixes on the CD-ROM describe the implementation and use of the programs and the interpretation of results from the programs. The body of this report provides an overview of the five programs included on this CD-ROM. The appendixes are the software manuals for each program. These manuals describe statistical and numerical methods used to implement each program, input-file formats, output-file formats, installation of the programs, and use of the programs. Each appendix is written as a self-contained manual because each program may have many uses alone or in tandem with other programs on the CD-ROM. Each of these programs uses graphical user interface that follows standard Microsoft Windows interface conventions.

Open-File Report↗
USGS2009

Coastal Processes Study of Santa Barbara and Ventura Counties, California

The Santa Barbara littoral cell (SBLC) is a complex coastal system with significant management challenges. The coastline ranges broadly in exposure to wave energy, fluvial inputs, hard structures, and urbanization. Geologic influence (structural control) on coastline orientation exerts an important control on local beach behavior, with anthropogenic alterations and the episodic nature of sediment supply and transport also playing important roles. Short- and long-term temporal analyses of shoreline change, beach width, and volume change show no obvious trends in regional beach behavior. Extensive armoring along the SBLC has accreted the back beach, narrowing beach widths and in some cases increasing sediment transport. Unarmored beaches have exhibited mild erosion while maintaining similar widths. Harbor constructions have had notable impacts on downdrift beaches, but once the coastal system has equilibrated the signal becomes strongly dampened and littoral-drift gradients driven by natural shoreline orientation again become dominant. Sediment inputs from the Santa Clara River dominate sediment processes on beaches to the south. The SBLC is dominated by episodic flood and storm-wave events. Exceptionally large accretion signals along this stretch of coastline are closely tied to major flood events when large amounts of sediment are deposited in deltas. These deltas decay over time, supplying downdrift beaches with sediment. Storm-wave impacts and gradients in alongshore transport can lead to beach rotations and migrating erosion hotspots when geological controls are weak. Annual and seasonal rates of cross-shore and alongshore transport are at least 2-3 times higher for the more west- and southwest-facing beaches south of the Ventura River as compared to the more sheltered beaches to the west/north. Gross littoral transports are good approximations of net littoral transports for beaches west/north of Ventura as transport is almost purely unidirectional. However, significant transport reversals occur intermittently in the east/south, especially adjacent to the Ventura and Channel Islands Harbors. For this reason, and due to the episodic nature of flood and storm wave events, using dredging rates from the harbors at Ventura and Channel Islands as a proxy for drift rates may be invalid. An extensive grain-size investigation of the surface and shallow subsurface in the nearshore region of the SBLC identified only two sites for potential beach-nourishment material: offshore of Santa Barbara Harbor and Oil Piers. However, seismic-reflection lines offshore of Santa Barbara suggest shallow bedrock (< 1 m), so the volume of coarse material in this area may be limited. Sampling of the Santa Clara River delta was minimal, but this site could be promising. Numerical modeling shows that local beach behavior is primarily influenced by local littoral-drift gradients, which are in turn controlled by natural shoreline orientation. Given the high rates of net littoral drift and the relatively insignificant cross-shore transport in the SBLC, the SBLC should be considered a sediment-limited system (as opposed to a transport-limited system). Management actions, such as any future beach nourishment, would likely have a severely limited life span without employing additional measures that adequately address local littoral-drift gradients to retain added sand.

Open-File Report↗
USGS2009

Estimation of Missing Water-Level Data for the Everglades Depth Estimation Network (EDEN)

The Everglades Depth Estimation Network (EDEN) is an integrated network of real-time water-level gaging stations, ground-elevation models, and water-surface elevation models designed to provide scientists, engineers, and water-resource managers with current (2000-2009) water-depth information for the entire freshwater portion of the greater Everglades. The U.S. Geological Survey Greater Everglades Priority Ecosystems Science provides support for EDEN and their goal of providing quality-assured monitoring data for the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. To increase the accuracy of the daily water-surface elevation model, water-level estimation equations were developed to fill missing data. To minimize the occurrences of no estimation of data due to missing data for an input station, a minimum of three linear regression equations were developed for each station using different input stations. Of the 726 water-level estimation equations developed to fill missing data at 239 stations, more than 60 percent of the equations have coefficients of determination greater than 0.90, and 92 percent have an coefficient of determination greater than 0.70.

Open-File Report↗
USGS2009

Benthic flux of nutrients and trace metals in the northern component of San Francisco Bay, California

Two sets of sampling trips were coordinated in late summer 2008 (weeks of July 8 and August 6) to sample the interstitial and overlying bottom waters at 10 shallow locations (9 sites <3 meters in depth) within the northern component of the San Francisco Bay/Delta (herein referred to as North Bay). The work was performed to better understand sources of biologically reactive solutes (namely, dissolved macronutrients and trace metals) that may affect the base of the food web in this part of the estuary. A nonmetallic pore-water profiler was used to obtain the first centimeter-scale estimates of the vertical solute-concentration gradients for diffusive-flux determinations. This study, performed in collaboration with scientists from San Francisco State University?s Romberg Tiburon Center for Environmental Studies, provides information to assist in developing and refining management strategies for the Bay/Delta system and supports efforts to monitor changes in food-web structure associated with regional habitat modifications directed by the California Bay-Delta Authority. On July 7, 2008, and August 5, 2008, pore-water profilers were successfully deployed at six North Bay sites per trip to measure the concentration gradient of dissolved macronutrients and trace metals near the sediment-water interface. Only two of the sites (433 and SSB009 within Honker Bay) were sampled in both series of profiler deployments. At each sampling site, profilers were deployed in triplicate, while discrete samples and dataloggers were used to collect ancillary data from both the water column and benthos to help interpret diffusive-flux measurements. Benthic flux of dissolved (0.2-micron filtered) inorganic phosphate (that is, soluble reactive phosphorus (SRP)) ranged from negligible levels (-0.003?0.005 millimole per square meter per day (mmole m-2d-1) at Site 4.1 outside Honker Bay) to 0.060?0.006 mmole m-2d-1 near the northern coast of Brown?s Island. Except for the elevated flux at Browns Island, the benthic flux of soluble reactive phosphorus (SRP) was consistently: (1) lower than previously reported for South Bay sites, (2) an order of magnitude lower than oligotrophic Coeur d?Alene Lake, (3) two orders of magnitude lower than determined for eutrophic Upper Klamath Lake, and (4) an order of magnitude or more lower than the estimated summer riverine inputs for SRP (900 to 1,300 kilograms of phosphorous per day (kg-P d-1)). In contrast to fluxes reported for the South Bay, nitrate fluxes were consistently negative (that is, drawn from the water column into the sediment), except for one site with statistically insignificant nitrate fluxes (Site 409 within Suisun Bay). The most negative nitrate flux (-7.3?0.1 mmole m-2d-1) was observed within Grizzly Bay (Site 416). Observed nitrate fluxes bracketed the estimated summer fluvial flux of nitrate (3,500 to 5,000 kg-N d-1). With the exception of the two Grizzly Bay sites (416 and 417), the consistently positive benthic flux of ammonia generally counteracted the negative flux of nitrate to yield a net balance of dissolved inorganic nitrogen. Ammonia benthic fluxes extrapolated for Suisun Bay ranged from 320 kg-N d-1 (Site SSB009 near the entrance to Honker Bay) to 1,900 kg-N d-1 (Montezuma Island). These values represent a significant ammonia source to the water column relative to summer riverine inputs (approximately 400 to 600 kg-N d-1). Dissolved silica also displayed a consistently positive benthic flux, except for Site 409 within Suisun Bay, which showed insignificant fluxes (also insignificant for nitrate and SRP). As with the nitrate fluxes, Grizzly Bay and Browns Island sites yielded the highest dissolved silica fluxes (1.3?1.2 to 2.5?0.6 mmole m-2d-1, respectively). These initial diffusive-flux estimates are greater than those measured in the South Bay using core-incubation experiments, which include bioturbation and bioirrigation effects, but they are nevertheless probably one to t

Open-File Report↗
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↗