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At least 109 records · Page 6Linked to original sources
USGS2015

Ground-based lidar beach topography of Fire Island, New York, April 2013

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center in Florida and the U.S. Army Corps of Engineers Field Research Facility in Duck, North Carolina, collaborated to gather alongshore ground-based lidar beach elevation data at Fire Island, New York. This high-resolution elevation dataset was collected on April 10, 2013, to characterize beach topography following substantial erosion that occurred during Hurricane Sandy, which made landfall on October 29, 2012, and multiple, strong winter storms. The ongoing beach monitoring is part of the Hurricane Sandy Supplemental Project GS2-2B. This USGS data series includes the resulting processed elevation point data (xyz) and an interpolated digital elevation model (DEM).

New York↗
USGS2015

High-resolution digital elevation model of lower Cowlitz and Toutle Rivers, adjacent to Mount St. Helens, Washington, based on an airborne lidar survey of October 2007

The lateral blast, debris avalanche, and lahars of the May 18th, 1980, eruption of Mount St. Helens, Washington, dramatically altered the surrounding landscape. Lava domes were extruded during the subsequent eruptive periods of 1980–1986 and 2004–2008. More than three decades after the emplacement of the 1980 debris avalanche, high sediment production persists in the Toutle River basin, which drains the northern and western flanks of the volcano. Because this sediment increases the risk of flooding to downstream communities on the Toutle and lower Cowlitz Rivers, the U.S. Army Corps of Engineers (USACE), under the direction of Congress to maintain an authorized level of flood protection, continues to monitor and mitigate excess sediment in North and South Fork Toutle River basins to help reduce this risk and to prevent sediment from clogging the shipping channel of the Columbia River. From October 22–27, 2007, Watershed Sciences, Inc., under contract to USACE, collected high-precision airborne lidar (light detection and ranging) data that cover 273 square kilometers (105 square miles) of lower Cowlitz and Toutle River tributaries from the Columbia River at Kelso, Washington, to upper North Fork Toutle River (below the volcano's edifice), including lower South Fork Toutle River. These data provide a digital dataset of the ground surface, including beneath forest cover. Such remotely sensed data can be used to develop sediment budgets and models of sediment erosion, transport, and deposition. The U.S. Geological Survey (USGS) used these lidar data to develop digital elevation models (DEMs) of the study area. DEMs are fundamental to monitoring natural hazards and studying volcanic landforms, fluvial and glacial geomorphology, and surface geology. Watershed Sciences, Inc., provided files in the LASer (LAS) format containing laser returns that had been filtered, classified, and georeferenced. The USGS produced a hydro-flattened DEM from ground-classified points at Castle and Coldwater Lakes. Final results averaged about two laser last-return points per square meter. As reported by Watershed Sciences, Inc., vertical accuracy is 10 centimeters (cm) at the 95-percent confidence interval on bare road surfaces; however, over natural terrain, USGS found vertical accuracy to be 10–50 cm. This USGS data series contains the bare-earth lidar data as 1- and 10-meter (m) resolution Esri grid files. Digital-elevation data can be downloaded (1m_DEM.zip and 10m_DEM.zip), as well as a 1-m resolution hillshade image with pyramids (1m_hillshade.zip). These geospatial data files require geographic information system (GIS) software for viewing.

Washington↗
USGS2016

Terrestrial-based lidar beach topography of Fire Island, New York, June 2014

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) in Florida and the USGS Lower Mississippi-Gulf Water Science Center (LMG WSC) in Montgomery, Alabama, collaborated to gather alongshore terrestrial-based lidar beach elevation data at Fire Island, New York. This high-resolution elevation dataset was collected on June 11, 2014, to characterize beach topography and document ongoing beach evolution and recovery, and is part of the ongoing beach monitoring within the Hurricane Sandy Supplemental Project GS2-2B. This USGS data series includes the resulting processed elevation point data (xyz) and an interpolated digital elevation model (DEM).

New York↗
USGS2022

Dynamic rating method for computing discharge from time-series stage data

Ratings are used for a variety of reasons in water-resources investigations. The simplest rating relates discharge to the stage of the river. From a pure hydrodynamics perspective, all rivers and streams have some form of hysteresis in the relation between stage and discharge because of unsteady flow as a flood wave passes. Simple ratings are unable to represent hysteresis in a stage/discharge relation. A dynamic rating method is capable of capturing hysteresis owing to the variable energy slope caused by unsteady momentum and pressure. A dynamic rating method developed to compute discharge from stage for compact channel geometry, referred to as DYNMOD, previously has been developed through a simplification of the one-dimensional Saint-Venant equations. A dynamic rating method, which accommodates compound and compact channel geometry, referred to as DYNPOUND, has been developed through a similar simplification as a part of this study. The DYNMOD and DYNPOUND methods were implemented in the Python programming language. Discharge time series computed with the dynamic rating method implementations were then compared to simulated discharge time series and discrete discharge measurements made at U.S. Geological Survey streamgage sites. Four sets of stage and discharge time series were created using one-dimensional unsteady simulation software with compound channel geometry to compare the results of both dynamic rating methods to results from the full one-dimensional shallow water equations. Discharge time series were computed from stage time series using DYNMOD and DYNPOUND. DYNPOUND outperformed DYNMOD in all four scenarios. The minimum and maximum mean squared logarithmic error (MSLE) for the DYNMOD results were 2.75×10 −2 and 3.40×10 −2 , respectively. The minimum and maximum MSLE for the DYNPOUND results were 2.51×10 −7 and 1.91×10 −4 , respectively. The dynamic rating methods were calibrated for six U.S. Geological Survey streamgage sites using observed discharge data collected at the sites. The calibration objective for each site was to minimize the MSLE of the discharge computed with the rating method with respect to observed discharge. For each site, the calibration included all field measurements within a selected water year. The DYNMOD method failed to compute discharge for the full calibration time series for three sites. A method fails to compute when the implementation returns a nonfinite value at a time step. Because the values computed for following time steps are dependent on the previous time step, a nonfinite value results in nonfinite values that follow. For the three sites for which DYNMOD computed the complete discharge time series, the minimum MSLE for calibration was 2.19×10 −3 and the maximum was 9.77×10 −3 . The MSLE of the DYNPOUND computed discharge calibration time series for the six sites ranged from 3.70×10 −3 to 1.25. For each site, an event-based time period was selected to compare the discharge time series computed with the dynamic rating methods to discrete discharge field measurements made at the streamgage sites. The DYNMOD-computed discharge time series for the three sites had an MSLE range of 2.76×10 −3 to 3.14×10 −2 . The range of MSLE for the six DYNPOUND sites was 3.64×10 −3 to 7.23×10 −2 . Although the DYNMOD method outperforms the DYNPOUND method when calibrated streamgage sites are under consideration, the DYNMOD method failed to compute a discharge time series at three of the six sites. The DYNPOUND method, therefore, was more robust than the DYNMOD method. Improvements to the implementation of the DYNPOUND method may improve the accuracy of the method.

Open-File Report↗
USGS1990

Reference manual for generation and analysis of Habitat Time Series: version II

The selection of an instream flow requirement for water resource management often requires the review of how the physical habitat changes through time. This review is referred to as 'Time Series Analysis." The Tune Series Library (fSLIB) is a group of programs to enter, transform, analyze, and display time series data for use in stream habitat assessment. A time series may be defined as a sequence of data recorded or calculated over time. Examples might be historical monthly flow, predicted monthly weighted usable area, daily electrical power generation, annual irrigation diversion, and so forth. The time series can be analyzed, both descriptively and analytically, to understand the importance of the variation in the events over time. This is especially useful in the development of instream flow needs based on habitat availability. The TSLIB group of programs assumes that you have an adequate study plan to guide you in your analysis. You need to already have knowledge about such things as time period and time step, species and life stages to consider, and appropriate comparisons or statistics to be produced and displayed or tabulated. Knowing your destination, you must first evaluate whether TSLIB can get you there. Remember, data are not answers . This publication is a reference manual to TSLIB and is intended to be a guide to the process of using the various programs in TSLIB. This manual is essentially limited to the hands-on use of the various programs. a TSLIB use interface program (called RTSM) has been developed to provide an integrated working environment where the use has a brief on-line description of each TSLIB program with the capability to run the TSLIB program while in the user interface. For information on the RTSM program, refer to Appendix F. Before applying the computer models described herein, it is recommended that the user enroll in the short course "Problem Solving with the Instream Flow Incremental Methodology (IFIM)." This course is offered by the Aquatic Systems Branch of the National Ecology Research Center. For more information about the TSLIB software, refer to the Memorandum of Understanding. Chapter 1 provides a brief introduction to the Instream Flow Incremental Methodology and TSLIB. Other chapters in this manual provide information on the different aspects of using the models. The information contained in the other chapters includes (2) acquisition, entry, manipulation, and listing of streamflow data; (3) entry, manipulation, and listing of the habitat-versus-streamflow function; (4) transferring streamflow data; (5) water resources systems analysis; (6) generation and analysis of daily streamflow and habitat values; (7) generation of the time series of monthly habitats; (8) manipulation, analysis, and display of month time series data; and (9) generation, analysis, and display of annual time series data. Each section includes documentation for the programs therein with at least one page of information for each program, including a program description, instructions for running the program, and sample output. The Appendixes contain the following: (A) sample file formats; (B) descriptions of default filenames; (C) alphabetical summary of batch-procedure files; (D) installing and running TSLIB on a microcomputer; (E) running TSLIB on a CDC Cyber computer; (F) using the TSLIB user interface program (RTSM); and (G) running WATSTORE on the USGS Amdahl mainframe computer. The number for this version of TSLIB--Version II-- is somewhat arbitrary, as the TSLIB programs were collected into a library some time ago; but operators tended to use and manage them as individual programs. Therefore, we will consider the group of programs from the past that were only on the CDC Cyber computer as Version 0; the programs from the past that were on both the Cyber and the IBM-compatible microcomputer as Version I; and the programs contained in this reference manual as Version II.

Report↗
USGS2023

Application of surrogate technology to predict real-time metallic-contaminant concentrations and loads in the Clark Fork near Grant-Kohrs Ranch National Historic Site, Montana, water years 2019–20

Grant-Kohrs Ranch National Historic Site (GRKO) in southwestern Montana commemorates the frontier cattle era and its formative role in shaping the culture and history of the Western United States. The ranch was designated a national historic landmark in 1960 and a unit of the National Park Service (NPS) by Congress in 1972. The GRKO is unique because of its proximity to large-scale extraction, milling, and smelting of gold, silver, copper, and lead ore from the 1860s to the 1980s in the Butte mining district. During this time, mining and milling wastes were discarded in the upper Clark Fork Basin, resulting in the deposition of large amounts of waste materials (tailings) enriched with metallic contaminants (including cadmium, copper, iron, lead, manganese, zinc, and the metalloid trace element arsenic) in soils and in nearby streams and floodplains. Denuded vegetation and fish kills attributed to large concentrations of heavy metals caused the U.S. Environmental Protection Agency to designate a 120-mile section of the Clark Fork River (hereafter referred to as the “Clark Fork”), including GRKO, to be included on the National Priority List for Superfund cleanup in 1989. In 2018, with oversight from the Montana Department of Environmental Quality, the NPS began remediation of 2.6 miles of the Clark Fork as it flows through GRKO property. In 2019, the U.S. Geological Survey (USGS), in collaboration with the NPS, conducted a study using time-series data from backscatter signals from fixed-point turbidity and acoustic sensors with the intent to provide a high-resolution monitoring tool to estimate metallic-contaminant concentrations (MCCs) and loads during NPS remediation of the Clark Fork. Two monitoring sites at USGS streamgages on the Clark Fork on either side of GRKO property were instrumented with turbidity and acoustic sensors and surrogate relations were developed among time-series data and MCCs. The application of high-resolution surrogate data was used to infer contaminant source and fate and evaluate MCC values relative to aquatic-life standards. Using high-resolution surrogate data, it was determined that during spring runoff and storm-related runoff events, MCCs peaked at their highest values at streamflows markedly lower and prior to peak streamflow. Because MCCs peaked prior to streamflow peaks, it could be inferred that the source of MCCs originated from channel bed sediments in close spatial proximity to the monitoring site or from nearby streambanks and floodplains. High-resolution surrogate data revealed that copper concentrations in the Clark Fork exceeded chronic aquatic-life standards 90 percent of the time when streamflow exceeded 200 cubic feet per second (ft 3 /s) and exceeded acute aquatic-life standards 85 percent of the time when streamflow exceeded 260 ft 3 /s. These data helped support NPS management goals for evaluating variation in water quality during remediation of GRKO property, evaluating MCC values relative to aquatic-life standards, and quantifying benefits from Superfund remediation activities.

Montana↗
USGS2024

Calculation of a suspended-sediment concentration-turbidity regression model and flood-ebb suspended-sediment concentration differentials from marshes near Stone Harbor and Thompsons Beach, New Jersey, 2018–19 and 2022–23

The U.S. Geological Survey collected water velocity and water quality data from salt marshes in Great Channel, southwest of Stone Harbor, New Jersey, and near Thompsons Beach, New Jersey, to evaluate restoration effectiveness after Hurricane Sandy and monitor postrestoration marsh health. Time series data of turbidity and water velocity were collected from 2018 to 2019 and 2022 to 2023 at both sites. Water samples were collected and analyzed for suspended-sediment concentration (SSC), which was used to derive a regression model to estimate a time series of SSC data from turbidity data. The SSC time series data were then combined with the water velocity data to calculate the flood-ebb SSC differential. This report presents the data collection methods, the repeated median regression model used to estimate SSC from turbidity, and the flood-ebb SSC differential calculations.

New Jersey↗
USGS2018

Analysis of groundwater response to tidal fluctuations, Operable Unit 2, Area 8, Naval Base Kitsap, Keyport, Washington

Operable Unit 2, Area 8, at Naval Base Kitsap, Keyport is the site of a former chrome-plating facility that released metals (primarily chromium and cadmium), chlorinated volatile organic compounds, and petroleum compounds into the local environment. To ensure long-term protectiveness, as stipulated in the Fourth Five-Year Review for the site, Naval Facilities Engineering Command Northwest collaborated with the U.S. Environmental Protection Agency, the Washington State Department of Ecology, and the Suquamish Tribe, to collect data to monitor the contamination left in place and to ensure the site does not pose a risk to human health or the environment. To support these efforts, refined information was needed on the interaction of fresh groundwater with seawater in response to the up-to 13-ft tidal fluctuations at this nearshore site adjacent to Port Orchard Bay. The information was analyzed to meet the primary objective of this investigation, which was to determine the optimal time during the semi-diurnal and the neap-spring tidal cycles to sample groundwater for freshwater contaminants in Area 8 monitoring wells. Groundwater levels and specific conductance in five monitoring wells, along with marine water-levels (tidal levels) in Port Orchard Bay, were monitored every 15 minutes during a 3-week duration to determine how nearshore groundwater responds to tidal forcing. Time series data were collected from October 24, 2017, to November 16, 2017, a period that included neap and spring tides. Vertical profiles of specific conductance were also measured once in the screened interval of each well prior to instrument deployment to determine if a freshwater/saltwater interface was present in the well during that particular time. The vertical profiles of specific conductance were measured only one time during an ebbing tide at approximately the top, middle, and bottom of the saturated thickness within the screened interval of each well. The landward-most well, MW8-8, was completely freshwater, while one of the most seaward wells, MW8-9, was completely saline. A distinct saltwater interface was measured in the three other shallow wells (MW8-11, MW8-12, and MW8-14), with the topmost groundwater occurring fresh underlain by higher conductivity water. Lag times between minimum spring-tide level and minimum groundwater levels in wells ranged from about 2 to 4.5 hours in the less-than 20-ft deep wells screened across the water table, and was about 7 hours for the single 48-ft deep well screened below the water table. Those lag times were surprisingly long considering the wells are all located within 200-ft of the shoreline and the local geology is largely coarse-grained glacial outwash deposits. Various manmade subsurface features, such as slurry walls and backfilled excavations, likely influence and confuse the connectivity between seawater and groundwater. The specific-conductance time-series data showed clear evidence of substantial saltwater intrusion into the screened intervals of most shallow wells. Unexpectedly, the intrusion was associated with the neap part of the tidal cycle around November 13–16, when relatively low barometric pressure and high southerly winds led to the highest high and low tides measured during the monitoring period. The data consistently indicated that the groundwater had the lowest specific conductance (was least mixed with seawater) during the prior neap tides around October 30, the same period when the shallow groundwater levels were lowest. Although the specific conductance response is somewhat different between wells, the data do suggest that it is the heights of the actual high-high and low-low tides, regardless of whether or not they occur during the neap or spring part of the cycle, that allows seawater intrusion into the nearshore aquifer at Area 8. With all the data taken into consideration, the optimal time for sampling the shallow monitoring wells at Area 8 would be centered on a 2–5-hour period following the predicted low-low tide during neap tide, with due consideration of local atmospheric pressure and wind conditions that have the potential to generate tides that can be substantially higher than those predicted from lunar-solar tidal forces. The optimal time for sampling the deeper monitoring wells at Area 8 would be during the 6–8-hour period following a predicted low-low tide, also during the neap tide part of the tidal cycle. The specific time window to sample each well following a low tide can be found in table 5. Those periods are when groundwater in the wells is most fresh and least diluted by seawater intrusion. In addition to timing, consideration should be given to collecting undisturbed samples from the top of the screened interval (or top of the water table if below the top of the interval) to best characterize contaminant concentrations in freshwater. A downhole conductivity probe could be used to identify the saltwater interface, above which would be the ideal depth for sampling.

Washington↗
USGS2014

Mapping mountain pine beetle mortality through growth trend analysis of time-series landsat data

Disturbances are key processes in the carbon cycle of forests and other ecosystems. In recent decades, mountain pine beetle (MPB; Dendroctonus ponderosae) outbreaks have become more frequent and extensive in western North America. Remote sensing has the ability to fill the data gaps of long-term infestation monitoring, but the elimination of observational noise and attributing changes quantitatively are two main challenges in its effective application. Here, we present a forest growth trend analysis method that integrates Landsat temporal trajectories and decision tree techniques to derive annual forest disturbance maps over an 11-year period. The temporal trajectory component successfully captures the disturbance events as represented by spectral segments, whereas decision tree modeling efficiently recognizes and attributes events based upon the characteristics of the segments. Validated against a point set sampled across a gradient of MPB mortality, 86.74% to 94.00% overall accuracy was achieved with small variability in accuracy among years. In contrast, the overall accuracies of single-date classifications ranged from 37.20% to 75.20% and only become comparable with our approach when the training sample size was increased at least four-fold. This demonstrates that the advantages of this time series work flow exist in its small training sample size requirement. The easily understandable, interpretable and modifiable characteristics of our approach suggest that it could be applicable to other ecoregions.

Colorado↗
USGS1998

Partitioning and transport of total and methyl mercury in the Lower Fox River, Wisconsin

To investigate transport and partitioning processes of Hg(T) in the Fox River, we coupled detailed time series data of total mercury (Hg(T)) at the river mouth with transect sampling in the Lower Fox River. Unfiltered Hg(T) concentrations in the Fox River during the study period (April 1994-October 1995) ranged from 1.8 to 182 ng L(-1) with a median of 24.8 ng L-1, predominantly (93.6%) in the particulate phase. These levels were significantly elevated compared with other large tributaries to Lake Michigan (Hurley, J. P.; Shafer, M. M.; Cowell, S. E.; Overdier, J. T.; Hughes, P. E.; Armstrong, D. E. Environ. Sci. Technol. 1996, 30, 20932098). Transect sampling revealed progressively increasing water column Hg(T) concentrations and Hg(T) particulate enrichment downstream, which were consistent with trends in sediment Hg(T) levels in the river. Resuspended sediments are likely the predominant source of Hg from the Fox River into Green Bay. Despite elevated Hg(T) concentrations, methyl mercury (MeHg) concentrations were relatively low, suggesting limited bioavailability of Hg(T) associated with sediments.To investigate transport and partitioning processes of HgT in the Fox River, we coupled detailed time series data of total mercury (HgT) at the river mouth with transect sampling in the Lower Fox River. Unfiltered HgT concentrations in the Fox River during the study period (April 1994-October 1995) ranged from 1.8 to 182 ng L-1 with a median of 24.8 ng L-1, predominantly (93.6%) in the particulate phase. These levels were significantly elevated compared with other large tributaries to Lake Michigan. Transect sampling revealed progressively increasing water column HgT concentrations and HgT particulate enrichment downstream, which were consistent with trends in sediment HgT levels in the river. Resuspended sediments are likely the predominant source of Hg from the Fox River into Green Bay. Despite elevated HgT concentrations, methyl mercury (MeHg) concentrations were relatively low, suggesting limited bioavailability of HgT associated with sediments.

Environmental Science & Technology↗
USGS2018

Analysis of groundwater response to tidal fluctuations, Site 10 Naval Magazine Indian Island, Port Hadlock, Washington

Site 10 at Naval Magazine Indian Island is an approximately 3.7-acre inactive landfill. The site was used as the primary landfill for the island from about 1945 until the mid-1970s, receiving paints, batteries, trash, and materials. In a memorandum to Washington State Department of Ecology, Naval Facilities Engineering Command Northwest (NAVFAC NW) stipulated that a new tidal study would be conducted to recalculate tidal influence lag-time in each groundwater monitoring well at Site 10. Groundwater levels and specific conductance in five monitoring wells, along with marine water-levels (tidal levels) in Port Townsend Bay, were monitored every 15 minutes during a 2-week period to better understand nearshore groundwater-seawater interactions at Site 10. Time series data were collected from April 17 to May 3, 2018, a period that included neap and spring tides. Vertical profiles of specific conductance were measured once in the screened interval of each well prior to instrument deployment to determine if a freshwater/saltwater interface was present in the well prior to instrument deployment. Profiles where measured during an ebbing tide at approximately the top, middle, and bottom of the saturated thickness within the screened interval of each well. The landward-most well, MW10-8 and coastline wells MW10-10, MW10-11 and MW10-12R, had a uniform specific conductance in the range of fresh or brackish water. Landfill monitoring well MW10-6 showed the highest uniform specific conductance profile also in the range of brackish water. Lag times between minimum spring-tide levels and minimum groundwater levels in wells ranged from about 0 to 4 hours. Results of lag times showed a logical increase in lag time as the distance increases from the shoreline to each monitoring well. The specific-conductance time-series data showed minimal change in the screened interval of each well. Fluctuation of specific conductance in each well was unique but no sharp groundwater saltwater interface was observed. Increases in specific conductivity concurrent with spring low tides were measured in coastline wells, suggesting shoreward transport of high specific conductivity landfill leachate rather than seawater intrusion. Based on all the data collected during this investigation, the optimal time for sampling monitoring wells at Site 10 would be during a 0–4-hour period following the predicted low-low tide.

Washington↗
USGS2013

Simulation of climate-change effects on streamflow, lake water budgets, and stream temperature using GSFLOW and SNTEMP, Trout Lake Watershed, Wisconsin

Although groundwater and surface water are considered a single resource, historically hydrologic simulations have not accounted for feedback loops between the groundwater system and other hydrologic processes. These feedbacks include timing and rates of evapotranspiration, surface runoff, soil-zone flow, and interactions with the groundwater system. Simulations that iteratively couple the surface-water and groundwater systems, however, are characterized by long run times and calibration challenges. In this study, calibrated, uncoupled transient surface-water and steady-state groundwater models were used to construct one coupled transient groundwater/surface-water model for the Trout Lake Watershed in north-central Wisconsin, USA. The computer code GSFLOW (Ground-water/Surface-water FLOW) was used to simulate the coupled hydrologic system; a surface-water model represented hydrologic processes in the atmosphere, at land surface, and within the soil-zone, and a groundwater-flow model represented the unsaturated zone, saturated zone, stream, and lake budgets. The coupled GSFLOW model was calibrated by using heads, streamflows, lake levels, actual evapotranspiration rates, solar radiation, and snowpack measurements collected during water years 1998–2007; calibration was performed by using advanced features present in the PEST parameter estimation software suite. Simulated streamflows from the calibrated GSFLOW model and other basin characteristics were used as input to the one-dimensional SNTEMP (Stream-Network TEMPerature) model to simulate daily stream temperature in selected tributaries in the watershed. The temperature model was calibrated to high-resolution stream temperature time-series data measured in 2002. The calibrated GSFLOW and SNTEMP models were then used to simulate effects of potential climate change for the period extending to the year 2100. An ensemble of climate models and emission scenarios was evaluated. Downscaled climate drivers for the period 2010–2100 showed increases in maximum and minimum temperature over the scenario period. Scenarios of future precipitation did not show a monotonic trend like temperature. Uncertainty in the climate drivers increased over time for both temperature and precipitation. Separate calibration of the uncoupled groundwater and surface-water models did not provide a representative initial parameter set for coupled model calibration. A sequentially linked calibration, in which the uncoupled models were linked by means of utility software, provided a starting parameter set suitable for coupled model calibration. Even with sequentially linked calibration, however, transmissivity of the lower part of the aquifer required further adjustment during coupled model calibration to attain reasonable parameter values for evaporation rates off a small seepage lake (a lake with no appreciable surface-water outlets) with a long history of study. The resulting coupled model was well calibrated to most types of observed time-series data used for calibration. Daily stream temperatures measured during 2002 were successfully simulated with SNTEMP; the model fit was acceptable for a range of groundwater inflow rates into the streams. Forecasts of potential climate change scenarios showed growing season length increasing by weeks, and both potential and actual evapotranspiration rates increasing appreciably, in response to increasing air temperature. Simulated actual evapotranspiration rates increased less than simulated potential evapotranspiration rates as a result of water limitation in the root zone during the summer high-evapotranspiration period. The hydrologic-system response to climate change was characterized by a reduction in the importance of the snow-melt pulse and an increase in the importance of fall and winter groundwater recharge. The less dynamic hydrologic regime is likely to result in drier soil conditions in rainfed wetlands and uplands, in contrast to less drying in groundwater-fed systems. Seepage lakes showed larger forecast stage declines related to climate change than did drainage lakes (lakes with outlet streams). Seepage lakes higher in the watershed (nearer to groundwater divides) had less groundwater inflow and thus had larger forecast declines in lake stage; however, ground-water inflow to seepage lakes in general tended to increase as a fraction of the lake budgets with lake-stage decline because inward hydraulic gradients increased. Drainage lakes were characterized by less simulated stage decline as reductions in outlet streamflow of set losses to other water flows. Net groundwater inflow tended to decrease in drainage lakes over the scenario period. Simulated stream temperatures increased appreciably with climate change. The estimated increase in annual average temperature ranged from approximately 1 to 2 degrees Celsius by 2100 in the stream characterized by a high groundwater inflow rate and 2 to 3 degrees Celsius in the stream with a lower rate. The climate drivers used for the climate-change scenarios had appreciable variation between the General Circulation Model and emission scenario selected; this uncertainty was reflected in hydrologic flow and temperature model results. Thus, as with all forecasts of this type, the results are best considered to approximate potential outcomes of climate change.

Wisconsin↗
USGS2016

Flexible risk metrics for identifying and monitoring conservation-priority species

Region-specific conservation programs should have objective, reliable metrics for species prioritization and progress evaluation that are customizable to the goals of a program, easy to comprehend and communicate, and standardized across time. Regional programs may have vastly different goals, spatial coverage, or management agendas, and one-size-fits-all schemes may not always be the best approach. We propose a quantitative and objective framework for generating metrics for prioritizing species that is straightforward to implement and update, customizable to different spatial resolutions, and based on readily available time-series data. This framework is also well-suited to handling missing-data and observer error. We demonstrate this approach using North American Breeding Bird Survey (NABBS) data to identify conservation priority species from a list of over 300 landbirds across 33 bird conservation regions (BCRs). To highlight the flexibility of the framework for different management goals and timeframes we calculate two different metrics. The first identifies species that may be inadequately monitored by NABBS protocols in the near future (TMT, time to monitoring threshold), and the other identifies species likely to decline significantly in the near future based on recent trends (TPD, time to percent decline). Within the individual BCRs we found up to 45% (mean 28%) of the species analyzed had overall declining population trajectories, which could result in up to 37 species declining below a minimum NABBS monitoring threshold in at least one currently occupied BCR within the next 50 years. Additionally, up to 26% (mean 8%) of the species analyzed within the individual BCRs may decline by 30% within the next decade. Conservation workers interested in conserving avian diversity and abundance within these BCRs can use these metrics to plan alternative monitoring schemes or highlight the urgency of those populations experiencing the fastest declines. However, this framework is adaptable to many taxa besides birds where abundance time-series data are available.

Ecological Indicators↗
USGS1996

Factors affecting suspended-solids concentrations in South San Francisco Bay, California

Measurements of suspended-solids concentration (SSC) were made at two depths at three sites in South San Francisco Bay (South Bay) to determine the factors that affect SSC. Twenty-eight segments of reliable and continuous SSC time series data longer than 14 days were collected from late 1991 or 1992 through September 1993. Spectral analysis and singular spectrum analysis were used to relate these data segments to time series of several potential forcing factors, including diurnal and semidiurnal tides, the spring-neap tidal cycle, wind shear, freshwater runoff, and longitudinal density differences. SSC is greatest during summer, when a landward wind shear is applied to South Bay by the afternoon sea breeze. About one half the variance of SSC is caused by the spring-neap cycle, and SSC lags the spring-neap cycle by about 2 days. Relatively short duration of slack water limits the duration of deposition of suspended solids and consolidation of newly deposited bed sediment during the tidal cycle, so suspended solids accumulate in the water column as a spring tide is approached and slowly deposit as a neap tide is approached. Perturbations in SSC caused by wind and local runoff from winter storms during the study period were usually much smaller than SSC variations caused by the spring-neap cycle. Variations of SSC at the study sites at tidal timescales are tidally forced, and nonlinear physical processes are significant. Advective transport dominates during spring tides, when water with higher SSC due to wind wave resuspension is advected to the main channel from shallow water, but, during neap tides, advective transport is less significant. The findings of this and other studies indicate that the tidally averaged transport of suspended solids responds to seasonal variations of wind shear in South Bay.

Journal of Geophysical Research C: Oceans↗
USGS2008

Joint variability of global runoff and global sea surface temperatures

Global land surface runoff and sea surface temperatures (SST) are analyzed to identify the primary modes of variability of these hydroclimatic data for the period 1905-2002. A monthly water-balance model first is used with global monthly temperature and precipitation data to compute time series of annual gridded runoff for the analysis period. The annual runoff time series data are combined with gridded annual sea surface temperature data, and the combined dataset is subjected to a principal components analysis (PCA) to identify the primary modes of variability. The first three components from the PCA explain 29% of the total variability in the combined runoff/SST dataset. The first component explains 15% of the total variance and primarily represents long-term trends in the data. The long-term trends in SSTs are evident as warming in all of the oceans. The associated long-term trends in runoff suggest increasing flows for parts of North America, South America, Eurasia, and Australia; decreasing runoff is most notable in western Africa. The second principal component explains 9% of the total variance and reflects variability of the El Ni??o-Southern Oscillation (ENSO) and its associated influence on global annual runoff patterns. The third component explains 5% of the total variance and indicates a response of global annual runoff to variability in North Aflantic SSTs. The association between runoff and North Atlantic SSTs may explain an apparent steplike change in runoff that occurred around 1970 for a number of continental regions.

Journal of Hydrometeorology↗
USGS1996

National energy research seismic library; Powder River basin, Montana-Wyoming; surface reflection and vertical seismic profile data used in seismic-stratigraphic investigations for ground-water aquifers and hydrocarbon traps

This Digital Data Series publication contains both raw and processed seismic data recorded during the period 1975 through 1978 by several geophysical service companies under contract to the USGS in the following study areas of the Powder River Basin, Montana and Wyoming: 1. Powder River and Custer Counties, MT (T. 1 S., T. 1-2 N., R. 53-54 E.) 2. Carter County, MT (T. 57-58 N., R. 65 W.) and Crook County, WY (T. 9 S., R.57-58 E.) 3. Powder River and Carter Counties, MT (T. 8 S., R. 53-55 E.) 4. Niobrara County, WY (T. 36-38 N., R. 61-62 W.) and Weston County, WY (T. 45 N., R. 61 W.) Four multichannel Vibroseis seismic lines, six Vertical Seismic Profiles (VSP's), and associated support material (observer's notes, X-Y coordinates, elevations of source and receivers, for example) are included. The raw (unprocessed) field data and a processed version of each surface profile and VSP are contained in standard SEG-Y format files; support material are in ASCII format text files. The processed surface data are versions which were reprocessed by the USGS in 1995 using state-of-the-art seismic data processing software.

Data Series↗
USGS2011

Geospatial Multi-Agency Coordination (GeoMAC) wildland fire perimeters, 2008

The Geospatial Multi-Agency Coordination (GeoMAC) has been collecting and storing data on wildland fire perimeters since August 2000. The dataset presented via this U.S. Geological Survey Data Series product contains the GeoMAC wildland fire perimeter data for the calendar year 2008, which are based upon input from incident intelligence sources, Global Positioning System (GPS) data, and infrared (IR) imagery. Wildland fire perimeter data are obtained from the incidents, evaluated for completeness and accuracy, and processed to reflect consistent field names and attributes. After a quality check, the perimeters are loaded to GeoMAC databases, which support the GeoMAC Web application for access by wildland fire managers and the public. The wildland fire perimeters are viewed through the Web application. The data are subsequently archived according to year and state and are made available for downloading through the Internet in shapefile and Keyhole Markup Language (KML) format. These wildland fire perimeter data are also retained for historical, planning, and research purposes. The datasets that pertain to this report can be found on the Rocky Mountain Geographic Science Center HTTP site at http://rmgsc.cr.usgs.gov/outgoing/GeoMAC/historic_fire_data/. The links are also provided on the sidebar.

Arizona;California;Colorado;Idaho;Nevada;New Mexic↗