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24 records · Page 2Linked to original sources
USGS2016

Using inferential sensors for quality control of Everglades Depth Estimation Network water-level data

The Everglades Depth Estimation Network (EDEN), with over 240 real-time gaging stations, provides hydrologic data for freshwater and tidal areas of the Everglades. These data are used to generate daily water-level and water-depth maps of the Everglades that are used to assess biotic responses to hydrologic change resulting from the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. The generation of EDEN daily water-level and water-depth maps is dependent on high quality real-time data from water-level stations. Real-time data are automatically checked for outliers by assigning minimum and maximum thresholds for each station. Small errors in the real-time data, such as gradual drift of malfunctioning pressure transducers, are more difficult to immediately identify with visual inspection of time-series plots and may only be identified during on-site inspections of the stations. Correcting these small errors in the data often is time consuming and water-level data may not be finalized for several months. To provide daily water-level and water-depth maps on a near real-time basis, EDEN needed an automated process to identify errors in water-level data and to provide estimates for missing or erroneous water-level data. The Automated Data Assurance and Management (ADAM) software uses inferential sensor technology often used in industrial applications. Rather than installing a redundant sensor to measure a process, such as an additional water-level station, inferential sensors, or virtual sensors, were developed for each station that make accurate estimates of the process measured by the hard sensor (water-level gaging station). The inferential sensors in the ADAM software are empirical models that use inputs from one or more proximal stations. The advantage of ADAM is that it provides a redundant signal to the sensor in the field without the environmental threats associated with field conditions at stations (flood or hurricane, for example). In the event that a station does malfunction, ADAM provides an accurate estimate for the period of missing data. The ADAM software also is used in the quality assurance and quality control of the data. The virtual signals are compared to the real-time data, and if the difference between the two signals exceeds a certain tolerance, corrective action to the data and (or) the gaging station can be taken. The ADAM software is automated so that, each morning, the real-time EDEN data are compared to the inferential sensor signals and digital reports highlighting potential erroneous real-time data are generated for appropriate support personnel. The development and application of inferential sensors is easily transferable to other real-time hydrologic monitoring networks.

Florida↗
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↗
USGS2013

Data management challenges in species distribution modeling

An important component in the fields of ecology and conservation biology is understanding the environmental conditions and geographic areas that are suitable for a given species to inhabit. A common tool in determining such areas is species distribution modeling which uses computer algorithms to determine the spatial distribution of organisms. Most commonly the correlative relationships between the organism and environmental variables are the primary consideration. The data requirements for this type of modeling consist of known presence and possibly absence locations of the species as well as the values of environmental or climatic covariates thought to define the species habitat suitability at these locations. These covariate data are generally extracted from remotely sensed imagery, interpolated/gridded historical climate data, or downscaled climate model output. Traditionally, ecologists and biologists have constructed species distribution models using workflows and data that reside primarily on their local workstations or networks. This workflow is becoming challenging as scientists increasingly try to use these modeling techniques to inform management decisions under different climate change scenarios. This challenge stems from the fact that remote sensing products, gridded historical climate, and downscaled climate models are not only increasing in spatial and temporal resolution but proliferating as well. Any rigorous assessment of uncertainty requires a computationally intensive sensitivity analysis accounting for various sources of uncertainty. The scientists fitting these models generally do not have the background in computer science required to take advantage of recent advances in web-service based data acquisition, remote high-powered data processing, or scientific workflow systems. Ecologists in the field of modeling are in need of a tractable platform that abstracts the inherent computational complexity required to incorporate the burgeoning field of coupled climate and ecological response modeling. In this paper we describe the computational challenges in species distribution modeling and solutions using scientific workflow systems. We focus on the Software for Assisted Species Modeling (SAHM) a package within VisTrails, an open-source scientific workflow system.

Bulletin of the Technical Committee on Data Engine↗
USGS2007

Surficial sediment character of the New York-New Jersey offshore continental shelf region: A GIS compilation

Broad continental shelf regions such as the New York Bight are the product of a complex geologic history and dynamic oceanographic processes, dominated by the Holocene marine transgression (>100 m sea-level rise) following the end of the last Pleistocene ice advance ~ 20,000 years ago. The area of the U.S. Exclusive Economic Zone (U.S. EEZ) territory, extending 200 nautical miles seaward from the coast, is larger than the continental U.S. and contains submerged landforms that provide a variety of natural functions and societal benefits, such as: critical habitats for fisheries, ship navigation and homeland security, and engineering activities (i.e. oil and gas platforms, pipeline and cable routes, potential wind-energy-generation sites). Some parts of the continental margins, particularly inner-continental shelf regions, also contain unconsolidated hard-mineral deposits such as sand and gravel that are regarded as potential aggregate resources to meet or augment needs not met by onshore deposits (Williams, 1992). The present distribution of surficial sediment off the northeastern United States is shaped from the deposits left by the last glaciation and reflects the cumulative effects of sediment erosion, transport, sorting, and deposition by storm and tidal processes during the Holocene rise in sea level. As a result, the sediments on the sea floor represent both an historical record of former conditions and a guide to possible future sedimentary environments. The U.S. Geological Survey (USGS) through the Coastal and Marine Geology Program, in cooperation with the University of Colorado and other partners, has compiled extant sediment character and textural data as well as other geologic information on the sea floor from all regions around the U.S. into the usSEABED data system (Reid and others, 2005; Buczkowski and others, 2006; Reid and others, 2006). The usSEABED system, which contains information on sediment grain size and lithology for more than 340,500 stations within the U.S. EEZ. has been developed and populated with data as part of the USGS Marine Aggregate Resources and Processes and the National Benthic Habitats projects in order to provide the base-line data needed to update the current maps of offshore surficial geologic character and sediment distribution. The maps are also used to characterize benthic sea floor environments important for marine ecosystems. U.S. Geological Survey, Data Series 118 (Reid and others, 2005), of the usSEABED data release series, represents the combined efforts of the USGS and several other government agencies to provide a unified resource for accessing and preserving records of U.S. east coast sea floor geologic information and sediment texture data. For this present report, we have chosen to focus on the New York-New Jersey region, an area that has been intensely studied by the USGS for many years to address many complex issues. This report illustrates the uses of the usSEABED database for GIS applications, while offering additional insight into the resources and data available from the USGS and its collaborative institutions. This report is based on data contained in U.S. Geological Survey Data Series 118 (Reid and others, 2005) and shows an assortment of example GIS products that are possible using usSEABED. All data are intended to be GIS-ready and should not require any additional cleanup, formatting, or renaming of fields in order to use the data in a Geographic Information System. This project employs the Environmental Systems Research Institute's (ESRI) ArcView™ software. Many of these maps were made as part of the ongoing USGS study to assess marine aggregate resources offshore New York and New Jersey, but these maps can serve many other purposes. The marine science community, educators, students and others are encouraged to use these data to generate GIS products for their own purposes. The objectives of the Marine Aggregate Resources and Processes project are to produce a series of new geologic maps and reports of the sea floor that will provide scientific insights into the character and geologic development of U.S. continental margins and to use these maps and information to assess the potential availability of offshore sand and gravel resources. The mapping and aggregate resource assessments are being conducted on a national scale using the usSEABED data base as described in Williams and others (2003). Potential uses for these data include: (1) defining the geological variability of the sea floor in relation to benthic habitat diversity; (2) improving our understanding of the processes that control the distribution and transport of bottom sediments and benthic habitats; (3) locating aggregate resources for beach nourishment and industrial applications; and (4) providing a detailed geospatial framework for future marine science research, monitoring, and management activities. The initial assessments are in progress for the New York Bight and Louisiana offshore areas.

New Jersey, New York↗
USGS2011

Compilation of watershed models for tributaries to the Great Lakes, United States, as of 2010, and identification of watersheds for future modeling for the Great Lakes Restoration Initiative

As part of the Great Lakes Restoration Initiative (GLRI) during 2009–10, the U.S. Geological Survey (USGS) compiled a list of existing watershed models that had been created for tributaries within the United States that drain to the Great Lakes. Established Federal programs that are overseen by the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Army Corps of Engineers (USACE) are responsible for most of the existing watershed models for specific tributaries. The NOAA Great Lakes Environmental Research Laboratory (GLERL) uses the Large Basin Runoff Model to provide data for the management of water levels in the Great Lakes by estimating United States and Canadian inflows to the Great Lakes from 121 large watersheds. GLERL also simulates streamflows in 34 U.S. watersheds by a grid-based model, the Distributed Large Basin Runoff Model. The NOAA National Weather Service uses the Sacramento Soil Moisture Accounting model to predict flows at river forecast sites. The USACE created or funded the creation of models for at least 30 tributaries to the Great Lakes to better understand sediment erosion, transport, and aggradation processes that affect Federal navigation channels and harbors. Many of the USACE hydrologic models have been coupled with hydrodynamic and sediment-transport models that simulate the processes in the stream and harbor near the mouth of the modeled tributary. Some models either have been applied or have the capability of being applied across the entire Great Lakes Basin; they are (1) the SPAtially Referenced Regressions On Watershed attributes (SPARROW) model, which was developed by the USGS; (2) the High Impact Targeting (HIT) and Digital Watershed models, which were developed by the Institute of Water Research at Michigan State University; (3) the Long-Term Hydrologic Impact Assessment (L–THIA) model, which was developed by researchers at Purdue University; and (4) the Water Erosion Prediction Project (WEPP) model, which was developed by the National Soil Erosion Research Laboratory of the U.S. Department of Agriculture. During 2010, the USGS used the Precipitation-Runoff Modeling System (PRMS) to create a hydrologic model for the Lake Michigan Basin to assess the probable effects of climate change on future groundwater and surface-water resources. The Water Availability Tool for Environmental Resources (WATER) model and the Analysis of Flows In Networks of CHannels (AFINCH) program also were used to support USGS GLRI projects that required estimates of streamflows throughout the Great Lakes Basin. This information on existing watershed models, along with an assessment of geologic, soils, and land-use data across the Great Lakes Basin and the identification of problems that exist in selected tributary watersheds that could be addressed by a watershed model, was used to identify three watersheds in the Great Lakes Basin for future modeling by the USGS. These watersheds are the Kalamazoo River Basin in Michigan, the Tonawanda Creek Basin in New York, and the Bad River Basin in Wisconsin. These candidate watersheds have hydrogeologic, land-type, and soil characteristics that make them distinct from each other, but that are representative of other tributary watersheds within the Great Lakes Basin. These similarities in the characteristics among nearby watersheds will enhance the usefulness of a model by improving the likelihood that parameter values from a previously modeled watershed could reliably be used in the creation of a model of another watershed in the same region. The software program Hydrological Simulation Program–Fortran (HSPF) was selected to simulate the hydrologic, sedimentary, and water-quality processes in these selected watersheds. HSPF is a versatile, process-based, continuous-simulation model that has been used extensively by the scientific community, has the ongoing technical support of the U.S. Environmental Protection Agency and USGS, and provides a means to evaluate the effects that land-use changes or management practices might have on the simulated processes.

Great Lakes Basin↗
USGS2022

Contaminants of emerging concern in the Great Lakes: Science to inform management practices for protecting the health and integrity of wildlife populations from adverse effects: GLRI action plan I, focus area 1, goal 5

Executive Summary: Under Action Plan I (2010-2014) of the Great Lakes Restoration Initiative (GLRI), Federal and Academic partners began an investigation of the presence and distribution of contaminants of emerging concern (CECs) in the Great Lakes and potential impacts on fish and wildlife. The term CECs is applied to a broad range of chemicals that are currently in use but for which we currently lack good understanding of whether fish, wildlife, or humans are being exposed and/or whether negative health or environmental effects are expected if exposure occurs. Pharmaceuticals, personal care products, flame retardants, many current use pesticides, and poly- and perfluorinated chemicals are some well-known groups of CECs, but there is no definitive or comprehensive list that can be used to support the management of CECs to reduce impacts on the Great Lakes ecosystem. Four overarching goals were identified for this collaborative investigation: 1. Evaluate the sources, occurrence, and distribution of CECs across the Great Lakes Basin. 2. Examine associations between the distribution of CECs and land-use patterns. 3. Review both scientific literature and field-generated data to determine the potential for CECs to cause adverse effects on Great Lakes fish and wildlife populations. 4. Develop efficient strategies to survey and/or monitor for threats that CECs may pose in order to take effective management actions before those threats evolve into large scale impacts on Great Lakes ecosystems or the services they provide. Achievement of these goals ensures progress towards Focus Area 1: Toxic Substances and Areas of Concern from GLRI Action Plan I, Goal 5: “ The health and integrity of wildlife populations and habitat are protected from adverse chemical and biological effects associated with the presence of toxic substances in the Great Lakes Basin ”. This large-scale research effort was comprised of individual and collaborative projects from multiple federal agencies and academic institutions, involving over 85 investigators, and overseen by the U.S. Environmental Protection Agency (EPA) Region 5, Great Lakes National Program Office. Partners include the United States Geological Survey, the National Oceanic and Atmospheric Administration, U.S. Fish and Wildlife Service, Saint Cloud State University, the U.S. EPA Office of Research and Development, and the U.S. Army Corps of Engineers. Key findings: 1. Contaminants of emerging concern were found throughout the monitored Great Lakes tributaries, but types and concentrations vary in association with regional land use. CECs were detected in nearly all samples collected. The type and concentration of the specific contaminants detected varied considerably among field sites and in association with land use type, such as urban, agricultural, wetland, 2 or forest. Contaminants were detected in the water column, sediment, and tissues of all species surveyed in the current work (mussels, aquatic insects, fish, and insect-eating birds). 2. There were over 20 contaminants for which CEC concentrations approached or exceeded those reported to cause toxicity in laboratory experiments. This was based on detection in water, sediments and or biota at one or more field sites. These contaminants represent compounds that warrant further investigation and monitoring with respect to potential impacts in certain areas of the Great Lakes basin. Based on the present investigation, compounds of greatest concern include: polycyclic aromatic hydrocarbons, associated with oil-based products and combustion of organic matter; atrazine, an herbicide; dichlorvos, an insecticide; and ibuprofen and venlafaxine, both pharmaceuticals. 3. Results suggest that mixtures of CECs presently found in most Great Lakes tributary locations surveyed may elicit subtle biological effects, but likely are not, alone, causing obvious detriment to current communities of fish and wildlife. CECs detected in the Great Lakes were associated with subtle biological effects like changes in gene expression, altered circulating glucose, etc. in both wild-caught and laboratory-reared organisms. These effects were generally not indicative of reproductive failure or mortality. However, the effects may have more serious implications when combined with other sources of stress like habitat degradation, changing climate conditions, and competition with invasive species. Due to limited historical data, it is unknown whether severe CEC-related impacts have already affected aquatic communities in waterbodies that have received long-term inputs of these contaminants. Likewise, under Action Plan I, biological effects were not necessarily evaluated at the sites where CEC concentrations exceeding laboratory toxicity thresholds were detected. As a result, strategic, ongoing surveillance and monitoring of CECs is warranted. This collaborative investigation resulted in new tools, approaches, and data that can be used to inform and support the management of CECs to reduce their impacts on Great Lakes natural resources. The following products of this research effort are available through https://communities.geoplatform.gov/glri/ or by contacting the investigators (see technical chapters found in Appendices A-F): 1. Database of CEC occurrence and concentrations in US tributary streams. The database includes CEC detections in water, sediment, and fish and wildlife tissues, and represents the most comprehensive survey of CECs in the Great Lakes Region. 2. Synopses of results and key findings. Integrated summaries of results, conclusions, and management implications of the CEC research are available through reports, topical fact sheets, and presentations. 3. Technical publications: This collaborative research effort has resulted in over 50 peer-reviewed publications, agency reports, and data releases that can be of use to resource managers, the scientific community, and members of the public. 4. Innovative tools. Innovative monitoring devices, sampling equipment, conceptual frameworks, and software applications were developed over the course of this 3 research. These tools are transferable to stakeholders via internet accessibility or via specifications, instructions, and demonstration detailed in technical publications. Hypotheses to guide CECs research under Action Plan II. Findings from 2010-2014 were used to guide further research in 2015-2018 for basin-wide surveillance of CECs and for sites warranting further study of potential biological impacts of CECs. Additional surveillance included both evaluation of additional classes of contaminants and expanded lists for chemical classes shown to be of greatest concern. Mixtures of some of the most frequently detected contaminants were also tested in laboratory studies to understand whether long term exposures to multiple contaminants may result in effects not evident from uncontrolled, short-term field experiments.

Great Lakes↗