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At least 217 records · Page 12Linked to original sources
USGS2003

Preliminary publications book 2 from project on mineral resources, metallogenesis, and tectonics of northeast Asia

This is the Web version of a CD-ROM publication. This report consists of summary major compilations and syntheses accomplished in the six-year project through April 2003 for the study on the Mineral Resources, Metallogenesis, and Tectonics of Northeast Asia (Eastern and Southern Siberia, Mongolia, Northeastern China, South Korea, and Japan). The major scientific goals and benefits of the project are to: (1) provide a comprehensive international data base on the mineral resources of the region that is the first, extensive knowledge available in English; (2) provide major new interpretations of the origin and crustal evolution of mineralizing systems and their host rocks, thereby enabling enhanced, broad-scale tectonic reconstructions and interpretations; and (3) promote trade and scientific and technical exchanges between the North America and Northeast Asia. Data from the project are providing sound scientific data and interpretations for commercial firms, governmental agencies, universities, and individuals that are developing new ventures and studies in the project area, and for land-use planning studies that deal with both mineral potential issues. Northeast Asia has vast potential for known and undiscovered mineral deposits; however, little information existed in English in the West until publication of products from this project. Consequently, data and interpretations from the project are providing basic knowledge for major scientific, commercial, national, and international endeavors by other interested individuals and groups.

Siberia↗
USGS2025

Scaling from microsite to landscape to resolve litter decomposition dynamics in globally extensive drylands

1. Decomposition controls the release of carbon and nutrients from decaying plant litter into soils or the atmosphere. In most biomes decomposition rates can be accurately predicted with simple mathematical models, but these models have long under-predicted decomposition in globally- extensive drylands. 2. We posit that the exposed surface conditions characteristic of drylands makes litter decomposition uniquely subject to microsite-specific environmental controls and spatially-variable microbial communities. As such, decomposition in dryland ecosystems – which are characterized by extremes in temporal heterogeneity of climate conditions and spatial heterogeneity of vegetation cover with corresponding microclimate variability – is a prime example of a macrosystems process that can be addressed by merging field data with new predictive models operating across a hierarchical continuum of spatial scales and process resolutions. 3. A macrosystems approach offers promise to reconcile model-measurement discrepancies by integrating observations and experiments across multiple scales, from microsites (e.g., shrub sub-canopy or intercanopy) to regions (e.g., across a 100s of km2 study site with complex topography, precipitation, and temperature) and ultimately to a continental perspective (e.g., North American drylands). 4. Recent developments in technology and data availability position the scientific community to integrate lab, field, modeling, and remote sensing approaches across a hierarchical range of scales to capture the spatiotemporal distribution of litter and environmental conditions needed to predict decay dynamics at the micro-to-macroscale. This multi-scale approach promises a path forward to resolving a longstanding disconnect between measured and modeled data in dryland litter decomposition. 5. Dryland litter decomposition presents an excellent case study for resolving spatially and temporally complex biogeochemical dynamics through a hierarchical, multidisciplinary macrosystems approach. 6. We focus on dryland litter decomposition, but the hierarchical, multidisciplinary macrosystems approach we outline shows great potential for resolving other spatially and temporally complex biogeochemical processes across a wide range of ecosystems.

Functional Ecology↗
USGS2021

System characterization report on the German Aerospace Center (DLR) Earth Sensing Imaging Spectrometer (DESIS)

Executive Summary This report addresses system characterization of the German Aerospace Center (DLR) Earth Sensing Imaging Spectrometer (DESIS) and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present the methodology and procedures for characterization and the technical and operational information about the specific sensing system being evaluated. These reports also provide a description of data measurements, data retention practices, and data analysis results and provide system characterization conclusions. In partnership with Teledyne Brown Engineering, DLR built the DESIS hyperspectral instrument, which Teledyne Brown Engineering then integrated onto its International Space Station-based imaging platform, the Multi-User System for Earth Sensing. DLR developed the processing software and, together with Innovative Imaging and Research, completes the validation and calibration of the data products. DESIS was launched in 2018, and the data are used for scientific research in atmospheric physics and Earth sciences. The DESIS sensor contributes to the scientific and commercial utilization of the International Space Station and helps to further hyperspectral remote sensing technologies for future satellites. More information on DLR satellites and sensors is included within the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and at https://www.dlr.de/DE/Home/home_node.html . The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that DESIS has an interior geometric performance of less than a 3.30-meter (less than 0.11 pixel) root mean square error in band-to-band registration, an exterior geometric performance in the range of a 2.40- (0.08 pixel) to 17.40-meter (0.58 pixel) offset in comparison to the Landsat 8 Operational Land Imager, a radiometric performance in the range of −0.013 to 1.011 (offset and slope), and a spatial performance for band 130 of 1.5 pixels at full width at half maximum, with a modulation transfer function at a Nyquist frequency of 0.167.

Open-File Report↗
USGS2017

Functional traits and ecological affinities of riparian plants along the Colorado River in Grand Canyon

Trait-based approaches to vegetation analyses are becoming more prevalent in studies of riparian vegetation dynamics, including responses to flow regulation, groundwater pumping, and climate change. These analyses require species trait data compiled from the literature and floras or original field measurements. Gathering such data makes trait-based research time intensive at best and impracticable in some cases. To support trait-based analysis of vegetation along the Colorado River through Grand Canyon, a data set of 20 biological traits and ecological affinities for 179 species occurring in that study area was compiled. This diverse flora shares species with many riparian areas in the western USA and includes species that occur across a wide moisture gradient. Data were compiled from published scientific papers, unpublished reports, plant fact sheets, existing trait databases, regional floras, and plant guides. Data for ordinal environmental tolerances were more readily available than were quantitative traits. More publicly available data are needed for traits of both common and rare southwestern U.S. plant species to facilitate comprehensive, trait-based research. The trait data set is free to use and can be downloaded from ScienceBase: https://www.sciencebase.gov/catalog/item/58af41dee4b01ccd54f9f2ff and https://dx.doi.org/10.5066/F7QV3JN1

Arizona↗
USGS2021

Field methods, quality-assurance, and data management plan for water-quality activities and water-level measurements, Idaho National Laboratory, Idaho

Introduction Water-quality activities and water-level measurements conducted by the U.S. Geological Survey (USGS) Idaho National Laboratory (INL) Project Office coincide with the USGS mission of appraising the quantity and quality of the Nation’s water resources. The activities are conducted in cooperation with the U.S. Department of Energy’s (DOE) Idaho Operations Office. Results of water-quality and hydraulic head investigations are presented in various USGS publications or in refereed scientific journals, and the data are stored in the National Water Information System (NWIS) database. The results of the studies are used by researchers, regulatory and managerial agencies, and civic groups. In its broadest sense, “quality assurance” refers to doing the job right the first time. It includes the functions of planning for products, review and acceptance of the products, and an audit designed to evaluate the system that produces the products. Quality control and quality assurance differ in that quality control ensures that things are done correctly given the “state-of-the-art” technology, and quality assurance ensures that quality control is maintained within specified limits.

Idaho↗
USGS2021

Can Landsat 7 preserve its science capability with a drifting orbit?

Since 2017, the orbit of Landsat 7 has drifted outside its nominal mission requirement toward an earlier acquisition time because of limited onboard fuel resources. This makes quantitative analyses from Landsat 7 data potentially unreliable for many scientific studies. To comprehensively understand the effect of ongoing (2018–2020) orbit drift on Landsat 7 data, we compared surface reflectance and Top-Of-Atmosphere (TOA) reflectance of growing season observations (July 1 ± 30 days) from Landsat 7 with orbit drift and Landsat 8 with nominal orbit using a total of 10,000 randomly selected Northern Hemisphere (0–75 0 N) terrestrial pixels. To evaluate the future (2021–2023) effect of Landsat 7's orbit drift, we analyzed the historical Northern Hemisphere terrestrial growing season Earth Observing-1 (EO-1) TOA reflectance images, which shared a similar orbit drift as Landsat 7 but occurred much earlier. Results suggest that Landsat 7's orbit drift has already led to a general decrease in surface reflectance and TOA reflectance in 2019 and 2020, with a limited impact (overall reflectance changes less than 0.007). The influence of orbit drift is more substantial for the two shortwave infrared (SWIR) bands and the near infrared (NIR) band, but less for the three visible bands (i.e., Red, Green, and Blue). The Normalized Difference Vegetation Index (NDVI), derived from either surface reflectance or TOA reflectance, increased less than 0.003 in 2020. According to the historical EO-1 TOA reflectance data, we estimate that the effect of Landsat 7's orbit drift will be much more dramatic in the future (e.g., the NIR and SWIR bands will decrease more than 0.015 since July 1, 2021), and for different land cover types, the effects of orbit drift are also quite different. To reduce this influence, we examined the c-factor Bidirectional Reflectance Distribution Function (BRDF) normalization approach to correct the orbit drift impact for Landsat 7 surface reflectance data collected between 2019 and 2020. We found that the c-factor BRDF can reduce the data difference substantially, but how this approach works after Landsat 7's orbit drifts further still requires more investigation. Therefore, we determined that Landsat 7 can preserve its science capability until 2020, but will be less reliable for remote sensing applications that need accurate absolute radiometric values after 2020. Correction methods such as c-factor BRDF could be a potential viable approach to maintain its science capability going forward.

Science of Remote Sensing↗
USGS2019

Fluvial sedimentary history of Arlington Canyon, Channel Islands National Park, California

Arlington Canyon, in the northwest part of Santa Rosa Island, Channel Islands National Park, California, has been the setting for important scientific discoveries over the past half century, including the oldest human remains in North America, several vertebrate fossil sites, and purported evidence of a catastrophic extinction event at the end of the Pleistocene. The canyon is filled with alluvial sediments that date to between 16.4 and 1.1 ka (thousands of calibrated years before present), representing accumulation that occurred primarily in response to rising sea levels during the late Pleistocene and Holocene. The deposits are laterally discontinuous, exhibit a high degree of sedimentary complexity, and contain evidence of past climates and environments, including fossil bones, burned plant macrofossils, and invertebrate microfossils. Here, we show that it is critical to view the observations, data, and conclusions of scientific studies conducted in the canyon within this larger context so that localized facets of the spatially and temporally extensive alluvial deposits are not misinterpreted or misrepresented. By improving the baseline understanding of processes and drivers of sediment accumulation in Arlington Canyon, we hope to offer a solid foundation and better underpinning for future archeological, paleontological, and geochemical studies here and throughout the northern Channel Islands.

California↗
USGS2025

Methodology for compilation of previously published contour data showing the altitude of the base of Dakota Sandstone on the Colorado Plateau, Arizona, Colorado, New Mexico, and Utah

Structure contours and other geologic information from numerous published geologic maps were digitized and compiled into a digital dataset showing the configuration of a single stratigraphic datum, the base of the Dakota Sandstone and its equivalents across the Colorado Plateau. The principal maps compiled in digital form are a series of 1:250,000-scale 1 degree (°) × 2° quadrangle maps published by the U.S. Geological Survey, augmented by other geologic maps published at various map scales. The compiled digital dataset contains geologic map polygons of the Dakota Sandstone and regional stratigraphic equivalents, the location of faults and fold axes, structure contour lines that define the altitude of the base of the unit and bedding orientation data computed from the structure contour lines. This report provides the scientific rationale for compilation of these data and describes the compilation methodology for each of the data elements. This report provides an extended description of the data compilation in a companion U.S. Geological Survey digital data release of spatial data and attributes associated with the contoured surface and associated geologic data layers.

Arizona, Colorado, New Mexico, Utah↗
USGS2011

Making United States Integrated Ocean Observing System (U.S. IOOS) inclusive of marine biological resources

An important Data Management and Communication (DMAC) goal is to enable a multi-disciplinary view of the ocean environment by facilitating discovery and integration of data from various sources, projects and scientific domains. United States Integrated Ocean Observing System (U.S. IOOS) DMAC functional requirements are based upon guidelines for standardized data access services, data formats, metadata, controlled vocabularies, and other conventions. So far, the data integration effort has focused on geophysical U.S. IOOS core variables such as temperature, salinity, ocean currents, etc. The IOOS Biological Observations Project is addressing the DMAC requirements that pertain to biological observations standards and interoperability applicable to U.S. IOOS and to various observing systems. Biological observations are highly heterogeneous and the variety of formats, logical structures, and sampling methods create significant challenges. Here we describe an informatics framework for biological observing data (e.g. species presence/absence and abundance data) that will expand information content and reconcile standards for the representation and integration of these biological observations for users to maximize the value of these observing data. We further propose that the approach described can be applied to other datasets generated in scientific observing surveys and will provide a vehicle for wider dissemination of biological observing data. We propose to employ data definition conventions that are well understood in U.S. IOOS and to combine these with ratified terminologies, policies and guidelines.

Conference Paper↗
USGS2022

U.S. Geological Survey Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST)—Information Management Technology Plan

Introduction More than 840 publications, 575 data releases, and 330 project web pages from the U.S. Geological Survey (USGS) pertain to the Colorado River Basin. Limited interconnections between Colorado River Basin publications, data, and web pages restrict the ability to synthesize and interpret scientific resources. Currently, these pieces are spread across multiple isolated locations, internal systems, data repositories, and local offices. The increasing size, complexity, and diversity of Colorado River Basin data creates additional need for integration. These different data types—including discrete, continuous, aerial, remote sensing, geophysical, geospatial, and other types in varied formats—are collected over numerous time and space scales and require data-intensive science and technology to integrate. Information management technology (IMT) resources are enterprise capabilities that the USGS workforce can leverage at multiple scales with consistent interoperable solutions to better facilitate integrated science. The USGS 21st Century Science Strategy directs the USGS to establish enterprise IMT capabilities that support integrated work through interoperable software and database solutions at multiple scales. This Information Management Technology Plan identifies nine steps to leverage new and existing technologies, data, models, and scientific knowledge to support integrated science projects conducted across the Colorado River Basin. These steps are transferable to integrated-science studies in other locations.

Arizona, Colorado, Nevada, New Mexico, Utah, Wyomi↗
USGS2007

Observatories, program in USA

The Geomagnetism Program of the US Geological Survey has, for over a century now, monitored the Earth's magnetic field through a network of magnetic observatories and conducted scientific analysis on the data collected. The program traces its origins to the Reorganization Act of 1843, in which Congress authorized the creation of a coastal survey agency, as part of the Treasury Department, that was responsible for, among other things, geomagnetic surveys. The 19th century saw the establishment of relatively short‐lived magnetic stations, as well as the production of declination maps for the United States and territories. With the purchase of Alaska, coastal surveys became an increasingly higher priority, and in 1889 the Coast and Geodetic Survey, with a Division of Terrestrial Magnetism, was established. The first essentially permanent geomagnetic observatories were established under the Division's leadership of Dr. Louis A. Bauer and Dr. John A. Fleming: Cheltenham Maryland Observatory was established in 1900, subsequently moved to the Fredericksburg site in 1956; Sitka Alaska Observatory was established in 1901 and that of Honolulu Hawaii in 1902. Soon after these observatories became operational, it was found that the Sitka and Honolulu magnetometers were also sensitive to local earthquakes, and so seismometers were installed at the sites. In part, because of this colocation of instruments, the magnetic and seismological programs in the Coast and Geodetic Survey were united in 1925 under the Division of Geomagnetism and Seismology. Over the years, the Geomagnetism Program has evolved in response to the needs of the United States and in response to changes in the nation's various federal agencies. In 1903 the Coast and Geodetic Survey was transferred to the newly organized Department of Commerce, and in 1970 the survey became part of the National Oceanic and Atmospheric Administration (NOAA). In 1973, the US Geological Survey of the Department of the Interior assumed responsibility for the nation's Geomagnetism and Seismology programs.

Book chapter↗
USGS2022

Trends in volcano seismology: 2010 to 2020 and beyond

Volcano seismology has been fundamental to our current understanding of crustal magma migration and eruption. The increasing availability of portable seismic networks with the creative use of seismic sources and ambient noise has led to a better understanding of the volcanic structure of many volcanoes and is producing increasingly detailed images of the volcanic subsurface. The past decade (2010-2020) has seen advances in our understanding of seismic sources under and surrounding volcanoes through precise locations, and through analysis of source mechanisms from seismic signals that are more varied and smaller in magnitude, reaching beyond traditional techniques. In tandem with continued research on fundamental physics-based understanding of volcano-seismic sources, new advances in computational analyses including machine learning methods will push our understanding of volcanic processes into the future. Incorporation of multidisciplinary geophysical observations (especially infrasound) has become commonplace, and our understanding of infrasound propagation and sources will feed back into our ability to monitor ongoing eruptions and surficial mass movements. Open-source codes will permit widespread evaluation and adoption of new methodologies for volcano-seismic analysis and inversion. Combined with quantitative and conceptual source models using improved structural constraints, these new methodologies will better characterize the range of volcano-seismic signal evolution scenarios and hold promise for creating better short-term forecasts. Finally, permanent instrumentation is available on an expanding range of volcanoes, and open data policies are increasingly making these data available to the scientific community in near real time.

Bulletin of Volcanology↗
USGS1978

Mars synthetic topographic mapping

Topographic contour maps of Mars are compiled by the synthesis of data acquired from various scientific experiments of the Mariner 9 mission, including S-band radio-occulation, the ultraviolet spectrometer (UVS), the infrared radiometer (IRR), the infrared interferometer spectrometer (IRIS) and television imagery, as well as Earth-based radar information collected at Goldstone, Haystack, and Arecibo Observatories. The entire planet is mapped at scales of 1:25,000,000 and 1:25,000,000 using Mercator, Lambert, and polar stereographic map projections. For the computation of map projections, a biaxial spheroid figure is adopted. The semimajor and semiminor axes are 3393.4 and 3375.7 km, respectively, with a polar flattening of 0.0052. For the computation of elevations, a topographic datum is defined by a gravity field described in terms of spherical harmonics of fourth order and fourth degree combined with a 6.1-mbar occulation pressure surface. This areoid can be approximated by a triaxial ellipsoid with semimajor axes of A = 3394.6 km and B = 3393.3 km and a semiminor axis of C = 3376.3 km. The semimajor axis A intersects the Martian surface at longitude 105°W. The dynamic flattening of Mars is 0.00525. The contour intercal of the maps is 1 km. For some prominent features where overlapping pictures from Mariner 9 are available, local contour maps at relatively larger scales were also compiled by photogrammetric methods on stereo plotters.

Icarus↗
USGS2026

Revisiting chlorophyll a thresholds for San Francisco Bay: Insights from observations of phytoplankton molecular abundance

Harmful Algal Blooms (HABs) are a hazard for coastal environments worldwide; identifying screening thresholds of chlorophyll- a (chl- a) associated with increased risk of HABs is a management priority. Molecular surveillance of coastal phytoplankton and bivalve biotoxins could be used to link chl- a with HAB risk, but requires an understanding of whether the HAB risks increase uniformly as chl-a rises, or whether some taxa are disproportionately favored, and if these relationships vary by season. In this study, we present a novel use of molecular abundance data to investigate the scientific bases for estuarine chl- a thresholds protective against HABs. In San Francisco Bay (SFB), California, the relationship between molecular relative abundance (as measured by 18S metabarcoding) of nine different HAB taxa, absolute quantitative polymerase chain reaction (qPCR) abundance, and mussel toxin concentrations of a subset of the taxa were investigated for thresholds as a function of increasing chl- a . Our results show most HAB taxa did not increase in absolute or relative abundance during SFB’s spring bloom interval, when chl- a levels were highest (>10 µg/L) but the assemblage was dominated by non-harmful diatoms. However, several flagellated, mixotrophic taxa did increase above their molecular baseline in fall, and the combined probability of any HAB occurring above baseline was elevated when chl- a reached ∼4.6 µg/L in the fall. This work demonstrates the promise of molecular approaches in disentangling the seasonally complex interplay between stressors and phytoplankton/HAB community responses and has the potential to provide clearer, more cost-effective monitoring and mitigation strategies for managers.

California↗
USGS2011

A simple and effective method for filling gaps in Landsat ETM+ SLC-off images

The scan-line corrector (SLC) of the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor failed in 2003, resulting in about 22% of the pixels per scene not being scanned. The SLC failure has seriously limited the scientific applications of ETM+ data. While there have been a number of methods developed to fill in the data gaps, each method has shortcomings, especially for heterogeneous landscapes. Based on the assumption that the same-class neighboring pixels around the un-scanned pixels have similar spectral characteristics, and that these neighboring and un-scanned pixels exhibit similar patterns of spectral differences between dates, we developed a simple and effective method to interpolate the values of the pixels within the gaps. We refer to this method as the Neighborhood Similar Pixel Interpolator (NSPI). Simulated and actual SLC-off ETM+ images were used to assess the performance of the NSPI. Results indicate that NSPI can restore the value of un-scanned pixels very accurately, and that it works especially well in heterogeneous regions. In addition, it can work well even if there is a relatively long time interval or significant spectral changes between the input and target image. The filled images appear reasonably spatially continuous without obvious striping patterns. Supervised classification using the maximum likelihood algorithm was done on both gap-filled simulated SLC-off data and the original "gap free" data set, and it was found that classification results, including accuracies, were very comparable. This indicates that gap-filled products generated by NSPI will have relevance to the user community for various land cover applications. In addition, the simple principle and high computational efficiency of NSPI will enable processing large volumes of SLC-off ETM+ data.

Remote Sensing of Environment↗
USGS2014

Discussion of “Some factors affecting rates of sedimentation in the Columbia River basin”

h ydrologists are generally aware of the number and complexity of the variables that are encountered in all aspects of hydrology, and the great difficulty of analyzing these factors quantitatively because of inadequacy of basic data. Because of limitations in funds, time, or scientific manpower, it is likely that the basic data will generally be less than the hydrologist's hopes. In this predicament, many students have sought methods whereby it might be possible to determine the approximate effects of various factors, on the basis of meager available information. The authors, by using statistical methods of analysis, have pointed out one way that may well be rewarding in studies of other aspects of hydrology where little basic information is available.

Eos, Transactions, American Geophysical Union↗
USGS1999

Contaminated-sediment database development and assessment in Boston Harbor

Bottom sediments have been regarded as memory banks for contaminant inputs to urban waterways. Bottom sediments accumulate by the addition of particles that enter the waterway from many sources (U.S. National Research Council, 1989). Sediments include solid contaminants, as well as contaminants from the water column that are adsorbed on organic matter or soil (rock) particles. Sediments from Boston Harbor and adjacent parts of Massachusetts Bay are now among the most intensively studied in the Nation in terms of chemical composition. Scientists at the U.S. Geological Survey (USGS), Woods Hole, Mass., undertook a pioneering effort to assemble a database from all available sources of information on chemicals in sediments of the Boston Harbor study area. The database was created to help understand the distribution of sediment contaminants and their sources, transport, and other processes and to support environmental management. The work involved collaboration with the U.S. Environmental Protection Agency (USEPA), the U.S. Army Corps of Engineers (USACOE), the Massachusetts Water Resources Authority, and other organizations. More than 100,000 sediment measurements from more than 3,000 samples were gleaned from 1,500 references. New approaches were developed to scientifically edit and validate data from heterogeneous sources. The compiled data included inorganic and organic chemical information and physical parameters like sediment texture (grain size), as well as documentation to minimize a userđs need to track down hard-to-find reports.

Massachusetts↗
USGS2007

A Science Plan for a Comprehensive Regional Assessment of the Atlantic Coastal Plain Aquifer System in Maryland

The Maryland Coastal Plain region is, at present, largely dependent upon ground water for its water supply. Decades of increasing pumpage have caused ground-water levels in parts of the Maryland Coastal Plain to decline by as much as 2 feet per year in some areas of southern Maryland. Continued declines at this rate could affect the long-term sustainability of ground-water resources in Maryland's heavily populated Coastal Plain communities and the agricultural industry of the Eastern Shore. In response to a recommendation in 2004 by the Advisory Committee on the Management and Protection of the State's Water Resources, the Maryland Geological Survey and the U.S. Geological Survey have developed a science plan for a comprehensive assessment that will provide new scientific information and new data management and analysis tools for the State to use in allocating ground water in the Coastal Plain. The comprehensive assessment has five goals aimed at improving the current information and tools used to understand the resource potential of the aquifer system: (1) document the geologic and hydrologic characteristics of the aquifer system in the Maryland Coastal Plain and appropriate areas of adjacent states; (2) conduct detailed studies of the regional ground-water-flow system and water budget for the aquifer system; (3) improve documentation of patterns of water quality in all Coastal Plain aquifers, including the distribution of saltwater; (4) enhance ground-water-level, streamflow, and water-quality-monitoring networks in the Maryland Coastal Plain; and (5) develop science-based tools to facilitate sound management of the ground-water resources in the Maryland Coastal Plain. The assessment, as designed, will be conducted in three phases and if fully implemented, is expected to take 7 to 8 years to complete. Phase I, which was initiated in January 2006, is an effort to assemble all the information and investigation tools needed to do a more comprehensive assessment of the aquifer system. The work will include updating the hydrogeologic framework, developing a Geographic Information System-based aquifer information system, refinement of water-use information, assessment of existing water-quality data, and development of detailed plans for ground-water-flow and management models. Phase II is an intensive study phase during which a regional ground-water-flow model will be developed and calibrated for the entire region of Maryland in the Atlantic Coastal Plain as well as appropriate areas of Delaware and Virginia. The model will be used to simulate flow and water levels in the aquifer system and to study the water budget of the system. The model analysis will be based on published information but will be supplemented with field investigations of recharge and leakage in the aquifer system. Localized and finely discretized ground-water-flow models that are embedded in the regional model will be developed for selected areas of heavy withdrawals. Other modeling studies will be conducted to better understand flow in the unconfined parts of the aquifer system and to support the recharge studies. Phase II will also include selected water-quality studies and a study to determine how hydrologic and water-quality-monitoring networks need to be enhanced to appropriately assess the sustainability of the Coastal Plain aquifer system. Phase III will be largely devoted to the development and application of a ground-water optimization model. This model will be linked to the ground-water-flow model to create a model package that can be used to test different water-management scenarios. The management criteria that will be used to develop these scenarios will be determined in consultation with a variety of state and local stakeholders and policy makers in Phases I and II of the assessment. The development of the aquifer information system is a key component of the assessment. The system will store all relevant aquifer data

Open-File Report↗