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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 559 records · Page 31Linked to original sources
USGS1987

BIA interpretation techniques for vegetation mapping using thematic mapper false color composites (interim report for San Carlos Reservation)

The Bureau of Indian Affairs (BIA) is responsible for the natural resource management of approximately 52 million acres of Trust lands in the contiguous United States. The lands are distributed in a "patchwork" fashion throughout the country. Management responsibilities on these areas include: minerals, range, timber, fish and wildlife, agricultural, cultural, and archaeological resources. In an age of decreasing natural resources and increasing natural resource values, effective multiple resource management is critical. BIA has adopted a "systems approach" to natural resource management which utilizes Geographic Information System (GIS) technology. The GIS encompasses a continuum of spatial and relational data elements, and included functional capabilities such as: data collection, data entry, data base development, data analysis, data base management, display, and report generalization. In support of database development activities, BIA and BLM/TGS conducted a cooperative effort to investigate the potential of 1:100,000 scale Thematic Mapper (TM) False Color Composites (FCCs) for providing vegetation information suitable for input to the GIS and to later be incorporated as a generalized Bureau wide land cover map. Land cover information is critical as the majority of reservations currently have no land cover information in either map or digital form. This poster outlines an approach which includes the manual interpretation of land cover using TM FCCs, the digitizing of interpreted polygons, and the editing of digital data, used upon ground truthing exercises. An efficient and cost-effective methodology for generating large area land cover information is illustrated for the Mineral Strip area on the San Carlos Indian Reservation in Arizona. Techniques which capitalize on the knowledge of the local natural resources professionals, while minimizing machine processing requirements, are suggested.

Arizona↗
USGS2016

Non-invasive genetic sampling of Southern Mule Deer ( Odocoileus hemionus fuliginatus ) reveals limited movement across California State Route 67 in San Diego County

—The Southern Mule Deer is a mobile but non-migratory large mammal found throughout southern California and is a covered species in the San Diego Multi-Species Conservation Plan. We assessed deer movement and population connectivity across California State Route 67 and two smaller roads in eastern San Diego County using non-invasive genetic sampling. We collected deer scat pellets between April and November 2015, and genotyped pellets at 15 microsatellites and a sex determination marker. We successfully genotyped 71 unique individuals from throughout the study area and detected nine recapture events. Recaptures were generally found close to original capture locations (within 1.5 km). We did not detect recaptures across roads; however, pedigree analysis detected 21 first order relative pairs, of which approximately 20% were found across State Route 67. Exact tests comparing allele frequencies between groups of individuals in pre-defined geographic clusters detected significant genetic differentiation across State Route 67. In contrast, the assignment-based algorithm of STRUCTURE supported a single genetic cluster across the study area. Our data suggest that State Route 67 may reduce, but does not preclude, movement and gene flow of Southern Mule Deer.

California↗
USGS2002

A hierarchical analysis of population change with application to Cerulean Warblers

Estimation of population change from count surveys is complicated by variation in quality of information among sample units, by the need for covariates to accommodate factors that influence detectability of animals, and by multiple geographic scales of interest. We present a hierarchical model for estimation of population change from the North American Breeding Bird Survey. Hierarchical models, in which population parameters at different geographic scales are viewed as random variables, provide a convenient framework for summary of population change among regions, accommodating regional variation in survey quality and a variety of distributional assumptions about observer effects and other nuisance parameters. Markov chain Monte Carlo methods provide a convenient means for fitting these models and also allow for construction of estimates of derived variables such as weighted regional trends and composite yearly population indices. We construct an overdispersed Poisson regression model for estimation of trend and year effects for Cerulean Warblers (Dendroica cerulea), accommodating nuisance covariates for observer and start-up effects, and estimating abundance- and area-weighted annual indices at regional and continent-wide geographic scales. A goodness-of-fit test is also presented for the model. Cerulean Warblers declined at a rate of 3.04% per year over the interval 1966-2000.

Ecology↗
USGS2018

Interoperability in planetary research for geospatial data analysis

For more than a decade there has been a push in the planetary science community to support interoperable methods for accessing and working with geospatial data. Common geospatial data products for planetary research include image mosaics, digital elevation or terrain models, geologic maps, geographic location databases (e.g., craters, volcanoes) or any data that can be tied to the surface of a planetary body (including moons, comets or asteroids). Several U.S. and international cartographic research institutions have converged on mapping standards that embrace standardized geospatial image formats, geologic mapping conventions, U.S. Federal Geographic Data Committee (FGDC) cartographic and metadata standards, and notably on-line mapping services as defined by the Open Geospatial Consortium (OGC). The latter includes defined standards such as the OGC Web Mapping Services (simple image maps), Web Map Tile Services (cached image tiles), Web Feature Services (feature streaming), Web Coverage Services (rich scientific data streaming), and Catalog Services for the Web (data searching and discoverability). While these standards were developed for application to Earth-based data, they can be just as valuable for planetary domain. Another initiative, called VESPA (Virtual European Solar and Planetary Access), will marry several of the above geoscience standards and astronomy-based standards as defined by International Virtual Observatory Alliance (IVOA). This work outlines the current state of interoperability initiatives in use or in the process of being researched within the planetary geospatial community.

Planetary and Space Science↗
USGS2001

Pesticides in the hydrologic system - What do we know and what's next?

Even though the occurrence and behaviour of pesticides in the environment have been studied for decades, water-quality managers and the public still demand more complete and consistent information, and there are many unanswered questions for environmental scientists. In many respects, the greatest potential for unintended adverse effects of pesticides is through contamination of the hydrologic system, which supports aquatic life and related food chains and is used for recreation, drinking water, and many other purposes. The movement of water is one of the primary mechanisms by which pesticides are transported from targeted application areas to other parts of the environment; thus, there is potential for movement into and through all components of the hydrologic system. Extensive reviews of existing information on pesticides in the hydrologic system, including the atmosphere (Majewski and Capel, 1995), ground water (Barbash and Resek, 1996), surface water (Larson et al., 1997), and fluvial sediments and aquatic biota (Nowell et al., 1999), uncovered volumes of useful information, but also noted critical information gaps. For example: (a) relatively few pesticides have been thoroughly studied, particularly transformation products; (b) most data have been collected for small-scale site and field studies in agricultural areas; (c) urban areas have received little attention for monitoring or research; (d) the geographic and temporal distributions of data collection have been highly uneven; and (e) comparing and synthesizing results from most studies is difficult because of inconsistent approaches to data collection and chemical analysis.

Hydrological Processes↗
USGS1983

Infrared remote sensing for monitoring rainfall

Evaluations of thermal infrared satellite data from TIROS-N and the Heat Capacity Mapping Mission (HCMM) showed that rainfall distribution patterns could be reliably detected on images acquired up to at least three days after the event. The temperature relationship decreased eight days after the event when soil variations influenced the signal. A time-series analysis reduced thermal variability normally observed over diverse landscapes and increased the sensitivity of the procedures. The method of repetitive low-resolution thermal observations could be operationally employed over large geographic regions with currently available satellite systems. The results would augment the existing rain gauge stations by increasing the spatial sensitivity and the reliability of detection and mapping individual rainfall events.

Agricultural Water Management↗
USGS2002

Snow chemistry of the Cascade-Sierra Nevada Mountains

This investigation assesses geographic variations in atmospheric deposition in Washington, Oregon, and California using snow cores from the Cascade-Sierra Nevada Mountains, collected from late February to mid-March 1983. A statistical analysis of the analytical and sampling precision was made. The snowpack in the higher Cascades and Sierra Nevada is not strongly influenced by anthropogenic activities at present. The pH of snow samples ranges from 5.11 to 5.88. Sulfate and nitrate correlate with H+ in some segments of the sample traverse. The SO4 data show apparent influence from major source areas in Washington and California; nitrate does not. An apparent decrease in NH4 in snow in Washington and California suggests atmospheric interactions resulting in the removal of NH4. The NH4 reduction raises questions about nutrient supply to the mountain vegetation. Heavy-metal correlations included Cd, Cu, and Fe with Pb, and Mn with K and DOC, among others. No correlation was found between constituents and snow-water content.

California, Oregon, Washington↗
USGS2022

Quantifying the relationship between prey density, livestock and illegal killing of leopards

Many large mammalian carnivores are facing population declines due to illegal killing (e.g., shooting) and habitat modification (e.g., livestock farming). Illegal killing occurs cryptically and hence is difficult to detect. However, reducing illegal killing requires a solid understanding of its magnitude and underlying drivers, while accounting for the imperfect detection of illegal killing events. Despite the importance of illegal killing of large carnivores in comparison with other causes of mortality, its relationship with potential drivers such as livestock density and wild prey abundance is rarely described. Using ranger-collected data (2007-2019) of leopard killing events and data on covariates (livestock density, wild prey abundance, road length, protected area size, elevation) across Iran, we applied a single-visit N-mixture model to jointly model variation in detection probability and expected annualized number of leopard killing events. Over the study period, we estimated 428 leopard mortalities (95% CI 184–1014), which was 45% larger than the observed number. Expected intensity of leopard killing was positively related to protected area size, livestock density and wild prey abundance. Detection of leopard killing was higher in areas with more developed road networks. Synthesis and applications: Ranger based monitoring data on poaching of carnivores are cost effective, but traditional analysis does not take into account imperfect detection. We show that innovative statistics (single-visit N-mixture modeling) can reliably quantify poaching events and address their drivers, at large geographical scales. We used the example of the Persian leopard across Iran, but our approach is also applicable to understand killing dynamics of other species. Results suggest that a high frequency of leopard killing is likely to occur in areas with > 100 livestock per km 2 and > 450 individuals of wild prey per km 2 . This highlights the need for improved management of livestock grazing and effective measures around high-risk protected areas to mitigate human-leopard conflict and reduce killing of leopards.

Journal of Applied Ecology↗
USGS2007

Climate factor for small-basin flood frequency

A climate factor, CT, (T = 2-, 25-, and 100-year recurrence intervals) that delineates regional trends in small-basin flood frequency was derived using data from 71 long-term rainfall record sites. Values of CT at these sites were developed by a regression analysis that related rainfall-runoff model estimates of T-year floods to a sample set of 50 model calibrations. CT was regionalized via kriging to develop maps depicting its geographic variation for a large part of the United States east of the 105th meridian. Kriged estimates of CT and basin-runoff characteristics were used to compute regionalized T-year floods for 200 small drainage basins. Observed T-year flood estimates also were developed for these sites. Regionalized floods are shown to account for a large percentage of the variability in observed flood estimates with coefficients of determination ranging from 0.89 for 2-year floods to 0.82 for 100-year floods. The relative importance of the factors comprising regionalized flood estimates is evaluated in terms of scale (size of drainage area), basin-runoff characteristics (rainfall-runoff model parameters), and climate (CT).

Water Resources Bulletin↗
USGS2004

Rectified images of selected geologic maps in the Northern Rockies Area, Idaho, Montana, Washington, and Wyoming

Selected geologic maps covering parts of the Northern Rocky Mountains and adjacent areas were converted to raster images and georeferenced (rectified) for use in a geographic information system (GIS). These rectified images were created for the purpose of visually comparing published geologic maps with other geospatial information. However, they cannot be queried or used for spatial analysis thus limiting their use in a GIS. The 42 georeferenced images included in this report range in scale from 1:250,000 to 1:100,000.Tagged Image Format (TIFF) images of the maps were generated by scanning an original paper map or converting previously published Portable Document Format (PDF) images or Encapsulated Post-Script (EPS) files. To reduce file size and minimize image overlap, the TIFF images were cropped, and then rectified using ArcMap? 8 and converted to MrSID? images. Information in the explanation and cross sections can be viewed in un-rectified images of the original publications that are included with this report. In addition, the text in the map unit description along with the unit name, map label, and a citation are organized in a searchable PDF file.

Data Series↗
USGS2014

Spatio-temporal analysis of gyres in oriented lakes on the Arctic Coastal Plain of northern Alaska based on remotely sensed images

The formation of oriented thermokarst lakes on the Arctic Coastal Plain of northern Alaska has been the subject of debate for more than half a century. The striking elongation of the lakes perpendicular to the prevailing wind direction has led to the development of a preferred wind-generated gyre hypothesis, while other hypotheses include a combination of sun angle, topographic aspect, and/or antecedent conditions. A spatio-temporal analysis of oriented thermokarst lake gyres with recent (Landsat 8) and historical (Landsat 4, 5, 7 and ASTER) satellite imagery of the Arctic Coastal Plain of northern Alaska indicates that wind-generated gyres are both frequent and regionally extensive. Gyres are most common in lakes located near the Arctic coast after several days of sustained winds from a single direction, typically the northeast, and decrease in number landward with decreasing wind energy. This analysis indicates that the conditions necessary for the Carson and Hussey (1962) wind-generated gyre for oriented thermokarst lake formation are common temporally and regionally and correspond spatially with the geographic distribution of oriented lakes on the Arctic Coastal Plain. Given an increase in the ice-free season for lakes as well as strengthening of the wind regime, the frequency and distribution of lake gyres may increase. This increase has implications for changes in northern high latitude aquatic ecosystems, particularly if wind-generated gyres promote permafrost degradation and thermokarst lake expansion.

Alaska↗
USGS2000

Genetic diversity and epidemiology of infectious hematopoietic necrosis virus in Alaska

Forty-two infectious hematopoietic necrosis virus (IHNV) isolates from Alaska were analyzed using the ribonuclease protection assay (RPA) and nucleotide sequencing. RPA analyses, utilizing 4 probes, N5, N3 (N gene), GF (G gene), and NV (NV gene), determined that the haplotypes of all 3 genes demonstrated a consistent spatial pattern. Virus isolates belonging to the most common haplotype groups were distributed throughout Alaska, whereas isolates in small haplotype groups were obtained from only 1 site (hatchery, lake, etc.). The temporal pattern of the GF haplotypes suggested a 'genetic acclimation' of the G gene, possibly due to positive selection on the glycoprotein. A pairwise comparison of the sequence data determined that the maximum nucleotide diversity of the isolates was 2.75% (10 mismatches) for the NV gene, and 1.99% (6 mismatches) for a 301 base pair region of the G gene, indicating that the genetic diversity of IHNV within Alaska is notably lower than in the more southern portions of the IHNV North American range. Phylogenetic analysis of representative Alaskan sequences and sequences of 12 previously characterized IHNV strains from Washington, Oregon, Idaho, California (USA) and British Columbia (Canada) distinguished the isolates into clusters that correlated with geographic origin and indicated that the Alaskan and British Columbia isolates may have a common viral ancestral lineage. Comparisons of multiple isolates from the same site provided epidemiological insights into viral transmission patterns and indicated that viral evolution, viral introduction, and genetic stasis were the mechanisms involved with IHN virus population dynamics in Alaska. The examples of genetic stasis and the overall low sequence heterogeneity of the Alaskan isolates suggested that they are evolutionarily constrained. This study establishes a baseline of genetic fingerprint patterns and sequence groups representing the genetic diversity of Alaskan IHNV isolates. This information could be used to determine the source of an IHN outbreak and to facilitate decisions in fisheries management of Alaskan salmonid stocks.

Diseases of Aquatic Organisms↗
USGS1987

Summer spawning in the fourhorn sculpin, Myoxocephalus quadricornis, from Alaska

Histological ovarian analysis indicates summer spawning occurs in Myoxocephalus quadricornis (Fourhorn Sculpin) from Alaska. Previous studies have shown this species spawns during winter in the Baltic Sea; the data presented herein suggests that geographical variation may occur in the timing of spawning of this species.

Alaska↗
USGS2009

Selected achievements, science directions, and new opportunities for the WEBB small watershed research program

Over nearly two decades, the Water, Energy, and Biogeochemical Budgets (WEBB) small watershed research program of the U.S. Geological Survey (USGS) has documented how water and solute fluxes, nutrient, carbon, and mercury dynamics, and weathering and sediment transport respond to natural and humancaused drivers, including climate, climate change, and atmospheric deposition. Together with a continued and increasing focus on the effects of climate change, more investigations are needed that examine ecological effects (e.g., evapotranspiration, nutrient uptake) and responses (e.g., species abundances, biodiversity) that are coupled with the physical and chemical processes historically observed in the WEBB program. Greater use of remote sensing, geographic modeling, and habitat/watershed modeling tools is needed, as is closer integration with the USGS-led National Phenology Network. Better understanding of process and system response times is needed. The analysis and observation of land-use and climate change effects over time should be improved by pooling data obtained by the WEBB program during the last two decades with data obtained earlier and (or) concurrently from other research and monitoring studies conducted at or near the five WEBB watershed sites. These data can be supplemented with historical and paleo-environmental information, such as could be obtained from tree rings and lake cores. Because of the relatively pristine nature and small size of its watersheds, the WEBB program could provide process understanding and basic data to better characterize and quantify ecosystem services and to develop and apply indicators of ecosystem health. In collaboration with other Federal and State watershed research programs, the WEBB program has an opportunity to contribute to tracking the short-term dynamics and long-term evolution of ecosystem services and health indicators at a multiplicity of scales across the landscape.

Conference Paper↗
USGS2000

Implementation strategy for production of National Land-Cover Data (NLCD) from the Landsat 7 Thematic Mapper satellite

As environmental programs within and outside the federal government continue to move away from point-based studies to larger and larger spatial (not cartographic) scale, the need for land-cover and other geographic data have become ineluctable. The national land-cover mapping project of MRLC marks the first consistently classified conterminous land-cover data set, effectively replacing USGS' Land Use Data Analysis (LUDA) system derived from high altitidue aerial photography acquired in the early 1970's. Because of the continually changing nature of the earth's surface due to anthropogenic activities and other factors, a single point-in-time land-cover product is insufficient for many applications. Production of a second point-in-time land-cover product is proposed as a database. That proposed database design includes: (1) second, independently classified land-cover data set derived from Landsat 7 Thematic Mapper data; (2) the land-cover product being produced under the current effort, (3) selected spectral-based change estimates (e.g., temporal NDVI), (4) thirty-meter DEMS; and (5) selected landscape metrics. Development of the database for the conterminous United States will start after evaluation of the prototype.

Technical Report↗
USGS2016

Community exposure to potential climate-driven changes to coastal-inundation hazards for six communities in Essex County, Massachusetts

Introduction Understanding if and how community exposure to coastal hazards may change over time is crucial information for coastal managers tasked with developing climate adaptation plans. This report summarizes estimates of population and asset exposure to coastal-inundation hazards associated with sea-level-rise and storm scenarios in six coastal communities of the Great Marsh region of Essex County, Massachusetts. This U.S. Geological Survey (USGS) analysis was conducted in collaboration with National Wildlife Federation (NWF) representatives, who are working with local stakeholders to develop local climate adaptation plans for the Towns of Salisbury, Newbury, Rowley, Ipswich, and Essex and the City of Newburyport (hereafter referred to as communities). Community exposure was characterized by integrating various community indicators (land cover and land use, population, economic assets, critical facilities, and infrastructure) with coastal-hazard zones that estimate inundation extents and water depth for three time periods. Estimates of community exposure are based on the presence of people, businesses, and assets in hazard zones that are calculated from geospatial datasets using geographic-information-system (GIS) tools. Results are based on current distributions of people and assets in hazard zones and do not take into account projections of human population, asset, or land-use changes over time. Results are not loss estimates based on engineering analysis or field surveys for any particular facility and do not take into account aspects of individual and household preparedness before an extreme event, adaptive capacity of a community during an event, or long-term resilience of individuals and communities after an event. Potential losses would match reported inventories only if all residents, business owners, public managers, and elected officials were unaware of what to do if warned of an imminent threat, failed to take protective measures during an extreme event, or failed to implement any long-term strategies to mitigate potential impacts. This analysis is intended to serve as a foundation for additional risk-related studies, plans, and mitigation efforts that are tailored to local needs. After a summary of the geospatial methods used in the analysis, results are organized by community so that local officials can easily use them in their local adaptation planning efforts.

Massachusetts↗
USGS2015

Developing a workflow to identify inconsistencies in volunteered geographic information: a phenological case study

Recent improvements in online information communication and mobile location-aware technologies have led to the production of large volumes of volunteered geographic information. Widespread, large-scale efforts by volunteers to collect data can inform and drive scientific advances in diverse fields, including ecology and climatology. Traditional workflows to check the quality of such volunteered information can be costly and time consuming as they heavily rely on human interventions. However, identifying factors that can influence data quality, such as inconsistency, is crucial when these data are used in modeling and decision-making frameworks. Recently developed workflows use simple statistical approaches that assume that the majority of the information is consistent. However, this assumption is not generalizable, and ignores underlying geographic and environmental contextual variability that may explain apparent inconsistencies. Here we describe an automated workflow to check inconsistency based on the availability of contextual environmental information for sampling locations. The workflow consists of three steps: (1) dimensionality reduction to facilitate further analysis and interpretation of results, (2) model-based clustering to group observations according to their contextual conditions, and (3) identification of inconsistent observations within each cluster. The workflow was applied to volunteered observations of flowering in common and cloned lilac plants ( Syringa vulgaris and Syringa x chinensis ) in the United States for the period 1980 to 2013. About 97% of the observations for both common and cloned lilacs were flagged as consistent, indicating that volunteers provided reliable information for this case study. Relative to the original dataset, the exclusion of inconsistent observations changed the apparent rate of change in lilac bloom dates by two days per decade, indicating the importance of inconsistency checking as a key step in data quality assessment for volunteered geographic information. Initiatives that leverage volunteered geographic information can adapt this workflow to improve the quality of their datasets and the robustness of their scientific analyses.

PLoS ONE↗
USGS2003

Raster dataset showing the probability of elevated concentrations of nitrate in ground water in Colorado, hydrogeomorphic regions and fertilizer use estimates included

This dataset is one of eight datasets produced by this study. Four of the datasets predict the probability of detecting atrazine and(or) desethyl-atrazine (a breakdown product of atrazine) in ground water in Colorado; the other four predict the probability of detecting elevated concentrations of nitrate in ground water in Colorado. The four datasets that predict the probability of atrazine and(or) desethyl-atrazine (atrazine/DEA) are differentiated by whether or not they incorporated atrazine use and whether or not they incorporated hydrogeomorphic regions. The four datasets that predict the probability of elevated concentrations of nitrate are differentiated by whether or not they incorporated fertilizer use and whether or not they incorporated hydrogeomorphic regions. Each of the eight datasets has its own unique strengths and weaknesses. The user is cautioned to read Rupert (2003, Probability of detecting atrazine/desethyl-atrazine and elevated concentrations of nitrate in ground water in Colorado: U.S. Geological Survey Water-Resources Investigations Report 02-4269, 35 p., http://water.usgs.gov/pubs/wri/wri02-4269/) to determine if he(she) is using the most appropriate dataset for his(her) particular needs. This dataset specifically predicts the probability of detecting elevated concentrations of nitrate in ground water in Colorado with hydrogeomorphic regions and fertilizer use included. The following text was extracted from Rupert (2003). Draft Federal regulations may require that each State develop a State Pesticide Management Plan for the herbicides atrazine, alachlor, metolachlor, and simazine. Maps were developed that the State of Colorado could use to predict the probability of detecting atrazine/DEA in ground water in Colorado. These maps can be incorporated into the State Pesticide Management Plan and can help provide a sound hydrogeologic basis for atrazine management in Colorado. Maps showing the probability of detecting elevated nitrite plus nitrate as nitrogen (nitrate) concentrations in ground water in Colorado also were developed because nitrate is a contaminant of concern in many areas of Colorado. Maps showing the probability of detecting atrazine/DEA at or greater than concentrations of 0.1 microgram per liter and nitrate concentrations in ground water greater than 5 milligrams per liter were developed as follows: (1) Ground-water quality data were overlaid with anthropogenic and hydrogeologic data by using a geographic information system (GIS) to produce a dataset in which each well had corresponding data on atrazine use, fertilizer use, geology, hydrogeomorphic regions, land cover, precipitation, soils, and well construction. These data then were downloaded to a statistical software package for analysis by logistic regression. (2) Relations were observed between ground-water quality and the percentage of land-cover categories within circular regions (buffers) around wells. Several buffer sizes were evaluated; the buffer size that provided the strongest relation was selected for use in the logistic regression models. (3) Relations between concentrations of atrazine/DEA and nitrate in ground water and atrazine use, fertilizer use, geology, hydrogeomorphic regions, land cover, precipitation, soils, and well-construction data were evaluated, and several preliminary multivariate models with various combinations of independent variables were constructed. (4) The multivariate models that best predicted the presence of atrazine/DEA and elevated concentrations of nitrate in ground water were selected. (5) The accuracy of the multivariate models was confirmed by validating the models with an independent set of ground-water quality data. (6) The multivariate models were entered into a geographic information system and the probability GRIDS were constructed.

Open-File Report↗