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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 235 records · Page 13Linked to original sources
USGS1998

Use of a ground-water flow model with particle tracking to evaluate ground-water vulnerability, Clark County, Washington

A ground-water flow model was used in conjunction with a particle-tracking program to demonstrate a method of evaluating ground-water vulnerability. The study area encompassed the part of the Portland Basin located in Clark County, Washington. A new computer program was developed that interfaces the particle-tracking program with a geographic information system (GIS). The GIS was used to display and analyze the particle-tracking results and to evaluate ground-water vulnerability by identifying recharge areas and their characteristics, determining the downgradient impact of land use at recharge areas, and estimating the age of ground water. The report presents a description of the methods used and the results of the evaluation of ground-water vulnerability.

Washington↗
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↗
USGS2000

Assessing land-use impacts on biodiversity using an expert systems tool

Habitat alteration, in the form of land-use development, is a leading cause of biodiversity loss in the U.S. and elsewhere. Although statutes in the U.S. may require consideration of biodiversity in local land-use planning and regulation, local governments lack the data, resources, and expertise to routinely consider biotic impacts that result from permitted land uses. We hypothesized that decision support systems could aid solution of this problem. We developed a pilot biodiversity expert systems tool (BEST) to test that hypothesis and learn what additional scientific and technological advancements are required for broad implementation of such a system. BEST uses data from the U.S. Geological Survey's Gap Analysis Program (GAP) and other data in a desktop GIS environment. The system provides predictions of conflict between proposed land uses and biotic elements and is intended for use at the start of the development review process. Key challenges were the development of categorization systems that relate named land-use types to ecological impacts, and relate sensitivities of biota to ecological impact levels. Although the advent of GAP and sophisticated desktop GIS make such a system feasible for broad implementation, considerable ongoing research is required to make the results of such a system scientifically sound, informative, and reliable for the regulatory process. We define a role for local government involvement in biodiversity impact assessment, the need for a biodiversity decision support system, the development of a prototype system, and scientific needs for broad implementation of a robust and reliable system.

Landscape Ecology↗
USGS1987

GEOGRAPHIC ESTIMATION OF RUNOFF-MODEL PARAMETERS.

The U. S. Geological Survey is developing techniques to estimate and evaluate unit-hydrograph and loss-rate parameter values for rainfall-runoff models using Geographic Information System (GIS) procedures. The data base includes basin, soil, and climatological characteristics that will be stored in a GIS, and unit-hydrograph and loss-rate parameters obtained from calibration of a commonly used flood-hydrograph rainfall-runoff model for 616 storms in 98 gaged drainage basins. Development of unit-hydrograph and loss-rate parameter-estimation techniques includes statistical methods (exploratory data analysis, regression analysis, and categorical data analysis) to relate the model parameters to hydrologic characteristics. The estimation techniques are evaluated by use of error analysis of simulated hydrograph characteristics (peak discharge, flood volume, and time to peak discharge). The hydrographs will be simulated with parameters estimated by the techniques for (1) 102 storms occurring at 36 gaged basins; and (2) a large storm system (one which produced floods with a 50-to 100-year recurrence interval).

Conference Paper↗
USGS2018

Species distribution modeling in regions of high need and limited data: waterfowl of China

Background A number of conservation and societal issues require understanding how species are distributed on the landscape, yet ecologists are often faced with a lack of data to develop models at the resolution and extent desired, resulting in inefficient use of conservation resources. Such a situation presented itself in our attempt to develop waterfowl distribution models as part of a multi-disciplinary team targeting the control of the highly pathogenic H5N1 avian influenza virus in China. Methods Faced with limited data, we built species distribution models using a habitat suitability approach for China’s breeding and non-breeding (hereafter, wintering) waterfowl. An extensive review of the literature was used to determine model parameters for habitat modeling. Habitat relationships were implemented in GIS using land cover covariates. Wintering models were validated using waterfowl census data, while breeding models, though developed for many species, were only validated for the one species with sufficient telemetry data available. Results We developed suitability models for 42 waterfowl species (30 breeding and 39 wintering) at 1 km resolution for the extent of China, along with cumulative and genus level species richness maps. Breeding season models showed highest waterfowl suitability in wetlands of the high-elevation west-central plateau and northeastern China. Wintering waterfowl suitability was highest in the lowland regions of southeastern China. Validation measures indicated strong performance in predicting species presence. Comparing our model outputs to China’s protected areas indicated that breeding habitat was generally better covered than wintering habitat, and identified locations for which additional research and protection should be prioritized. Conclusions These suitability models are the first available for many of China’s waterfowl species, and have direct utility to conservation and habitat planning and prioritizing management of critically important areas, providing an example of how this approach may aid others faced with the challenge of addressing conservation issues with little data to inform decision making.

Avian Research↗
USGS1998

A female black bear denning habitat model using a geographic information system

We used the Mahalanobis distance statistic and a raster geographic information system (GIS) to model potential black bear ( Ursus americanus ) denning habitat in the Ouachita Mountains of Arkansas. The Mahalanobis distance statistic was used to represent the standard squared distance between sample variates in the GIS database (forest cover type, elevation, slope, aspect, distance to streams, distance to roads, and forest cover richness) and variates at known bear dens. Two models were developed: a generalized model for all den locations and another specific to dens in rock cavities. Differences between habitat at den sites and habitat across the study area were represented in 2 new GIS themes as Mahalanobis distance values. Cells similar to the mean vector derived from the known dens had low Mahalanobis distance values, and dissimilar cells had high values. The reliability of the predictive model was tested by overlaying den locations collected subsequent to original model development on the resultant den habitat themes. Although the generalized model demonstrated poor reliability, the model specific to rock dens had good reliability. Bears were more likely to choose rock den locations with low Mahalanobis distance values and less likely to choose those with high values. The model can be used to plan the timing and extent of management actions (e.g., road building, prescribed fire, timber harvest) most appropriate for those sites with high or low denning potential.

Arkansas↗
USGS2000

Probability of detecting atrazine/desethyl-atrazine and elevated concentrations of nitrate plus nitrate as nitrogen in ground water in the Idaho part of the western Snake River Plain

As ground water continues to provide an ever-growing proportion of Idaho?s drinking water, concerns about the quality of that resource are increasing. Pesticides (most commonly, atrazine/desethyl-atrazine, hereafter referred to as atrazine) and nitrite plus nitrate as nitrogen (hereafter referred to as nitrate) have been detected in many aquifers in the State. To provide a sound hydrogeologic basis for atrazine and nitrate management in southern Idaho—the largest region of land and water use in the State—the U.S. Geological Survey produced maps showing the probability of detecting these contaminants in ground water in the upper Snake River Basin (published in a 1998 report) and the western Snake River Plain (published in this report). The atrazine probability map for the western Snake River Plain was constructed by overlaying ground-water quality data with hydrogeologic and anthropogenic data in a geographic information system (GIS). A data set was produced in which each well had corresponding information on land use, geology, precipitation, soil characteristics, regional depth to ground water, well depth, water level, and atrazine use. These data were analyzed by logistic regression using a statistical software package. Several preliminary multivariate models were developed and those that best predicted the detection of atrazine were selected. The multivariate models then were entered into a GIS and the probability maps were produced. Land use, precipitation, soil hydrologic group, and well depth were significantly correlated with atrazine detections in the western Snake River Plain. These variables also were important in the 1998 probability study of the upper Snake River Basin. The effectiveness of the probability models for atrazine might be improved if more detailed data were available for atrazine application. A preliminary atrazine probability map for the entire Snake River Plain in Idaho, based on a data set representing that region, also was produced. In areas where this map overlaps the 1998 map of the upper Snake River Basin, the two maps show broadly similar probabilities of detecting atrazine. Logistic regression also was used to develop a preliminary statistical model that predicts the probability of detecting elevated nitrate in the western Snake River Plain. A nitrate probability map was produced from this model. Results showed that elevated nitrate concentrations were correlated with land use, soil organic content, well depth, and water level. Detailed information on nitrate input, specifically fertilizer application, might have improved the effectiveness of this model.

Idaho↗
USGS2007

Probabilistic prediction models for aggregate quarry siting

Weights-of-evidence (WofE) and logistic regression techniques were used in a GIS framework to predict the spatial likelihood (prospectivity) of crushed-stone aggregate quarry development. The joint conditional probability models, based on geology, transportation network, and population density variables, were defined using quarry location and time of development data for the New England States, North Carolina, and South Carolina, USA. The Quarry Operation models describe the distribution of active aggregate quarries, independent of the date of opening. The New Quarry models describe the distribution of aggregate quarries when they open. Because of the small number of new quarries developed in the study areas during the last decade, independent New Quarry models have low parameter estimate reliability. The performance of parameter estimates derived for Quarry Operation models, defined by a larger number of active quarries in the study areas, were tested and evaluated to predict the spatial likelihood of new quarry development. Population density conditions at the time of new quarry development were used to modify the population density variable in the Quarry Operation models to apply to new quarry development sites. The Quarry Operation parameters derived for the New England study area, Carolina study area, and the combined New England and Carolina study areas were all similar in magnitude and relative strength. The Quarry Operation model parameters, using the modified population density variables, were found to be a good predictor of new quarry locations. Both the aggregate industry and the land management community can use the model approach to target areas for more detailed site evaluation for quarry location. The models can be revised easily to reflect actual or anticipated changes in transportation and population features. ?? International Association for Mathematical Geology 2007.

Natural Resources Research↗
USGS2015

Predicting locations of post-fire debris-flow erosionin the San Gabriel Mountains of southern California

Timely hazard assessments are needed to assess post-fire debris flows that may impact communities located within and adjacent to recently burned areas. Implementing existing models for debris-flow probability and magnitude can be time-consuming because the geographic extent for applying the models is manually defined. In this study, a model is presented for predicting locations of post-fire debris-flow erosion. This model is further calibrated to identify the geographic extent for applying post-fire hazard assessment models. Aerial photographs were used to map locations of post-fire debris-flow erosion and deposition in the San Gabriel Mountains. Terrain, burn severity, and soil characteristics expected to influence debris-flow erosion and deposition were calculated for each mapped location using 10-m resolution DEMs, GIS data for burn severity, and soil surveys. Multiple logistic regression was used to develop a model that predicts the probability of erosion as a function of channel slope, planform curvature, and the length of the longest upstream flow path. The model was validated using an independent database of mapped locations of debris-flow erosion and deposition and found to make accurate and precise predictions. The model was further calibrated by identifying the average percentage of the drainage network classified as erosion for mapped locations where debris flows transitioned from eroding to depositing material. The calibrated model provides critical information for consistent and timely application of post-fire debris-flow hazard assessment models and the ability to identify locations of post-fire debris-flow erosion.

California↗
USGS2022

Social Values for Ecosystem Services (SolVES): Open-source spatial modeling of cultural services

Social Values for Ecosystem Services (SolVES) version 4.0 is a fully open-source, GIS-based tool designed to aid in the creation of quantitative, spatially explicit models of the nonmonetary values attributed to cultural ecosystem services, such as aesthetics and recreation, specifically to facilitate their incorporation into larger ecosystem service assessments. Newly redeveloped for QGIS, SolVES can be applied in a wide variety of biophysical and social contexts including mountain, forest, coastal, riparian, agricultural, and urban settings worldwide. Redeveloping SolVES for an open-source platform was intended to expand its user base by eliminating the cost of proprietary GIS software licenses and to remove the impact of proprietary software changes on SolVES development. Providing additional options would enable users to delineate relevant stakeholder groups to better assess how differing preferences impact the intensity and spatial distribution of perceived social values.

Environmental Modelling & Software↗
USGS2011

Bounding species distribution models

Species distribution models are increasing in popularity for mapping suitable habitat for species of management concern. Many investigators now recognize that extrapolations of these models with geographic information systems (GIS) might be sensitive to the environmental bounds of the data used in their development, yet there is no recommended best practice for “clamping” model extrapolations. We relied on two commonly used modeling approaches: classification and regression tree (CART) and maximum entropy (Maxent) models, and we tested a simple alteration of the model extrapolations, bounding extrapolations to the maximum and minimum values of primary environmental predictors, to provide a more realistic map of suitable habitat of hybridized Africanized honey bees in the southwestern United States. Findings suggest that multiple models of bounding, and the most conservative bounding of species distribution models, like those presented here, should probably replace the unbounded or loosely bounded techniques currently used.

Current Zoology↗
USGS2007

Latin hypercube approach to estimate uncertainty in ground water vulnerability

A methodology is proposed to quantify prediction uncertainty associated with ground water vulnerability models that were developed through an approach that coupled multivariate logistic regression with a geographic information system (GIS). This method uses Latin hypercube sampling (LHS) to illustrate the propagation of input error and estimate uncertainty associated with the logistic regression predictions of ground water vulnerability. Central to the proposed method is the assumption that prediction uncertainty in ground water vulnerability models is a function of input error propagation from uncertainty in the estimated logistic regression model coefficients (model error) and the values of explanatory variables represented in the GIS (data error). Input probability distributions that represent both model and data error sources of uncertainty were simultaneously sampled using a Latin hypercube approach with logistic regression calculations of probability of elevated nonpoint source contaminants in ground water. The resulting probability distribution represents the prediction intervals and associated uncertainty of the ground water vulnerability predictions. The method is illustrated through a ground water vulnerability assessment of the High Plains regional aquifer. Results of the LHS simulations reveal significant prediction uncertainties that vary spatially across the regional aquifer. Additionally, the proposed method enables a spatial deconstruction of the prediction uncertainty that can lead to improved prediction of ground water vulnerability. ?? 2007 National Ground Water Association.

Ground Water↗
USGS1997

Proceedings of a workshop on digital mapping techniques; methods for geologic map data capture, management, and publication - June 2 - 5, 1997, Lawrence, Kansas

Introduction: From June 2-5, 1997, selected technical representatives of the USGS and State geological surveys participated in the 'AASG/USGS Digital Mapping Techniques' workshop in Lawrence, Kansas. The workshop was initiated by the AASG/USGS Data Capture Working Group, and was hosted by the Kansas Geological Survey (KGS). With a focus on methods for data capture and digital map production, the goal was to help move the state surveys and the USGS toward development of more cost-effective, flexible, and useful systems for digital mapping and GIS analysis.

Open-File Report↗
USGS2009

Groundwater availability of the Central Valley Aquifer, California

California's Central Valley covers about 20,000 square miles and is one of the most productive agricultural regions in the world. More than 250 different crops are grown in the Central Valley with an estimated value of $17 billion per year. This irrigated agriculture relies heavily on surface-water diversions and groundwater pumpage. Approximately one-sixth of the Nation's irrigated land is in the Central Valley, and about one-fifth of the Nation's groundwater demand is supplied from its aquifers. The Central Valley also is rapidly becoming an important area for California's expanding urban population. Since 1980, the population of the Central Valley has nearly doubled from 2 million to 3.8 million people. The Census Bureau projects that the Central Valley's population will increase to 6 million people by 2020. This surge in population has increased the competition for water resources within the Central Valley and statewide, which likely will be exacerbated by anticipated reductions in deliveries of Colorado River water to southern California. In response to this competition for water, a number of water-related issues have gained prominence: conservation of agricultural land, conjunctive use, artificial recharge, hydrologic implications of land-use change, and effects of climate variability. To provide information to stakeholders addressing these issues, the USGS Groundwater Resources Program made a detailed assessment of groundwater availability of the Central Valley aquifer system, that includes: (1) the present status of groundwater resources; (2) how these resources have changed over time; and (3) tools to assess system responses to stresses from future human uses and climate variability and change. This effort builds on previous investigations, such as the USGS Central Valley Regional Aquifer System and Analysis (CV-RASA) project and several other groundwater studies in the Valley completed by Federal, State and local agencies at differing scales. The principal product of this new assessment is a tool referred to as the Central Valley Hydrologic Model (CVHM) that accounts for integrated, variable water supply and demand, and simulates surface-water and groundwater-flow across the entire Central Valley system. The development of the CVHM comprised four major elements: (1) a comprehensive Geographic Information System (GIS) to compile, analyze and visualize data; (2) a texture model to characterize the aquifer system;(3) estimates of water-budget components by numerically modeling the hydrologic system with the Farm Process (FMP); and (4) simulations to assess and quantify hydrologic conditions.

Professional Paper↗
USGS1991

Institutional issues affecting the integration and use of remotely sensed data and geographic information systems

The developers as well as the users of remotely sensed data and geographic information system (GIS) techniques are associated with nearly all types of institutions in government, industry, and academia. Individuals in these various institutions often find the barriers to accepting remote sensing and GIS are not necessarily technical in nature, but can be attributed to the institutions themselves. Several major institutional issues that affect the technologies of remote sensing and GIS are data availability, data marketing and costs, equipment availability and costs, standards and practices, education and training, and organizational infrastructures. Not only are problems associated with these issues identified, but needs and opportunities also are discussed. -from Authors

Photogrammetric Engineering and Remote Sensing↗
USGS2019

A comparison of hydrocarbon-related landscape disturbance patterns along the New York-Pennsylvania border, 2004–2013

Executive Summary The New York-Pennsylvania area has a long history of hydrocarbon extraction, and the addition of shale gas extraction methods contributes to landscape disturbance borne by previously developed oil and non-shale gas resources. The main unconventional extraction method used to extract shale gas from the Marcellus Shale located in New York and Pennsylvania is hydraulic fracturing, or “fracking,” although other conventional methods are used extensively. All forms of hydrocarbon extraction disturb the surrounding landscape to some extent, primarily in the form of land clearance and degradation, road construction, and pipeline development, although the effects of these disturbances are not fully understood. In this study, landscape-change metrics and indicators are used to analyze change in a 10-county region along the New York-Pennsylvania border—the New York counties of Allegany, Steuben, Chemung, Tioga, and Broome, and the Pennsylvania counties of McKean, Potter, Tioga, Bradford, and Susquehanna. This 10-county region was selected due to the differences in policies between the States of New York and Pennsylvania. While fracking occurred extensively in Pennsylvania over the past 10 years or more, the State of New York issued a temporary moratorium against hydraulic fracturing in 2010—citing repercussions that might affect air quality, water quality, and public health—and officially banned hydraulic fracturing in June 2015. The quantification of landscape disturbance due to hydrocarbon extraction activities is presented in this report as land-use and land-cover (LULC) change between 2004 and 2013 and defined using specific disturbance categories (including well sites, roads, and pipelines) to compare the disturbances and changes, by county, on both sides of the New York-Pennsylvania border. The quantification was accomplished by gathering the signatures of disturbance from high-resolution aerial images, comparing the derived totals of disturbance, and then computing landscape metrics in a geographic information system (GIS) environment. The collected data represent a summation of landscape disturbance from oil and gas development, as some of the data represented were established decades earlier. The Analytical Tools Interface for Landscape Assessments (ATtILA) software was used to calculate land-cover area and landscape metrics for each shale gas, non-shale gas, oil, and other infrastructure types associated with hydrocarbons across each county and both five-county regions in the study area. The three primary metrics used to describe changes in forest structure were (1)forest area, (2) interior forest area, and (3) forest edge area. The changes in metrics were subsequently evaluated using the Pearson correlation coefficient. Overall, the disturbed-area footprint in the Pennsylvania region is considerably larger than the disturbed-area footprint in the New York region (13,687.9 hectares [ha] in Pennsylvania; 3,840.5 ha in New York). Disturbance per site is similar, with 1.2 disturbed ha per site in New York and 1.6 disturbed ha per site in Pennsylvania. In the New York-Pennsylvania 10-county region, hydrocarbon-development and extraction disturbance strongly correlate with a reduction in the percentage of forest for the entire region. This observation also appears to be true in the New York five-county region for forest area. This form of disturbance in the New York five-county region shows significantly correlated changes in forest metrics (–0.4 percent total forest area), particularly in the percentage of interior forest (–1.2 percent total area) and forest edge (+0.7 percent total area). On the other hand, gas and hydrocarbon-development and extraction disturbance (1.0 percent total area) in the Pennsylvania five-county region strongly correlates with a total decline in forest area and agricultural land area (–0.8 percent combined total area) but not with either land-cover class separately.

New York, Pennsylvania↗
USGS2013

Mitigating the effects of landscape development on streams in urbanizing watersheds

This collaborative study examined urbanization and impacts on area streams while using the best available sediment and erosion control (S&EC) practices in developing watersheds in Maryland, United States. During conversion of the agricultural and forested watersheds to urban land use, land surface topography was graded and vegetation was removed creating a high potential for sediment generation and release during storm events. The currently best available S&EC facilities were used during the development process to mitigate storm runoff water quality, quantity, and timing before entering area streams. Detailed Geographic Information System (GIS) maps were created to visualize changing land use and S&EC practices, five temporal collections of LiDAR (light detection and ranging) imagery were used to map the changing landscape topography, and streamflow, physical geomorphology, and habitat data were used to assess the ability of the S&EC facilities to protect receiving streams during development. Despite the use of the best available S&EC facilities, receiving streams experienced altered flow, geomorphology, and decreased biotic community health. These impacts on small streams during watershed development affect sediment and nutrient loads to larger downstream aquatic ecosystems such as the Chesapeake Bay.

Maryl↗
USGS2013

Current status, issues and applications of GIS to inland fisheries

This chapter is concerned with GIS applications made to inland fisheries. These include fisheries in freshwater rivers, lakes and reservoirs. Although these GIS applications have increased rapidly since the late 1980s, this area of fish production receives less attention than either aquaculture or marine fisheries. This is probably because inland fisheries are often practised in remote areas, at a semi-subsistence level, or are recreational in many developed countries, and data on most aspects of the fisheries are scattered, fragmented and frequently unsuited for use as inputs to GIS. The GIS-based inland fisheries work has concentrated on mapping the distribution and abundance of fish species and mapping and modelling habitats in rivers, reservoirs and lakes, and relating the two. Much of the material included in the chapter on inland fisheries comes from either Fisher and Rahel (2004) or from the series of symposium proceedings published by the Fishery-Aquatic GIS Research Group (Nishida and Caton, 2010).

Book chapter↗