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At least 145 records · Page 8Linked to original sources

Use of a spatial decision support system for analysis of habitat use by wintering northern pintails

A multi-functional spatial decision support system (SDSS) was,developed at the spatial analysis branch Of the National Wetlands Research Center, and the wildlife analysis module of the system was used to study habitat use by wintering pintail. We instrumented female pintails at Catahoula Lake, Louisiana, in October of 1992-94 and located the instrumented birds weekly through the following March. Using the SDSS developed in an ARC/INFO geographical information system (GIS) - environment. We were able to visualize movements of instrumented pintails over varied environmental conditions and landscape features to determine habitat use. Weather data were used to determine factors important in the timing of movements. The analyses indicated that female pintails dispersed from Catahoula Lake, Louisiana, in three general patterns, based upon wetland conditions. Timing of movements coincided with periods of precipitation or disturbance, primarily hunting. Pintails which arrived at Catahoula Lake in October and November remained in the agricultural areas of Louisiana and Arkansas, with very limited movements to the coastal marshes or westward into the agricultural areas of Texas. Northward movements into Arkansas occurred whenever there was substantial rainfall in the agricultural regions, and northward movements generally stopped at the frost-line. No differences in adult or juvenile female movement patterns were apparent.

Louisiana

Book review: Spatial capture-recapture

Understanding how animals use space is a vital aspect of conservation planning and wildlife management. Technological developments (e.g., increased computer power and desktop geographic information system [GIS] applications) are bringing the ability to analyze spatial data sets to the individual biologist. Therefore, it is not surprising that methodologies have been developed to incorporate space into capture-recapture models, which are some of the most fundamental models in the field of wildlife ecology. Spatial Capture-Recapture (hereafter SCR) is a timely and informative contribution that summarizes the history and motivation behind SCR models, in addition to providing details of the methodological framework that allows the reader to develop and customize SCR models to address their own ecological questions. Review info: Spatial Capture-Recapture. By J. Andrew Royle, Richard B. Chandler, Rahel Sollmann, and Beth Gardner, 2014. ISBN: 978-0124059399, 577 pp.

Journal of Wildlife Management

Limitations to mapping habitat use areas in changing landscapes using the Mahalanobis distance statistic

We tested the potential of a GIS mapping technique, using a resource selection model developed for black-tailed jackrabbits (Lepus californicus) and based on the Mahalanobis distance statistic, to track changes in shrubsteppe habitats in southwestern Idaho. If successful, the technique could be used to predict animal use areas, or those undergoing change, in different regions from the same selection function and variables without additional sampling. We determined the multivariate mean vector of 7 GIS variables that described habitats used by jackrabbits. We then ranked the similarity of all cells in the GIS coverage from their Mahalanobis distance to the mean habitat vector. The resulting map accurately depicted areas where we sighted jackrabbits on verification surveys. We then simulated an increase in shrublands (which are important habitats). Contrary to expectation, the new configurations were classified as lower similarity relative to the original mean habitat vector. Because the selection function is based on a unimodal mean, any deviation, even if biologically positive, creates larger Malanobis distances and lower similarity values. We recommend the Mahalanobis distance technique for mapping animal use areas when animals are distributed optimally, the landscape is well-sampled to determine the mean habitat vector, and distributions of the habitat variables does not change.

Journal of Agricultural, Biological, and Environme

Knowledge-based geographic information systems (KBGIS): New analytic and data management tools

In its simplest form, a geographic information system (GIS) may be viewed as a data base management system in which most of the data are spatially indexed, and upon which sets of procedures operate to answer queries about spatial entities represented in the data base. Utilization of artificial intelligence (AI) techniques can enhance greatly the capabilities of a GIS, particularly in handling very large, diverse data bases involved in the earth sciences. A KBGIS has been developed by the U.S. Geological Survey which incorporates AI techniques such as learning, expert systems, new data representation, and more. The system, which will be developed further and applied, is a prototype of the next generation of GIS's, an intelligent GIS, as well as an example of a general-purpose intelligent data handling system. The paper provides a description of KBGIS and its application, as well as the AI techniques involved. ?? 1988 International Association for Mathematical Geology.

Mathematical Geology

Mapping development preferences on the perceived value of ecosystem services and land use conflict and compatibility in Greater Kuala Lumpur

Rapid and unplanned development can diminish the social values for ecosystem services associated with urban landscapes. Tropical Global South cities, such as Greater Kuala Lumpur (GKL), Malaysia, that are highly biodiverse, are particularly vulnerable to the fragmentation and loss of natural ecosystems. This study investigates the social values for ecosystem services in GKL, a rapidly urbanising metropolitan area in Southeast Asia and presents the novel application of the SolVES ( Social Values for Ecosystem Services ) tool to an urban area. A public participatory GIS (PPGIS) survey was conducted to assess residents’ development preferences and perceived distribution of social values. The study revealed two groups of respondents, using cluster analysis, each with unique development preferences - a group favouring both green and grey developments and another favouring green development but strongly opposing grey development. The two groups differed statistically in their sociodemographic characteristics, and also how they mapped different social values. Our spatial analysis of their preferences towards future urban expansion in GKL highlighted locations where there is potential for land-use conflict. For example, the favour-balanced-development group tended to value built areas over green spaces. These findings support the need to consider residents’ preferences and socioecological traits through greater public engagement in urban landscape management.

Greater Kuala Lumpur

Large-scale control site selection for population monitoring: an example assessing Sage-grouse trends

Human impacts on wildlife populations are widespread and prolific and understanding wildlife responses to human impacts is a fundamental component of wildlife management. The first step to understanding wildlife responses is the documentation of changes in wildlife population parameters, such as population size. Meaningful assessment of population changes in potentially impacted sites requires the establishment of monitoring at similar, nonimpacted, control sites. However, it is often difficult to identify appropriate control sites in wildlife populations. We demonstrated use of Geographic Information System (GIS) data across large spatial scales to select biologically relevant control sites for population monitoring. Greater sage-grouse (Centrocercus urophasianus; hearafter, sage-grouse) are negatively affected by energy development, and monitoring of sage-grouse population within energy development areas is necessary to detect population-level responses. Weused population data (1995–2012) from an energy development area in Wyoming, USA, the Atlantic Rim Project Area (ARPA), and GIS data to identify control sites that were not impacted by energy development for population monitoring. Control sites were surrounded by similar habitat and were within similar climate areas to the ARPA. We developed nonlinear trend models for both the ARPA and control sites and compared long-term trends from the 2 areas. We found little difference between the ARPA and control sites trends over time. This research demonstrated an approach for control site selection across large landscapes and can be used as a template for similar impact-monitoring studies. It is important to note that identification of changes in population parameters between control and treatment sites is only the first step in understanding the mechanisms that underlie those changes. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Wyoming

Depth to water in the western Snake River Plain and surrounding tributary valleys, southwestern Idaho and eastern Oregon, calculated using water levels from 1980 to 1988

The vulnerability of ground water to contamination in Idaho is being assessed by the ISHW/DEQ (Idaho Department of Health and Welfare, Division of Environmental Quality), using a modified version of the Environmental Protection Agency DRASTIC methods (Allers and others, 1985). The project was designed as a technique to: (1) Assign priorities for development of ground-water management and monitoring programs; (2) build support for, and public awareness of, vulnerability of ground water to contamination; (3) assist in the development of regulatory programs; and (4) provide access to technical data through the use of a GIS (geographic information system) (C. Grantham, Idaho Department of Health and Welfare, written commun., 1989). Digital representation of first-encountered water below land surface is an important element in evaluating vulnerability of ground water to contamination. Depth-to-water values were developed using existing data and computer software to construct a GIS data set to be combined with a soils data set developed by the SCS (Soul Conservation Service) and the IDHW/WQB (Idaho Department of Health and Welfare/Water Quality Bureau), and a recharge data set developed by the IDWR/RSF (idaho Department of Water Resources/Remote Sensing Facility). The USGS (U.S. Geological Survey) has developed digital depth-to-water values for eleven 1:100,00-scale quadrangles on the eastern Snake River Plain and surrounding tributary valleys.

Idaho

Tidal wetlands of the Yaquina and Alsea River estuaries, Oregon: Geographic Information Systems layer development and recommendations for National Wetlands Inventory revisions

Geographic Information Systems (GIS) layers of current, and likely former, tidal wetlands in two Oregon estuaries were generated by enhancing the 2010 National Wetlands Inventory (NWI) data with expert local field knowledge, Light Detection and Ranging-derived elevations, and 2009 aerial orthophotographs. Data were generated for two purposes: First, to enhance the NWI by recommending revised Cowardin classifications for certain NWI wetlands within the study area; and second, to generate GIS data for the 1999 Yaquina and Alsea River Basins Estuarine Wetland Site Prioritization study. Two sets of GIS products were generated: (1) enhanced NWI shapefiles; and (2) shapefiles of prioritization sites. The enhanced NWI shapefiles contain recommended changes to the Cowardin classification (system, subsystem, class, and/or modifiers) for 286 NWI polygons in the Yaquina estuary (1,133 acres) and 83 NWI polygons in the Alsea estuary (322 acres). These enhanced NWI shapefiles also identify likely former tidal wetlands that are classified as upland in the current NWI (64 NWI polygons totaling 441 acres in the Yaquina estuary; 16 NWI polygons totaling 51 acres in the Alsea estuary). The former tidal wetlands were identified to assist strategic planning for tidal wetland restoration. Cowardin classifications for the former tidal wetlands were not provided, because their current hydrology is complex owing to dikes, tide gates, and drainage ditches. The scope of this project did not include the field evaluation that would be needed to determine whether the former tidal wetlands are currently wetlands, and if so, determine their correct Cowardin classification. The prioritization site shapefiles contain 49 prioritization sites totaling 2,177 acres in the Yaquina estuary, and 39 prioritization sites totaling 1,045 acres in the Alsea estuary. The prioritization sites include current and former (for example, diked) tidal wetlands, and provide landscape units appropriate for basin-scale wetland restoration and conservation action planning. Several new prioritization sites (not included in the 1999 prioritization) were identified in each estuary, consisting of NWI polygons formerly classified as nontidal wetland or upland. The GIS products of this project improve the accuracy and utility of the NWI data, and provide useful tools for estuarine resource management.

Oregon

The Maryland Coastal Plain Aquifer Information System: A GIS-based tool for assessing groundwater resources

Groundwater is the source of drinking water for ∼1.4 million people in the Coastal Plain Province of Maryland (USA). In addition, groundwater is essential for commercial, industrial, and agricultural uses. Approximately 0.757 × 109 L d –1 (200 million gallons/d) were withdrawn in 2010. As a result of decades of withdrawals from the coastal plain confined aquifers, groundwater levels have declined by as much as 70 m (230 ft) from estimated prepumping levels. Other issues posing challenges to long-term groundwater sustainability include degraded water quality from both man-made and natural sources, reduced stream base flow, land subsidence, and changing recharge patterns (drought) caused by climate change. In Maryland, groundwater supply is managed primarily by the Maryland Department of the Environment, which seeks to balance reasonable use of the resource with long-term sustainability. The chief goal of groundwater management in Maryland is to ensure safe and adequate supplies for all current and future users through the implementation of appropriate usage, planning, and conservation policies. To assist in that effort, the geographic information system (GIS)–based Maryland Coastal Plain Aquifer Information System was developed as a tool to help water managers access and visualize groundwater data for use in the evaluation of groundwater allocation and use permits. The system, contained within an ESRI ArcMap desktop environment, includes both interpreted and basic data for 16 aquifers and 14 confining units. Data map layers include aquifer and ­confining unit layer surfaces, aquifer extents, borehole information, hydraulic properties, time-series groundwater-level data, well records, and geophysical and lithologic logs. The aquifer and confining unit layer surfaces were generated specifically for the GIS system. The system also contains select groundwater-quality data and map layers that quantify groundwater and surface-water withdrawals. The aquifer information system can serve as a pre- and postprocessing environment for groundwater-flow models for use in water-supply planning, development, and management. The system also can be expanded to include features that evaluate constraints to groundwater development, such as insufficient available drawdown, degraded groundwater quality, insufficient aquifer yields, and well-field interference. Ultimately, the aquifer information system is intended to function as an interactive Web-based utility that provides a broad array of information related to groundwater resources in Maryland’s coastal plain to a wide-ranging audience, including well drillers, consultants, academia, and the general public.

Special Paper of the Geological Society of America

Onondaga Lake Watershed – A Geographic Information System Project Phase I – Needs assessment and spatial data framework

In the fall of 2002, the Onondaga Lake Partnership (OLP) formed a Geographic Information System (GIS) Planning Committee to begin the process of developing a comprehensive watershed geographic information system for Onondaga Lake. The goal of the Onondaga Lake Partnership geographic information system is to integrate the various types of spatial data used for scientific investigations, resource management, and planning and design of improvement projects in the Onondaga Lake Watershed. A needs-assessment survey was conducted and a spatial data framework developed to support the Onondaga Lake Partnership use of geographic information system technology. The design focused on the collection, management, and distribution of spatial data, maps, and internet mapping applications. A geographic information system library of over 100 spatial datasets and metadata links was assembled on the basis of the results of the needs assessment survey. Implementation options were presented, and the Geographic Information System Planning Committee offered recommendations for the management and distribution of spatial data belonging to Onondaga Lake Partnership members. The Onondaga Lake Partnership now has a strong foundation for building a comprehensive geographic information system for the Onondaga Lake watershed. The successful implementation of a geographic information system depends on the Onondaga Lake Partnership’s determination of: (1) the design and plan for a geographic information system, including the applications and spatial data that will be provided and to whom, (2) the level of geographic information system technology to be utilized and funded, and (3) the institutional issues of operation and maintenance of the system.

Open-File Report

Selected field parameters from streams and preliminary analytical data from water and macroinvertebrate samples, Central Colorado Assessment Project, task, 2004 and 2005

The U.S. Geological Survey (USGS) Central Colorado Assessment Project (CCAP) began in October 2003 and is planned to last through September 2008. One major goal of this project is to compare the relationships between surface-water chemistry and aquatic fauna in mined and unmined areas. To accomplish this goal, we are conducting a State-scale reconnaissance sampling program, in which we are collecting water and macroinvertebrate samples. Selected results from the first two years of project analyses are reported here. We plan to develop statistical models and use geographic information system (GIS) technology to quantify the relationships between ecological indicators of metal contamination in Rocky Mountain streams and water quality, landscape and land-use characteristics (for example, mine density, geology, geomorphology, vegetation, topography). Our research will test the hypothesis that physicochemical variables and ecological responses to metal concentrations in stream water in Rocky Mountain streams are ultimately determined largely by historical land uses.

Colorado

GIS mapping of earthquake ground shaking in San Francisco, California

Severe earthquakes of the last decade in Mexico, Armenia, and the United States have reemphasized the importance of local geologic site conditions in estimating damage and consequent losses. Recent advances in geographic information system (GIS) technology have created new opportunities for maintaining and integrating extensive spatial databases for applications in seismic hazard analysis. Ground motion data and damage distributions from past earthquakes are combined with GIS databases of geologic information to prepare preliminary maps for inferring input ground motion levels for earthquake resistant design. Maps of bedrock elevation, surface topography, and surface geology are used to develop maps of soil thickness and predominant period. Ground motion attenuation relationships are used to create maps estimating ground shaking intensity for a uniform ground condition. Relationships between geologic characteristics, ground motion amplification, and earthquake intensity are used to produce amplification capability maps. Estimated ground shaking for the uniform ground condition is combined with amplification capability to develop maps predicting regional ground shaking intensity. The methods of predictive GIS mapping described here are useful for estimating characteristics of input ground motion in many urbanized seismic regions of the world.

California

Estimating natural recharge in San Gorgonio Pass watersheds, California, 1913–2012

A daily precipitation-runoff model was developed to estimate spatially and temporally distributed recharge for groundwater basins in the San Gorgonio Pass area, southern California. The recharge estimates are needed to define transient boundary conditions for a groundwater-flow model being developed to evaluate the effects of pumping and climate on the long-term availability of groundwater. The area defined for estimating recharge is referred to as the San Gorgonio Pass watershed model (SGPWM) and includes three watersheds: San Timoteo Creek, Potrero Creek, and San Gorgonio River. The SGPWM was developed by using the U.S. Geological Survey INFILtration version 3.0 (INFILv3) model code used in previous studies of recharge in the southern California region, including the San Gorgonio Pass area. The SGPWM uses a 150-meter gridded discretization of the area of interest in order to account for spatial variability in climate and watershed characteristics. The high degree of spatial variability in climate and watershed characteristics in the San Gorgonio Pass area is caused, in part, by the high relief and rugged topography of the area. Daily climate data developed from a network of monitoring sites and published average monthly precipitation maps were used to develop the climate inputs for the SGPWM. Geographic Information System (GIS) data defining land surface altitude, vegetation, soils, surficial geology, and land cover were used to define input parameters representing the physical characteristics of the land surface, root zone, and shallow subsurface underlying the root zone. Model parameterization was based on a previous INFILv3 model developed for an area including the upper parts of the San Timoteo Creek and Potrero Creek drainages and the western part of the San Gorgonio River watershed. The previous INFILv3 model was calibrated by using available streamflow records from the model area. The SGPWM uses an updated INFILv3 version to represent shallow groundwater flow better beneath the root zone that contributes to lateral, downslope seepage rather than deep recharge. The SGPWM calibration was tested by using available streamflow records in the San Gorgonio Pass region. The SGPWM was used to simulate a 100-year water budget, including recharge and runoff, for water years 1913 through 2012. Results indicated that most recharge came from episodic infiltration of surface-water runoff in the larger stream channels. Results also indicated periods of great variability in recharge and runoff in response to variability in precipitation. More recharge was simulated for the area of the groundwater basin underlying the more permeable alluvial fill of the valley floor compared to recharge in the neighboring upland areas of the less permeable mountain blocks. The greater recharge was in response to the episodic streamflow that discharged from the mountain block areas and quickly infiltrated the permeable alluvial fill of the groundwater basin. Although precipitation at the higher altitudes of the mountain block was more than double precipitation at the lower altitudes of the valley floor, recharge for inter-channel areas of the mountain block was limited by the lower permeability bedrock underlying the thin soil cover, and most of the recharge in the mountain block was limited to the main stream channels underlain by alluvial fill.

California

U.S. Geological Survey Hydrologic Toolbox — A graphical and mapping interface for analysis of hydrologic data

The Hydrologic Toolbox is a Windows-based desktop software program that provides a graphical and mapping interface for analysis of hydrologic time-series data with a set of widely used and standardized computational methods. The software combines the analytical and statistical functionality provided in the U.S. Geological Survey Groundwater and Surface-Water Toolboxes and provides several enhancements to these programs. The main analytical methods are the computation of hydrologic-frequency statistics such as the 7-day minimum flow that occurs on average only once every 10 years (7Q10); the computation of design flows, including biologically based flows; the computation of flow-duration curves and duration hydrographs; eight computer-programming methods for hydrograph separation of a streamflow time series, including the Base-Flow Index (BFI), HYSEP, PART, and SWAT Bflow methods and Eckhardt’s two-parameter digital-filtering method; and the RORA recession-curve displacement method and associated RECESS program to estimate groundwater-recharge values from streamflow data. Several of the statistical methods provided in the Hydrologic Toolbox are used primarily for computation of critical low-flow statistics. The Hydrologic Toolbox also facilitates retrieval of streamflow and groundwater-level time-series data from the U.S. Geological Survey National Water Information System and outputs text reports that describe their analyses. The Hydrologic Toolbox was developed by use of the DotSpatial geographic information system (GIS) programming library, which is part of the MapWindow project. DotSpatial is a nonproprietary, open-source program written for the .NET framework that includes a spatial data viewer and GIS capabilities. Advantages of the DotSpatial system include its pure .NET implementation for both the user interface and the GIS mapping engine, and thus the DotSpatial system simplifies software deployment and installation. In addition to combining the functionality of the separate Groundwater and Surface-Water Toolboxes, the Hydrologic Toolbox also organizes the functionality by theme (Groundwater Tools, Surface-Water Tools, and general Time-Series Tools). This report provides a description of how to build a Hydrologic Toolbox project and to download and manage hydrologic time-series data. It includes an overview of the analytical and statistical capabilities of the Hydrologic Toolbox and highlights the primary differences between the Hydrologic Toolbox and the Groundwater and Surface-Water Toolboxes. The report supplements information available in an extensive online Help manual and is intended to provide a set of instructions that will allow users to quickly develop skills to use the mapping, data-retrieval, and computational tools of the program.

Techniques and Methods

Development of regression equations to estimate flow durations and low-flow-frequency statistics in New Hampshire streams

Regression equations and basin-characteristic digital datasets were developed to help water-resource managers estimate surface-water resources during periods of low flow in New Hampshire. The regression equations were developed to estimate statistics for the seasonal and annual low-flow-frequency and seasonal period-of-record and period-of-record flow durations. Because streamflow is maintained by ground-water discharge during periods of low flow, these equations also will aid in the assessment of ground-water availability. Ultimately, the equations and datasets developed herein can be combined with data on water withdrawals, discharges, and interbasin transfers in a geographic information system (GIS) to allow assessments of water use and water availability in any drainage basin in the State of New Hampshire. Regression equations developed in this study provide estimates of the seasonal (spring, summer, fall, and winter) and annual 7-day 2-year (7Q2) and 7-day 10-year (7Q10) low-flow-frequency values, as well as seasonal period-of-record and period-of-record flow durations (60-, 70-, 80-, 90-, 95-, and 98-percent exceedences) for ungaged reaches of unregulated New Hampshire streams. Regression equations were developed using seasonal and annual low-flow statistics from 58 to 60 continuous-record stream-gaging stations in New Hampshire and nearby areas in neighboring states, and measurements of various characteristics of the drainage basins that contribute flow to those stations. The estimating equations for the seasonal and annual 7Q2 and 7Q10 values were developed using generalized-least-squares (GLS) regression analyses. The GLS equations developed for these flow statistics gave average prediction errors that ranged from 11 to 61 percent. The estimating equations for flow-duration exceedence frequency values were developed using ordinary-least-squares (OLS) regression analysis. The OLS equations developed for these flow statistics gave average prediction errors ranging from 14 to 79 percent. A total of 93 measurable drainage-basin characteristics were selected as possible predictor variables. Of these 93 variables, the following 10 were determined to be statistically significant predictors for at least one of the dependent variables: drainage area, average basin slope, maximum basin elevation, average summer gage precipitation for 1961-90, average spring gage precipitation for 1961-90, average mean annual basin temperature for 1961-90, average mean summer basin temperature for 1961-90, average winter basin-centroid precipitation for 1961-90, percent of the basin that is coniferous, and percent of the basin that is mixed coniferous and deciduous. These 10 basin characteristics were selected because they were statistically significant based on several statistical parameters that evaluated which combination of characteristics contributed the most to the predictive accuracy of the regression-equation models. A GIS is required to measure the values of the predictor variables for the equations developed in this study.

New Hampshire

Net-infiltration map of the Navajo Sandstone outcrop area in western Washington County, Utah

As populations grow in the arid southwestern United States and desert bedrock aquifers are increasingly targeted for future development, understanding and quantifying the spatial variability of net infiltration and recharge becomes critically important for inventorying groundwater resources and mapping contamination vulnerability. A Geographic Information System (GIS)-based model utilizing readily available soils, topographic, precipitation, and outcrop data has been developed for predicting net infiltration to exposed and soil-covered areas of the Navajo Sandstone outcrop of southwestern Utah. The Navajo Sandstone is an important regional bedrock aquifer. The GIS model determines the net-infiltration percentage of precipitation by using an empirical equation. This relation is derived from least squares linear regression between three surficial parameters (soil coarseness, topographic slope, and downgradient distance from outcrop) and the percentage of estimated net infiltration based on environmental tracer data from excavations and boreholes at Sand Hollow Reservoir in the southeastern part of the study area. Processed GIS raster layers are applied as parameters in the empirical equation for determining net infiltration for soil-covered areas as a percentage of precipitation. This net-infiltration percentage is multiplied by average annual Parameter-elevation Regressions on Independent Slopes Model (PRISM) precipitation data to obtain an infiltration rate for each model cell. Additionally, net infiltration on exposed outcrop areas is set to 10 percent of precipitation on the basis of borehole net-infiltration estimates. Soils and outcrop net-infiltration rates are merged to form a final map. Areas of low, medium, and high potential for ground-water recharge have been identified, and estimates of net infiltration range from 0.1 to 66 millimeters per year (mm/yr). Estimated net-infiltration rates of less than 10 mm/yr are considered low, rates of 10 to 50 mm/yr are considered medium, and rates of more than 50 mm/yr are considered high. A comparison of estimated net-infiltration rates (determined from tritium data) to predicted rates (determined from GIS methods) at 12 sites in Sand Hollow and at Anderson Junction indicates an average difference of about 50 percent. Two of the predicted values were lower, five were higher, and five were within the estimated range. While such uncertainty is relatively small compared with the three order-of-magnitude range in predicted net-infiltration rates, the net-infiltration map is best suited for evaluating relative spatial distribution rather than for precise quantification of recharge to the Navajo aquifer at specific locations. An important potential use for this map is land-use zoning for protecting high net-infiltration parts of the aquifer from potential surface contamination.

Utah

Onshore and offshore geologic map of the Coal Oil Point area, southern California

Geologic maps that span the shoreline and include both onshore and offshore areas are potentially valuable tools that can lead to a more in depth understanding of coastal environments. Such maps can contribute to the understanding of shoreline change, geologic hazards, both offshore and along-shore sediment and pollutant transport. They are also useful in assessing geologic and biologic resources. Several intermediate-scale (1:100,000) geologic maps that include both onshore and offshore areas (herein called onshore-offshore geologic maps) have been produced of areas along the California coast (see Saucedo and others, 2003; Kennedy and others, 2007; Kennedy and Tan, 2008), but few large-scale (1:24,000) maps have been produced that can address local coastal issues. A cooperative project between Federal and State agencies and universities has produced an onshore-offshore geologic map at 1:24,000 scale of the Coal Oil Point area and part of the Santa Barbara Channel, southern California (fig. 1). As part of the project, the U.S. Geological Survey (USGS) and the California Geological Survey (CGS) hosted a workshop (May 2nd and 3rd, 2007) for producers and users of coastal map products (see list of participants) to develop a consensus on the content and format of onshore-offshore geologic maps (and accompanying GIS files) so that they have relevance for coastal-zone management. The USGS and CGS are working to develop coastal maps that combine geospatial information from offshore and onshore and serve as an important tool for addressing a broad range of coastal-zone management issues. The workshop was divided into sessions for presentations and discussion of bathymetry and topography, geology, and habitat products and needs of end users. During the workshop, participants reviewed existing maps and discussed their merits and shortcomings. This report addresses a number of items discussed in the workshop and details the onshore and offshore geologic map of the Coal Oil Point area. Results from this report directly address issues raised in the California Ocean Protection Act (COPA) Five Year Strategic Plan. For example, one of the guiding principles of the COPA five-year strategic plan is to 'Recognize the interconnectedness of the land and the sea, supporting sustainable uses of the coast and ensuring the health of ecosystems.' Results from this USGS report directly connect the land and sea with the creation of both a seamless onshore and offshore digital terrain model (DTM) and geologic map. One of the priority goals (and objectives) of the COPA plan is to 'monitor and map the ocean environment to provide data about conditions and trends.' Maps within this report provide land and sea geologic information for mapping and monitoring nearshore sediment processes, pollution transport, and sea-level rise and fall.

California

Loose-coupling a cellular automaton model and GIS: Long-term urban growth prediction for San Francisco and Washington/Baltimore

Prior research developed a cellular automaton model, that was calibrated by using historical digital maps of urban areas and can be used to predict the future extent of an urban area. The model has now been applied to two rapidly growing, but remarkably different urban areas: the San Francisco Bay region in California and the Washington/Baltimore corridor in the Eastern United States. This paper presents the calibration and prediction results for both regions, reviews their data requirements, compares the differences in the initial configurations and control parameters for the model in the two settings, and discusses the role of GIS in the applications. The model has generated some long term predictions that appear useful for urban planning and are consistent with results from other models and observations of growth. Although the GIS was only loosely coupled with the model, the model's provision of future urban patterns as data layers for GIS description and analysis is an important outcome of this type of calculation.

California, Maryland