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At least 1,027 records · Page 57Linked to original sources

USGS2005

Conceptual model of sediment processes in the upper Yuba River watershed, Sierra Nevada, CA

This study examines the development of a conceptual model of sediment processes in the upper Yuba River watershed; and we hypothesize how components of the conceptual model may be spatially distributed using a geographical information system (GIS). The conceptual model illustrates key processes controlling sediment dynamics in the upper Yuba River watershed and was tested and revised using field measurements, aerial photography, and low elevation videography. Field reconnaissance included mass wasting and channel storage inventories, assessment of annual channel change in upland tributaries, and evaluation of the relative importance of sediment sources and transport processes. Hillslope erosion rates throughout the study area are relatively low when compared to more rapidly eroding landscapes such as the Pacific Northwest and notable hillslope sediment sources include highly erodible andesitic mudflows, serpentinized ultramafics, and unvegetated hydraulic mine pits. Mass wasting dominates surface erosion on the hillslopes; however, erosion of stored channel sediment is the primary contributor to annual sediment yield. We used GIS to spatially distribute the components of the conceptual model and created hillslope erosion potential and channel storage models. The GIS models exemplify the conceptual model in that landscapes with low potential evapotranspiration, sparse vegetation, steep slopes, erodible geology and soils, and high road densities display the greatest hillslope erosion potential and channel storage increases with increasing stream order. In-channel storage in upland tributaries impacted by hydraulic mining is an exception. Reworking of stored hydraulic mining sediment in low-order tributaries continues to elevate upper Yuba River sediment yields. Finally, we propose that spatially distributing the components of a conceptual model in a GIS framework provides a guide for developing more detailed sediment budgets or numerical models making it an inexpensive way to develop a roadmap for understanding sediment dynamics at a watershed scale.

Geomorphology↗

USGS2008

GIS technology and models for assessing landslide hazard and risk

Advances in Geographical Information Systems (GIS) technology and the mathematical/statistical tools for modelling and simulation have led to the growing application of quantitative techniques in many areas of the earth sciences. Few disciplines have embraced these developments more enthusiastically than the study of landslide hazards. Because the shape of the land surface plays a fundamental role in landslide processes, much of this new work has been driven by the increasing availability of digital elevation models (DEMs) and the software to manipulate them. As a result, investigators worldwide are devising spatial models to forecast slope instability in efforts to keep landslide hazards from becoming landslide disasters. The methods range from empirical and heuristic to statistical and physically-based. Despite nearly a quarter-century of progress, e.g. since Carrara (1983) , and a veritable “cottage industry” of current DEM-based hazard mapping, many of these spatial predictions either are based on unsuitable data or are not properly modelled.

Geomorphology↗

USGS2011

Hillslope chemical weathering across Paraná, Brazil: a data mining-GIS hybrid approach

Self-organizing map (SOM) and geographic information system (GIS) models were used to investigate the nonlinear relationships associated with geochemical weathering processes at local (~100 km 2 ) and regional (~50,000 km 2 ) scales. The data set consisted of 1) 22 B-horizon soil variables: P, C, pH, Al, total acidity, Ca, Mg, K, total cation exchange capacity, sum of exchangeable bases, base saturation, Cu, Zn, Fe, B, S, Mn, gammaspectrometry (total count, potassium, thorium, and uranium) and magnetic susceptibility measures; and 2) six topographic variables: elevation, slope, aspect, hydrological accumulated flux, horizontal curvature and vertical curvature. It is characterized at 304 locations from a quasi-regular grid spaced about 24 km across the state of Paraná. This data base was split into two subsets: one for analysis and modeling (274 samples) and the other for validation (30 samples) purposes. The self-organizing map and clustering methods were used to identify and classify the relations among solid-phase chemical element concentrations and GIS derived topographic models. The correlation between elevation and k-means clusters related the relative position inside hydrologic macro basins, which was interpreted as an expression of the weathering process reaching a steady-state condition at the regional scale. Locally, the chemical element concentrations were related to the vertical curvature representing concave–convex hillslope features, where concave hillslopes with convergent flux tends to be a reducing environment and convex hillslopes with divergent flux, oxidizing environments. Stochastic cross validation demonstrated that the SOM produced unbiased classifications and quantified the relative amount of uncertainty in predictions. This work strengthens the hypothesis that, at B-horizon steady-state conditions, the terrain morphometry were linked with the soil geochemical weathering in a two-way dependent process: the topographic relief was a factor on environmental geochemistry while chemical weathering was for terrain feature delineation.

Parana↗

USGS2020

Global physical controls on estuarine habitat distribution during sea levelchange: Consequences for genetic diversification through time

Determining the extrinsic (physical) factors controlling speciation and diversification of species through time is of key interest in paleontology and evolutionary biology. The role of sea-level change in shaping species richness patterns of marginal marine species has received much attention, but with variable conclusions. Recent work combining genetic data and Geographical Information Systems (GIS)-based habitat modeling yielded a framework for how geomorphology of continental margins mediates genetic connectivity of populations during sealevel change. This approach may ultimately yield insights on how distinct lineages, species, and biodiversity accumulate in coastal settings. Here, we expand this GIS work globally to different geomorphic settings to model estuarine habitat in a larger geographic framework and test how tectonic setting, oceanographic setting, climate, and margin age affect habitat distribution during sea-level change. In addition, independent of estuaries we explore paleobiologic (e.g. Olsson, 1961) and neontolologic effects of sea-level change on evolution, and test the relation between overall shelf area and species richness using data of 1721 fish species. We find 82% global reduction of estuarine habitat abundance at lowstand relative to highstand, and find large habitats change in size much more than small habitats. Consistent with prior work, narrow continental margins have significantly less habitat at highstand and lowstand than wide margins, and narrow margins significantly associate with fore-arc settings, effectively linking tectonic setting to habitat abundance. Surprisingly, narrow margins host greater species richness, a finding which violates the canonical species-area relation. This finding can be explained if: 1) the physical isolation imposed by narrow margins facilitates the formation of new species over time; 2) the sizestability of small habitats, which disproportionately occur on narrow margins, accumulate and retain species extirpated in the more variable habitats on wide margins; or 3) the smaller habitats on narrow margins facilitate greater species richness through greater habitat heterogeneity. These results are generally at odds with prior interpretations, but the combination of richness data and population genetic principles offer a different perspective on these long-studied questions. Finally, we emphasize that the nuance of Pleistocene-Holocene sea level oscillations should be more explicitly considered in genetic studies.

Global and Planetary Change↗

USGS2022

Multi-hazard risk analysis for the U.S. Department of the Interior: An integration of expert elicitation, planning priorities, and geospatial analysis

An integral part of disaster risk management is identifying and prioritizing hazards and their potential impacts in a meaningful way to support risk-reduction planning. There has been considerable use and subsequent criticism of threat prioritization efforts that simply compare likelihoods and consequences of plausible threats. This article summarizes a new mixed-methods and scalable approach for prioritizing risks in a multi-hazard, multi-objective, and multi-criteria organizational context. This approach integrates (1) hazard characterizations using subject-matter-expert (SME) elicitation, (2) expressed preferences in planning priorities provided by emergency managers, and (3) quantitative estimates of asset exposure to hazards using geospatial data and geographic-information-systems (GIS) software. We demonstrate this approach with a case study designed to support multi-hazard mitigation and response planning done by the U.S. Department of the Interior (DOI) Office of Emergency Management, which required a national understanding of the risks posed by 75 natural, technological, and adversarial hazards to DOI managed and administered lands, facilities, people, revenues, and resources. Results demonstrate that hazard priorities vary depending on the asset, scale, and risk-management context, thereby making the case that “one-size-fits-all” hazard rankings have limited utility or relevance to real-world, risk mitigation and response planning. Our results suggest that recognizing the risk-management context provides greater transparency, flexibility, and relevance in comparing threats than traditional likelihood-threat matrices or the use of hazard SMEs to decide for planners which hazard scenarios are emphasized in risk planning.

International Journal of Disaster Risk Reduction↗

USGS2009

GIS applications for military operations in coastal zones

In order to successfully support current and future US military operations in coastal zones, geospatial information must be rapidly integrated and analyzed to meet ongoing force structure evolution and new mission directives. Coastal zones in a military-operational environment are complex regions that include sea, land and air features that demand high-volume databases of extreme detail within relatively narrow geographic corridors. Static products in the form of analog maps at varying scales traditionally have been used by military commanders and their operational planners. The rapidly changing battlefield of 21st Century warfare, however, demands dynamic mapping solutions. Commercial geographic information system (GIS) software for military-specific applications is now being developed and employed with digital databases to provide customized digital maps of variable scale, content and symbolization tailored to unique demands of military units. Research conducted by the Center for Remote Sensing and Mapping Science at the University of Georgia demonstrated the utility of GIS-based analysis and digital map creation when developing large-scale (1:10,000) products from littoral warfare databases. The methodology employed-selection of data sources (including high resolution commercial images and Lidar), establishment of analysis/modeling parameters, conduct of vehicle mobility analysis, development of models and generation of products (such as a continuous sea-land DEM and geo-visualization of changing shorelines with tidal levels)-is discussed. Based on observations and identified needs from the National Geospatial-Intelligence Agency, formerly the National Imagery and Mapping Agency, and the Department of Defense, prototype GIS models for military operations in sea, land and air environments were created from multiple data sets of a study area at US Marine Corps Base Camp Lejeune, North Carolina. Results of these models, along with methodologies for developing large-scale littoral warfare databases, aid the National Geospatial-Intelligence Agency in meeting littoral warfare analysis, modeling and map generation requirements for US military organizations. ?? 2008 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

ISPRS Journal of Photogrammetry and Remote Sensing↗

USGS2018

Landscape-scale processes influence riparian plant composition along a regulated river

Hierarchical frameworks are useful constructs when exploring landscape- and local-scale factors affecting patterns of vegetation in riparian areas. In drylands, which have steep environmental gradients and high habitat heterogeneity, landscape-scale variables, such as climate, can change rapidly along a river's course, affecting the relative influence of environmental variables at different scales. To assess how landscape-scale factors change the structure of riparian vegetation, we measured riparian vegetation composition along the Colorado River through Grand Canyon, determined which factors best explain observed changes, identified how richness and functional diversity vary, and described the implications of our results for river management. Cluster analysis identified three divergent floristic groups that are distributed longitudinally along the river. These groups were distributed along gradients of elevation, temperature and seasonal precipitation, but were not associated with annual precipitation or local-scale factors. Species richness and functional diversity decreased as a function of distance downstream showing that changing landscape-scale factors result in changes to ecosystem characteristics. Species composition and distribution remain closely linked to seasonal precipitation and temperature. These patterns in floristic composition in a semiarid system inform management and provide insights into potential future changes as a result of shifts in climate and changes in flow management.

Arizona↗

USGS2014

Habitat used by juvenile lake sturgeon ( Acipenser fulvescens ) in the North Channel of the St. Clair River (Michigan, USA)

Lake sturgeon ( Acipenser fulvescens ) occupy the St. Clair River, part of a channel connecting lakes Huron and Erie in the Laurentian Great Lakes. In the North Channel of the St. Clair River, juvenile lake sturgeon (3–7 years old and 582–793 mm in length) were studied to determine movement patterns and habitat usage. Fourteen juveniles were implanted with ultrasonic transmitters and tracked June–August of 2004, 2005 and 2006. Telemetry data, Geographic Information System software, side-scan sonar, video images of the river bottom, scuba diving, and benthic substrate samples were used to determine the extent and composition of habitats they occupied. Juvenile lake sturgeon habitat selection was strongly related to water depth. No fish were found in <6 m of water and over 97% of the relocations were found at depths greater than 9 m. Available water depths exceeding 18 m only represented 3.5% of the available habitat, however 34.9% of the relocations were found at depths exceeding 18 m. Juvenile lake sturgeon did not use most areas in proportion to their availability. Sturgeon avoided clay ledges and shallow areas with silt or soft clay, which comprised approximately 39% of the benthic habitat in the North Channel. A total of 300 out of 351 documented locations were on sand and gravel habitat types mixed with clay. Lake sturgeon > 700 mm in length selected sand and gravel areas mixed with zebra mussels and areas dominated by zebra mussels, while fish < 700 mm used these habitat types in proportion to their availability.

Michigan↗

USGS2006

Estimating recharge using relations between precipitation and yield in a mountainous area with large variability in precipitation

Estimates of recharge to bedrock aquifers from infiltration of precipitation can be difficult to obtain, especially in areas with large spatial and temporal variability in precipitation. In the Black Hills area of western South Dakota and eastern Wyoming, streamflow yield is highly influenced by annual precipitation, with yield efficiency (annual yield divided by annual precipitation) increasing with increasing annual precipitation. Spatial variability in annual yield characteristics for Black Hills streams is predictably influenced by precipitation patterns. Relations between precipitation and yield efficiency were used to estimate annual recharge from long-term records of annual precipitation. A series of geographic information system algorithms was used to derive annual estimates for 1000- by 1000-m grid cells. These algorithms were composited to derive estimates of annual recharge rates to the Madison and Minnelusa aquifers in the Black Hills area of western South Dakota and eastern Wyoming during water years 1931-1998 and an estimate of average recharge for water years 1950-1998. This approach provides a systematic method of obtaining consistent and reproducible estimates of recharge from infiltration of precipitation. Resulting estimates of average annual recharge (water years 1950-1998) ranged from 1 cm in the southern Black Hills to 22 cm in the northwestern Black Hills. Recharge rates to these aquifers from infiltration of precipitation on outcrops was estimated to range from 0.9 m 3/s in 1936 to 18.8 m3/s in 1995.

Journal of Hydrology↗

USGS2018

Metamodeling and mapping of nitrate flux in the unsaturated zone and groundwater, Wisconsin, USA

Nitrate contamination of groundwater in agricultural areas poses a major challenge to the sustainability of water resources. Aquifer vulnerability models are useful tools that can help resource managers identify areas of concern, but quantifying nitrogen (N) inputs in such models is challenging, especially at large spatial scales. We sought to improve regional nitrate (NO 3 − ) input functions by characterizing unsaturated zone NO 3 − transport to groundwater through use of surrogate, machine-learning metamodels of a process-based N flux model. The metamodels used boosted regression trees (BRTs) to relate mappable landscape variables to parameters and outputs of a previous “vertical flux method” (VFM) applied at sampled wells in the Fox, Wolf, and Peshtigo (FWP) river basins in northeastern Wisconsin. In this context, the metamodels upscaled the VFM results throughout the region, and the VFM parameters and outputs are the metamodel response variables. The study area encompassed the domain of a detailed numerical model that provided additional predictor variables, including groundwater recharge, to the metamodels. We used a statistical learning framework to test a range of model complexities to identify suitable hyperparameters of the six BRT metamodels corresponding to each response variable of interest: NO 3 − source concentration factor (which determines the local NO 3 − input concentration); unsaturated zone travel time; NO 3 − concentration at the water table in 1980, 2000, and 2020 (three separate metamodels); and NO 3 − “extinction depth”, the eventual steady state depth of the NO 3 − front. The final metamodels were trained to 129 wells within the active numerical flow model area, and considered 58 mappable predictor variables compiled in a geographic information system (GIS). These metamodels had training and cross-validation testing R 2 values of 0.52 – 0.86 and 0.22 – 0.38, respectively, and predictions were compiled as maps of the above response variables. Testing performance was reasonable, considering that we limited the metamodel predictor variables to mappable factors as opposed to using all available VFM input variables. Relationships between metamodel predictor variables and mapped outputs were generally consistent with expectations, e.g. with greater source concentrations and NO 3 − at the groundwater table in areas of intensive crop use and well drained soils. Shorter unsaturated zone travel times in poorly drained areas likely indicated preferential flow through clay soils, and a tendency for fine grained deposits to collocate with areas of shallower water table. Numerical estimates of groundwater recharge were important in the metamodels and may have been a proxy for N input and redox conditions in the northern FWP, which had shallow predicted NO 3 − extinction depth. The metamodel results provide proof-of-concept for regional characterization of unsaturated zone NO 3 − transport processes in a statistical framework based on readily mappable GIS input variables.

Wisconsin↗

USGS2019

An ANCOVA model for porosity and its uncertainty for oil reservoirs based on TORIS dataset

Porosity is one of the most important parameters to assess in-place oil or gas in reservoirs, and to evaluate recovery from enhanced production operations. Since it is relatively well-established to determine porosity using different laboratory and field methods, its value is usually determined at many locations across a reservoir as part of the common practice to capture reservoir heterogeneity and the variability in values. This suite of measurements and the distribution of values are most valuable for probabilistic reservoir assessments, and for spatial modeling if the exact data locations are known. Despite the importance of individual measurements to set the range of values for probabilistic studies, it is not always possible to access these data due to confidentiality. In most cases, commercial or publicly available databases that assessments may rely on usually report only mean values of porosity, like any other reservoir data, or they may not report a value at all. This makes both quantifying the mean value and the uncertainty around it difficult for probabilistic assessments. In this study, the TORIS (Tertiary Oil Recovery Information System) dataset of the National Petroleum Council and the U.S. Department of Energy was used to model porosity and the uncertainty around predicted values. TORIS is an integrated dataset of production data, reservoir properties, and project databases of crude oil reservoirs in the United States. The model presented in the paper was based on ANCOVA (Analysis of Co-Variance) of data from 1038 reservoirs from the TORIS dataset for porosity prediction, validation and testing for quantitative and qualitative parameters that may be readily available in most cases, and to estimate uncertainty around the mean values. This model also explored association of porosity values to different parameters, and to different depositional systems and diagenetic overprint conditions. Furthermore, an ANN (Artificial Neural Network) model was created to compare the predicted values of both models. Results showed that the ANN model was able to represent more of the variability, however it lacked the insights that might be gained from the ANCOVA model.

Journal of Petroleum Science and Engineering↗

USGS2014

The digital global geologic map of Mars: Chronostratigraphic ages, topographic and crater morphologic characteristics, and updated resurfacing history

A new global geologic map of Mars has been completed in a digital, geographic information system (GIS) format using geospatially controlled altimetry and image data sets. The map reconstructs the geologic history of Mars, which includes many new findings collated in the quarter century since the previous, Viking-based global maps were published, as well as other discoveries that were made during the course of the mapping using new data sets. The technical approach enabled consistent and regulated mapping that is appropriate not only for the map's 1:20,000,000 scale but also for its widespread use by diverse audiences. Each geologic unit outcrop includes basic attributes regarding identity, location, area, crater densities, and chronostratigraphic age. In turn, units are grouped by geographic and lithologic types, which provide synoptic global views of material ages and resurfacing character for the Noachian, Hesperian, and Amazonian periods. As a consequence of more precise and better quality topographic and morphologic data and more complete crater-density dating, our statistical comparisons identify significant refinements for how Martian geologic terrains are characterized. Unit groups show trends in mean elevation and slope that relate to geographic occurrence and geologic origin. In comparison with the previous global geologic map series based on Viking data, the new mapping consists of half the number of units due to simpler, more conservative and globally based approaches to discriminating units. In particular, Noachian highland surfaces overall have high percentages of their areas now dated as an epoch older than in the Viking mapping. Minimally eroded (i.e., pristine) impact craters ≥3 km in diameter occur in greater proportion on Hesperian surfaces. This observation contrasts with a deficit of similarly sized craters on heavily cratered and otherwise degraded Noachian terrain as well as on young Amazonian surfaces. We interpret these as reflecting the relatively stronger, lava-rich, yet less-impacted materials making up much of the younger units. Reconstructions of resurfacing of Mars by its eight geologic epochs using the Hartmann and Neukum chronology models indicate high rates of highland resurfacing during the Noachian (peaking at 0.3 km 2 /yr during the Middle Noachian), modest rates of volcanism and transition zone and lowland resurfacing during the Hesperian (∼0.1 km 2 /yr), and low rates of mainly volcanic and polar resurfacing (∼0.01 km 2 /yr) for most of the Amazonian. Apparent resurfacing increased in the Late Amazonian (∼0.03 km 2 /yr), perhaps due to better preservation of this latest record.

Planetary and Space Science↗

USGS2016

Near-real-time cheatgrass percent cover in the Northern Great Basin, USA, 2015

Cheatgrass ( Bromus tectorum L.) dramatically changes shrub steppe ecosystems in the Northern Great Basin, United States. Current-season cheatgrass location and percent cover are difficult to estimate rapidly. We explain the development of a near-real-time cheatgrass percent cover dataset and map in the Northern Great Basin for the current year (2015), display the current year’s map, provide analysis of the map, and provide a website link to download the map (as a PDF) and the associated dataset. The near-real-time cheatgrass percent cover dataset and map were consistent with non-expedited, historical cheatgrass percent cover datasets and maps. Having cheatgrass maps available mid-summer can help land managers, policy makers, and Geographic Information Systems personnel as they work to protect socially relevant areas such as critical wildlife habitats.

Rangelands↗

USGS2012

Potential pollutant sources in a Choptank River (USA) subwatershed and the influence of land use and watershed characteristics

Row-crop and poultry production have been implicated as sources of water pollution along the Choptank River, an estuary and tributary of the Chesapeake Bay. This study examined the effects of land use, subwatershed characteristics, and climatic conditions on the water quality parameters of a subwatershed in the Choptank River watershed. The catchments within the subwatershed were defined using advanced remotely-sensed data and current geographic information system processing techniques. Water and sediment samples were collected in May–October 2009 and April–June 2010 under mostly baseflow conditions and analyzed for select bacteria, nitrate-N, ammonium-N, total arsenic, total phosphorus (TP), orthophosphate (ortho-P), and particle-phase phosphorus (PP); n = 96 for all analytes except for arsenic, n = 136, and for bacteria, n = 89 (aqueous) and 62 (sediment). Detections of Enterococci and Escherichia coli concentrations were ubiquitous in this subwatershed and showed no correlation to location or land use, however larger bacterial counts were observed shortly after precipitation. Nitrate-N concentrations were not correlated with agricultural lands, which may reflect the small change in percent agriculture and/or the similarity of agronomic practices and crops produced between catchments. Concentration data suggested that ammonia emission and possible deposition to surface waters occurred and that these processes may be influenced by local agronomic practices and climatic conditions. The negative correlation of PP and arsenic concentrations with percent forest was explained by the stronger signal of the head waters and overland flow of particulate phase analytes versus dissolved phase inputs from groundwater. Service roadways at some poultry production facilities were found to redirect runoff from the facilities to neighboring catchment areas, which affected water quality parameters. Results suggest that in this subwatershed, catchments with poultry production facilities are possible sources for arsenic and PP as compared to catchment areas where these facilities were not present.

Choptank River↗

USGS2014

A GIS-based vulnerability assessment of brine contamination to aquatic resources from oil and gas development in eastern Sheridan County, Montana

Water (brine) co-produced with oil in the Williston Basin is some of the most saline in the nation. The Prairie Pothole Region (PPR), characterized by glacial sediments and numerous wetlands, covers the northern and eastern portion of the Williston Basin. Sheridan County, Montana, lies within the PPR and has a documented history of brine contamination. Surface water and shallow groundwater in the PPR are saline and sulfate dominated while the deeper brines are much more saline and chloride dominated. A Contamination Index (CI), defined as the ratio of chloride concentration to specific conductance in a water sample, was developed by the Montana Bureau of Mines and Geology to delineate the magnitude of brine contamination in Sheridan County. Values > 0.035 indicate contamination. Recently, the U.S. Geological Survey completed a county level geographic information system (GIS)-based vulnerability assessment of brine contamination to aquatic resources in the PPR of the Williston Basin based on the age and density of oil wells, number of wetlands, and stream length per county. To validate and better define this assessment, a similar approach was applied in eastern Sheridan County at a greater level of detail (the 2.59 km 2 Public Land Survey System section grid) and included surficial geology. Vulnerability assessment scores were calculated for the 780 modeled sections and these scores were divided into ten equal interval bins representing similar probabilities of contamination. Two surface water and two groundwater samples were collected from the section with the greatest acreage of Federal land in each bin. Nineteen of the forty water samples, and at least one water sample from seven of the ten selected sections, had CI values indicating contamination. Additionally, CI values generally increased with increasing vulnerability assessment score, with a stronger correlation for groundwater samples (R 2 = 0.78) than surface water samples (R 2 = 0.53).

Montana↗

USGS1997

Coal quality trends and distribution of potentially hazardous trace elements in eastern Kentucky coals

Coal in the Eastern Kentucky coalfield has been, and continues to be, a valuable energy resource, especially for the electric utility industry. However, Federal mandates in Titles III and IV of the Clean Air Act Amendments of 1990 have placed increasingly stringent demands on the type and grade of coal that can be burnt in an environmentally acceptable manner. Therefore, a greater understanding of the spatial and temporal distribution of thickness and quality parameters, and the geologic factors that control their distribution, is critical if the Eastern Kentucky coalfield is to continue to be a major producer of high-quality coal. Information from the Kentucky Geological Survey's Coal Resource Information System database is used in this paper to document the geographic and stratigraphic distribution of important factors such as bed thickness, calorific value, ash yield and total sulfur content. The distribution of 15 elements that naturally occur in trace amounts in Kentucky coal is also discussed, as these elements may require monitoring with passage of Title III of the Clean Air Act Amendments of 1990.

Kentucky↗

USGS2002

Long-term cliff retreat and erosion hotspots along the central shores of the Monterey Bay National Marine Sanctuary

Quantification of cliff retreat rates for the southern half of Santa Cruz County, CA, USA, located within the Monterey Bay National Marine Sanctuary, using the softcopy/geographic information system (GIS) methodology results in average cliff retreat rates of 7–15 cm/yr between 1953 and 1994. The coastal dunes at the southern end of Santa Cruz County migrate seaward and landward through time and display net accretion between 1953 and 1994, which is partially due to development. In addition, three critically eroding segments of coastline with high average erosion rates ranging from 20 to 63 cm/yr are identified as erosion ‘hotspots’. These locations include: Opal Cliffs, Depot Hill and Manresa. Although cliff retreat is episodic, spatially variable at the scale of meters, and the factors affecting cliff retreat vary along the Santa Cruz County coastline, there is a compensation between factors affecting retreat such that over the long-term the coastline maintains a relatively smooth configuration. The softcopy/GIS methodology significantly reduces errors inherent in the calculation of retreat rates in high-relief areas (e.g. erosion rates generated in this study are generally correct to within 10 cm) by removing errors due to relief displacement. Although the resulting root mean squared error for erosion rates is relatively small, simple projections of past erosion rates are inadequate to provide predictions of future cliff position. Improved predictions can be made for individual coastal segments by using a mean erosion rate and the standard deviation as guides to future cliff behavior in combination with an understanding of processes acting along the coastal segments in question. This methodology can be applied on any high-relief coast where retreat rates can be measured.

California↗

USGS2001

A geostatistical approach to predicting sulfur content in the Pittsburgh coal bed

The US Geological Survey (USGS) is completing a national assessment of coal resources in the five top coal-producing regions in the US. Point-located data provide measurements on coal thickness and sulfur content. The sample data and their geologic interpretation represent the most regionally complete and up-to-date assessment of what is known about top-producing US coal beds. The sample data are analyzed using a combination of geologic and Geographic Information System (GIS) models to estimate tonnages and qualities of the coal beds. Traditionally, GIS practitioners use contouring to represent geographical patterns of "similar" data values. The tonnage and grade of coal resources are then assessed by using the contour lines as references for interpolation. An assessment taken to this point is only indicative of resource quantity and quality. Data users may benefit from a statistical approach that would allow them to better understand the uncertainty and limitations of the sample data. To develop a quantitative approach, geostatistics were applied to the data on coal sulfur content from samples taken in the Pittsburgh coal bed (located in the eastern US, in the southwestern part of the state of Pennsylvania, and in adjoining areas in the states of Ohio and West Virginia). Geostatistical methods that account for regional and local trends were applied to blocks 2.7 mi (4.3 km) on a side. The data and geostatistics support conclusions concerning the average sulfur content and its degree of reliability at regional- and economic-block scale over the large, contiguous part of the Pittsburgh outcrop, but not to a mine scale. To validate the method, a comparison was made with the sulfur contents in sample data taken from 53 coal mines located in the study area. The comparison showed a high degree of similarity between the sulfur content in the mine samples and the sulfur content represented by the geostatistically derived contours. Published by Elsevier Science B.V.

International Journal of Coal Geology↗