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At least 433 records · Page 24Linked to original sources

USGS2001

The Upper Pennsylvanian Pittsburgh coal bed: Resources and mine models

The U.S. Geological Survey recently completed a digital coal resource assessment model of the Upper Pennsylvanian Pittsburgh coal bed, which indicates that after subtracting mined-out coal, 16 billion short tons (14 billion tonnes) remain of the original 34 billion short tons (31 billion tonnes) of coal. When technical, environmental, and social restrictions are applied to the remaining Pittsburgh coal model, only 12 billion short tons (11 billion tonnes) are available for mining. Our assessment models estimate that up to 0.61 billion short tons (0.55 billion tonnes), 2.7 billion short tons (2.4 billion tonnes), and 8.5 billion short tons (7.7 billion tonnes) could be available for surface mining, continuous mining, and longwall mining, respectively. This analysis is an example of a second-generation regional coal availability study designed to model recoverability characteristics for all the major coal beds in the United States.

Maryland, Ohio, Pennsylvania, West Virginia↗

USGS2019

Development and implementation of an empirical habitat change model and decision support tool for estuarine ecosystems

Widespread land use change in coastal ecosystems has led to a decline in the amount of habitat available for fish and wildlife, lower production of ecosystem goods and services, and loss of recreational and aesthetic value. This has prompted global efforts to restore the natural hydrologic regimes of developed shorelines, especially resource-rich estuaries, but the resilience of these restored ecosystems in the face of accelerated sea-level rise (SLR) remains uncertain. We implemented a Mo nitoring-based S imulation of A ccretion i n C oastal E s tuaries (MOSAICS) in R statistical software to address uncertainty in the resilience of modified estuarine habitats, using the Nisqually River Delta in the Pacific Northwest USA as a case study. MOSAICS is a spatially explicit model with a numerical foundation that uses empirical monitoring datasets to forecast habitat change in response to rising tidal levels. Because it accounts for the crucial ecomorphodynamic feedbacks between tidal inundation, vegetative growth, and sediment accretion, MOSAICS can be used to determine whether alternative management scenarios, such as enhanced sediment inputs, will bolster estuarine resilience to SLR. Under moderate SLR (0.62 m), the model predicted that a two-fold increase in mean daily suspended sediment during the rainy season was sufficient to maintain Nisqually’s emergent marshes through 2100, but under high SLR (1.35 m) MOSAICS indicated that greater sediment additions would be necessary to prevent submergence. A comparison between a restored marsh with subsided and high-elevation areas and a relict marsh demonstrated that the subsided restoration area was highly susceptible to SLR. Findings from the MOSAICS model highlight the importance of a site’s initial elevation, capacity for producing above and belowground biomass, and suspended sediment availability when considering management actions in estuaries and other coastal ecosystems.

Washington↗

USGS2020

Units recovery methods in compositional data analysis

Compositional data carry relative information. Hence, their statistical analysis has to be performed on coordinates with respect to a log-ratio basis. Frequently, the modeler is required to back-transform the estimates obtained with the modeling to have them in the original units such as euros, kg or mg/liter. Approaches for recovering original units need to be formally introduced and its properties explored. Here, we formulate and analyze the properties of two procedures: a simple approach consisting of adding a residual part to the composition and an approach based on the use of an auxiliary variable. Both procedures are illustrated using a geochemical data set where the original units are recovered when spatial models are applied.

Natural Resources Research↗

USGS2009

Introduction to special section on impacts of land use change on water resources

Changes in land use have potentially large impacts on water resources, yet quantifying these impacts remains among the more challenging problems in hydrology. Water, food, energy, and climate are linked through complex webs of direct and indirect effects and feedbacks. Land use is undergoing major changes due not only to pressures for more efficient food, feed, and fiber production to support growing populations but also due to policy shifts that are creating markets for biofuel and agricultural carbon sequestration. Hydrologic systems embody flows of water, solutes, sediments, and energy that vary even in the absence of human activity. Understanding land use impacts thus necessitates integrated scientific approaches. Field measurements, remote sensing, and modeling studies are shedding new light on the modes and mechanisms by which land use changes impact water resources. Such studies can help deconflate the interconnected influences of human actions and natural variations on the quantity and quality of soil water, surface water, and groundwater, past, present, and future.

Water Resources Research↗

USGS2013

The 3D Elevation Program: summary for California

California↗

USGS2012

Analytical resource assessment method for continuous (unconventional) oil and gas accumulations - The "ACCESS" Method

The U.S. Geological Survey (USGS) periodically assesses petroleum resources of areas within the United States and the world. The purpose of this report is to explain the development of an analytic probabilistic method and spreadsheet software system called Analytic Cell-Based Continuous Energy Spreadsheet System (ACCESS). The ACCESS method is based upon mathematical equations derived from probability theory. The ACCESS spreadsheet can be used to calculate estimates of the undeveloped oil, gas, and NGL (natural gas liquids) resources in a continuous-type assessment unit. An assessment unit is a mappable volume of rock in a total petroleum system. In this report, the geologic assessment model is defined first, the analytic probabilistic method is described second, and the spreadsheet ACCESS is described third. In this revised version of Open-File Report 00-044 , the text has been updated to reflect modifications that were made to the ACCESS program. Two versions of the program are added as appendixes.

Open-File Report↗

USGS2005

Sensitivity of alpine and subalpine lakes to acidification from atmospheric deposition in Grand Teton National Park and Yellowstone National Park, Wyoming

The sensitivity of 400 lakes in Grand Teton and Yellowstone National Parks to acidification from atmospheric deposition of nitrogen and sulfur was estimated based on statistical relations between acid-neutralizing capacity concentrations and basin characteristics to aid in the design of a long-term monitoring plan for Outstanding Natural Resource Waters. Acid-neutralizing capacity concentrations that were measured at 52 lakes in Grand Teton and 23 lakes in Yellowstone during synoptic surveys were used to calibrate the statistical models. Three acid-neutralizing capacity concentration bins (bins) were selected that are within the U.S. Environmental Protection Agency criteria of sensitive to acidification; less than 50 microequivalents per liter (?eq/L) (0-50), less than 100 ?eq/L (0-100), and less than 200 ?eq/L (0-200). The development of discrete bins enables resource managers to have the ability to change criteria based on the focus of their study. Basin-characteristic information was derived from Geographic Information System data sets. The explanatory variables that were considered included bedrock type, basin slope, basin aspect, basin elevation, lake area, basin area, inorganic nitrogen deposition, sulfate deposition, hydrogen ion deposition, basin precipitation, soil type, and vegetation type. A logistic regression model was developed and applied to lake basins greater than 1 hectare in Grand Teton (n = 106) and Yellowstone (n = 294). A higher percentage of lakes in Grand Teton than in Yellowstone were predicted to be sensitive to atmospheric deposition in all three bins. For Grand Teton, 7 percent of lakes had a greater than 60-percent probability of having acid-neutralizing capacity concentrations in the 0-50 bin, 36 percent of lakes had a greater than 60-percent probability of having acid-neutralizing capacity concentrations in the 0-100 bin, and 59 percent of lakes had a greater than 60-percent probability of having acid-neutralizing capacity concentrations in the 0-200 bin. The elevation of the lake outlet and the area of the basin with northeast aspects were determined to be statistically significant and were used as the explanatory variables in the multivariate logistic regression model for the 0-100 bin. For Yellowstone, results indicated that 13 percent of lakes had a greater than 60-percent probability of having acid-neutralizing capacity concentrations in the 0-100 bin, and 27 percent of lakes had a greater than 60-percent probability of having acid-neutralizing capacity concentrations in the 0-200 bin. Only the elevation of the lake outlet was determined to be statistically significant and was used as the explanatory variable for the 0-100 bin. The lakes that exceeded 60-percent probability of having an acid-neutralizing capacity concentration in the 0-100 bin, and therefore had the greatest sensitivity to acidification from atmospheric deposition, are located at elevations greater than 2,790 meters in Grand Teton, and greater than 2,590 meters in Yellowstone.

Scientific Investigations Report↗

USGS2014

Analysis of projected water availability with current basin management plan, Pajaro Valley, California

The projection and analysis of the Pajaro Valley Hydrologic Model (PVHM) 34 years into the future using MODFLOW with the Farm Process (MF-FMP) facilitates assessment of potential future water availability. The projection is facilitated by the integrated hydrologic model, MF-FMP that fully couples the simulation of the use and movement of water from precipitation, streamflow, runoff, groundwater flow, and consumption by natural and agricultural vegetation throughout the hydrologic system at all times. MF-FMP allows for more complete analysis of conjunctive-use water-resource systems than previously possible with MODFLOW by combining relevant aspects of the landscape with the groundwater and surface-water components. This analysis is accomplished using distributed cell-by-cell supply-constrained and demand-driven components across the landscape within “water-balance subregions” (WBS) comprised of one or more model cells that can represent a single farm, a group of farms, watersheds, or other hydrologic or geopolitical entities. Analysis of conjunctive use would be difficult without embedding the fully coupled supply-and-demand into a fully coupled simulation, and are difficult to estimate a priori. The analysis of projected supply and demand for the Pajaro Valley indicate that the current water supply facilities constructed to provide alternative local sources of supplemental water to replace coastal groundwater pumpage, but may not completely eliminate additional overdraft. The simulation of the coastal distribution system (CDS) replicates: 20 miles of conveyance pipeline, managed aquifer recharge and recovery (MARR) system that captures local runoff, and recycled-water treatment facility (RWF) from urban wastewater, along with the use of other blend water supplies, provide partial relief and substitution for coastal pumpage (aka in-lieu recharge). The effects of these Basin Management Plan (BMP) projects were analyzed subject to historical climate variations and assumptions of 2009 urban water demand and land use. Water supplied directly from precipitation, and indirectly from reuse, captured local runoff, and groundwater is necessary but inadequate to satisfy agricultural demand without coastal and regional storage depletion that facilitates seawater intrusion. These facilities reduce potential seawater intrusion by about 45% with groundwater levels in the four regions served by the CDS projected to recover to levels a few feet above sea level. The projected recoveries are not high enough to prevent additional seawater intrusion during dry-year periods or in the deeper aquifers where pumpage is greater. While these facilities could reduce coastal pumpage by about 55% of the historical 2000–2009 pumpage for these regions, and some of the water is delivered in excess of demand, other coastal regions continue to create demands on coastal pumpage that will need to be replaced to reduce seawater intrusion. In addition, inland urban and agricultural demands continue to sustain water levels below sea level causing regional landward gradients that also drive seawater intrusion. Seawater intrusion is reduced by about 45% but it supplies about 55% of the recovery of groundwater levels in the coastal regions served by the CDS. If economically feasible, water from summer agricultural runoff and tile-drain returnflows could be another potential local source of water that, if captured and reused, could offset the imbalance between supply and demand as well as reducing discharge of agricultural runoff into the National Marine Sanctuary of Monterey Bay. A BMP update (2012) identifies projects and programs that will fund a conservation program and will provide additional, alternative water sources to reduce or replace coastal and inland pumpage, and to replenish the aquifers with managed aquifer recharge in an inland portion of the Pajaro Valley.

California↗

USGS2015

The 3D Elevation Program: summary for New Hampshire

Elevation data are essential to a broad range of applications important to New Hampshire, including flood mitigation, land development, agriculture, transportation planning and design, infrastructure asset inventory and management, and many others. For the State of New Hampshire, elevation data are critical for many business uses such as flood risk management, natural resources conservation, forest resources management, agriculture and precision farming, infrastructure and construction management, and geologic resource assessment and hazard mitigation. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

New Hampshire↗

USGS2016

Conservation planning for the Colorado River in Utah

Strategic planning is increasingly recognized as necessary for providing the greatest possible conservation benefits for restoration efforts. Rigorous, science-based resource assessment, combined with acknowledgement of broader basin trends, provides a solid foundation for determining effective projects. It is equally important that methods used to prioritize conservation investments are simple and practical enough that they can be implemented in a timely manner and by a variety of resource managers. With the help of local and regional natural resource professionals, we have developed a broad-scale, spatially-explicit assessment of 146 miles (~20,000 acres) of the Colorado River mainstem in Grand and San Juan Counties, Utah that will function as the basis for a systematic, practical approach to conservation planning and riparian restoration prioritization. For the assessment we have: 1) acquired, modified or created spatial datasets of Colorado River bottomland conditions; 2) synthesized those datasets into habitat suitability models and estimates of natural recovery potential, fire risk and relative cost; 3) investigated and described dominant ecosystem trends and human uses, and; 4) suggested site selection and prioritization approaches. Partner organizations (The Nature Conservancy, National Park Service, Bureau of Land Management and Utah Forestry Fire and State Lands) are using the assessment and datasets to identify and prioritize a suite of restoration actions to increase ecosystem resilience and improve habitat for bottomland species. Primary datasets include maps of bottomland cover types, bottomland extent, maps of areas inundated during high and low flow events, as well as locations of campgrounds, roads, fires, invasive vegetation treatment areas and other features. Assessment of conditions and trends in the project area entailed: 1) assemblage of existing data on geology, changes in stream flow, and predictions of future conditions; 2) identification of fish and wildlife species present and grouping species into Conservation Elements (CEs) based on habitat needs, and: 3) acquisition, review and creation of spatial datasets characterizing vegetation, fluvial geomorphic and human features within the bottomland. Interpretation of aerial imagery and assimilation of pre-existing spatial data were central to our efforts in characterizing resources conditions. Detailed maps of vegetation and channel habitat features in the project area were generated from true color, high resolution (0.3m) imagery flown September 16, 2010. We also mapped channel habitat features at high flow on 1.0-m resolution, publicly available, true color imagery. We obtained additional layers such as land ownership, roads, fire history, non-native vegetation treatment areas, and recreational use features from public sources and project partners. Habitat suitability models were created for groups of terrestrial species by combining spatial datasets with the habitat needs of conservation elements, guided by literature, where available, and extensive use of expert knowledge. Conservation elements for endangered fish species life stages were identified but not modeled. Terrestrial CE’s included: • Riparian Overstory -yellow-billed cuckoo, Bullock’s oriole, black-headed grosbeak, blue grosbeak, warbling vireo, Cooper's hawk, screech owl, saw-whet owl, and bald eagle, (best: tall trees, dense canopy, diverse shrub understory, no tamarisk); • Riparian Understory - southwestern willow flycatcher, common yellowthroat, yellow warbler, yellow-breasted chat, beaver, northern river otter, black-necked garter snake, (best: dense mesic shrubs near still water, no tamarisk); • Bat Feeding - Allen's big-eared bat, Townsend's big-eared bat, fringed myotis, Yuma myotis, big free-tailed bat, spotted bat (best: diverse vegetation, close to still water); • Bat Watering - big free-tailed and spotted bats (best: still water with no tall vegetation); •

Utah↗

USGS2014

The 3D Elevation Program: summary for Kansas

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Kansas, elevation data are critical for agriculture and precision farming, natural resources conservation, flood risk management, infrastructure and construction management, geologic resource assessment and hazard mitigation, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

Kansas↗

USGS2015

3D Elevation Program: summary for Nebraska

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Nebraska, elevation data are critical for agriculture and precision farming, natural resources conservation, flood risk management, infrastructure and construction management, geologic resource assessment and hazard mitigation, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

Nebraska↗

USGS2014

The 3D Elevation Program: summary for Maine

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Maine, elevation data are critical for natural resources conservation, flood risk management, forest resources management, agriculture and precision farming, coastal zone management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

Maine↗

USGS2014

The 3D Elevation Program: summary for Arizona

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Arizona, elevation data are critical for infrastructure and construction management, natural resources conservation, flood risk management, geologic resource assessment and hazard mitigation, agriculture and precision farming, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

Arizona↗

USGS2015

The 3D Elevation Program: summary for Nevada

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Nevada, elevation data are critical for infrastructure and construction management, natural resources conservation, flood risk management, geologic resource assessment and hazard mitigation, agriculture and precision farming, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

Nevada↗

USGS2014

The 3D Elevation Program: summary for Louisiana

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Louisiana, elevation data are critical for flood risk management, natural resources conservation, agriculture and precision farming, infrastructure and construction management, water supply and quality, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

Louisiana↗

USGS2019

Optimal spatial allocation of control effort to manage invasives in the face of imperfect detection and misclassification

Imperfect detection and misclassification errors are often ignored in the context of invasive species management. Here we present an approach that combines spatially explicit models and an optimization technique to design optimal search and destroy strategies based on noisy monitoring observations. We focus on two invasive plants, melaleuca ( Melaleuca quinquenervia ) and Old World climbing fern ( Lygodium microphyllum ), which continue to cause important damages to the Everglades ecosystem. We present a methodological framework that combines Hidden Markov Random Field (HMRF, initially developed for image analysis) and linear programming to optimally search for invasive species. A benefit of this approach is that it accounts for the spatial structure of the system by using a spatially explicit modeling approach (i.e. HMRF), and does not require repeated visits to model the probability of occurrence of species. We found on simulated cases that our approach can lead to substantial improvements in control efficiency when compared to state of the art model-free approaches. For example, in the case of the old world fern, simulations showed that the optimal strategy would allow managers to control up to 34% more sites than with model-free approaches that ignored misclassification and imperfect detection. For melaleuca it was possible to control up to 20% more sites. The vast increase in imagery data obtained from different sources (e.g. unmanned aerial systems, and satellite) provides great opportunities to improve management of natural resources by applying modern computational methods such as the one we present. Our approach can substantially increases the efficiency of invasive species control by accounting for imperfect detection, misclassification error and the spatial structure of the system. Our approach is applicable to other systems and problems, for example it could be applied to the control of plant pathogens, or optimal extraction of resources (e.g. minerals or biological resources).

Ecological Modelling↗

USGS2024

A methodology to estimate CO2 and energy gas storage resources in depleted conventional gas reservoirs

Depleted hydrocarbon reservoirs are subsurface geological structures capable of sequestering vast quantities of carbon dioxide (CO 2 ) as well as storing other energy gases for later usage, such as natural gas, and potentially hydrogen (H 2 ). Here we outline a methodology to quantify multi-gas storage resources in depleted conventional gas reservoirs for usage in assessments by the United States Geological Survey (USGS) at the scale of sedimentary basins. The methodology consists first of quantifying accessible pore volume in a depleted reservoir for natural gas storage using up to three equations. Input data are derived from commonly reported or estimated reservoir parameters and natural gas production volumes, and equations may be combined in linear models to improve pore volume estimates. Storage estimates from these equations are tested and validated for 31 reservoirs in the Michigan Basin Province, USA that were previously converted to underground gas storage facilities and have known (federally reported) natural gas storage capacities. Secondly, natural gas storage capacities can be transformed via fluid substitution calculations to estimate the storage resources for non-native fluids, applied here for, CO 2 , H 2 , and methane-H 2 blends, accounting for molecule-specific deviations from ideal gas behavior at reservoir pressures and temperatures as well as differing storage efficiencies. Importantly, the storage of non-native fluids may not be appropriate in all depleted gas reservoir settings due to potential risks like leakage, in particular in the case of H 2 storage, requiring additional knowledge of caprock sealing capacity. Given this caveat, we demonstrate the fluid substitution method for natural gas reservoirs of the Northern Niagaran Reef and Southern Niagaran Reef USGS plays in the Michigan Basin Province, as these trends of Silurian pinnacle reefs are capped with tight-sealing evaporite facies. The deterministic equations outlined from this methodology can be incorporated into future probabilistic USGS gas storage assessments for CO 2 , H 2 , and natural gas resources in the United States.

Michigan↗