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1,696 records · Page 29Linked to original sources

USGS2025

Preventing overfitting when using tree-based methods for mapping hydrothermal favorability

Ensemble tree-based algorithms are robust tools for estimating sparsely distributed resources with non-linear dependencies (e.g., hydrothermal systems). These algorithms naturally accommodate the threshold conditions necessary to enable and support hydrothermal systems (e.g., having sufficient heat and permeability) and are simpler than many other non-linear machine learning strategies (e.g., artificial neural networks), which is an advantage when working with few labeled examples from which to learn. In previous work, we used eXtreme Gradient Boosting (XGBoost) to produce regional prediction and uncertainty maps of hydrothermal favorability; however, recent studies suggest that, even when properly applied, XGBoost has some risk of overfitting when there are few labeled examples from which to learn. To evaluate overfitting when constructing hydrothermal favorability maps with tree-based methods, we compare XGBoost with Extremely Randomized Trees (ExtraTrees), another ensemble tree-based algorithm that has the potential to underfit when using few labeled examples. We hold all other modeling parameters constant, resulting in two contrasting favorability maps of conventional geothermal resources for the Great Basin. Our results indicate that ExtraTrees demonstrably reduces overfitting compared with XGBoost. After considering overall performance, we conclude that ExtraTrees provides a more suitable modeling approach than XGBoost for the purposes of conventional hydrothermal resource assessments.

Conference Paper↗

USGS1998

Technique for simulating peak-flow hydrographs in Maryland

The efficient design and management of many bridges, culverts, embankments, and flood-protection structures may require the estimation of time-of-inundation and (or) storage of floodwater relating to such structures. These estimates can be made on the basis of information derived from the peak-flow hydrograph. Average peak-flow hydrographs corresponding to a peak discharge of specific recurrence interval can be simulated for drainage basins having drainage areas less than 500 square miles in Maryland, using a direct technique of known accuracy. The technique uses dimensionless hydrographs in conjunction with estimates of basin lagtime and instantaneous peak flow. Ordinary least-squares regression analysis was used to develop an equation for estimating basin lagtime in Maryland. Drainage area, main channel slope, forest cover, and impervious area were determined to be the significant explanatory variables necessary to estimate average basin lagtime at the 95-percent confidence interval. Qualitative variables included in the equation adequately correct for geographic bias across the State. The average standard error of prediction associated with the equation is approximated as plus or minus (+/-) 37.6 percent. Volume correction factors may be applied to the basin lagtime on the basis of a comparison between actual and estimated hydrograph volumes prior to hydrograph simulation. Three dimensionless hydrographs were developed and tested using data collected during 278 significant rainfall-runoff events at 81 stream-gaging stations distributed throughout Maryland and Delaware. The data represent a range of drainage area sizes and basin conditions. The technique was verified by applying it to the simulation of 20 peak-flow events and comparing actual and simulated hydrograph widths at 50 and 75 percent of the observed peak-flow levels. The events chosen are considered extreme in that the average recurrence interval of the selected peak flows is 130 years. The average standard errors of prediction were +/- 61 and +/- 56 percent at the 50 and 75 percent of peak-flow hydrograph widths, respectively.

Maryland↗

USGS2021

Virginia and Landsat

From the shores of Jamestown and spreading north, south, and west, the lands that became the State of Virginia were some of the first in North America top experience rapid landscape change from European settlement. Imagery and data from the USGS Landsat series of satellites offer an unparalleled resource for the study, understanding, and preservation of Virginia’s land and water resources. From monitoring the health of water bodies to managing invasive species to planning for a range of climate change effects, the USGS National Land Imaging Program’s stewardship and public delivery of Landsat data have benefitted Virginians in myriad ways.

Virginia↗

USGS1998

Characterization of hydrogeologic units using matrix properties, Yucca Mountain, Nevada

Determination of the suitability of Yucca Mountain, in southern Nevada, as a geologic repository for high-level radioactive waste requires the use of numerical flow and transport models. Input for these models includes parameters that describe hydrologic properties and the initial and boundary conditions for all rock materials within the unsaturated zone, as well as some of the upper rocks in the saturated zone. There are 30 hydrogeologic units in the unsaturated zone, and each unit is defined by limited ranges where a discrete volume of rock contains similar hydrogeologic properties. These hydrogeologic units can be easily located in space by using three-dimensional lithostratigraphic models based on relation- ships of the properties with the lithostratigraphy. Physical properties of bulk density, porosity, and particle density; flow properties of saturated hydraulic conductivity and moisture-retention characteristics; and the state variables (variables describing the current state of field conditions) of saturation and water potential were determined for each unit. Units were defined using (1) a data base developed from 4,892 rock samples collected from the coring of 23 shallow and 8 deep boreholes, (2) described lithostratigraphic boundaries and corresponding relations to porosity, (3) recognition of transition zones with pronounced changes in properties over short vertical distances, (4) characterization of the influence of mineral alteration on hydrologic properties such as permeability and moisture-retention characteristics, and (5) a statistical analysis to evaluate where boundaries should be adjusted to minimize the variance within layers. This study describes the correlation of hydrologic properties to porosity, a property that is well related to the lithostratigraphy and depositional and cooling history of the volcanic deposits and can, therefore, be modeled to be distributed laterally. Parameters of the hydrogeologic units developed in this study and the relation of flow properties to porosity that are described can be used to produce detailed and accurate representations of the core-scale hydrologic processes ongoing at Yucca Mountain.

Nevada↗

USGS2026

Recent scientific contributions by the U.S. Geological Survey in the San Francisco Bay and Sacramento–San Joaquin Delta Estuary

Introduction The San Francisco Bay and Sacramento–San Joaquin Delta Estuary (hereafter, Bay-Delta) is the largest estuary on the West Coast of the United States. The Bay-Delta covers more than 1,600 square miles and drains a watershed of more than 75,000 square miles, which is greater than 40 percent of California. The region surrounding the Bay-Delta is home to about 10 million people, and its habitats (fig. 1) support more than 800 plant and animal species. The waterways of the Bay-Delta are the central hub of California’s extensive freshwater delivery system, supplying water to more than 27 million Californians and 4 million acres of farmland in the Central Valley. The U.S. Geological Survey (USGS) is the primary science agency of the U.S. Department of the Interior, providing a broad range of Earth, water, biological, and mapping data and expertise to inform natural resource management across the country. This fact sheet focuses on research conducted by the USGS in the Bay-Delta region, mostly within the past 5 years. The fact sheet is organized across five major themes: water flow and water quality, fish and wildlife, wetland restoration, invasive species, and hazards. In each of these areas, the USGS works closely with Federal, State, and local agencies; academia; and non-governmental organizations to provide objective, evidence-based science. The data and knowledge gained from USGS research and monitoring are publicly available and are routinely used by agencies, including the U.S. Bureau of Reclamation, U.S. Army Corps of Engineers, U.S. Fish and Wildlife Service, California Department of Water Resources, California Department of Fish and Wildlife, California State Water Resources Control Board, Delta Stewardship Council, and many additional organizations and stakeholders to inform management of the Bay-Delta region and its resources.

California↗

USGS2023

Cursed? Why one does not simply add new data sets to supervised geothermal machine learning models

Recent advances in machine learning (ML) identifying areas favorable to hydrothermal systems indicate that the resolution of feature data remains a subject of necessary improvement before ML can reliably produce better models. Herein, we consider the value of adding new features or replacing other, low-value features with new input features in existing ML pipelines. Our previous work identified stress and seismicity as having less value than the other feature types (i.e., heat flow, distance to faults, and distance to magmatic activity) for the 2008 USGS hydrothermal energy assessment; hence, a fundamental question regards if the addition of new but partially correlated features will improve resulting models for hydrothermal favorability. Therefore, we add new maps for shear strain rate and dilation strain rate to fit logistic regression and XGBoost models, resulting in new 7-feature models that are compared to the old 5-feature models. Because these new features share a degree of correlation with the original relatively uninformative stress and seismicity features, we also consider replacement of the two lower-value features with the two new features, creating new 5-feature models. Adding the new features improves the predictive skill of the new 7-feature model over that of the old 5-feature model; albeit, that improvement is not statistically significant because the new features are correlated with the old features and, consequently, the new features do not present considerable new information. However, the new 5-feature XGBoost model has a statistically significant increase in predictive skill for known positives over the old 5-feature model at p = 0.06. This improved performance is due to the lower-dimensional feature space of the former than that of the latter. In higher-dimensional feature space, relationships between features and the presence or absence of hydrothermal systems are harder to discern (i.e., the 7-feature model likely suffers from the “curse of dimensionality”).

Geothermal Resources Council Transactions↗

USGS1995

Effects of waste-disposal practices on ground-water quality at five poultry (broiler) farms in north-central Florida, 1992-93

Waste-disposal areas such as chicken-house floors, litter stockpiles, fields that receive applications of litter, and dead-chicken pits are potential sources of nitrates and other chemical constituents in downward-percolating recharge water. Broiler- farms in north-central Florida are concentrated in a region where the Upper Floridan aquifer is unconfined and susceptible to contamination. Eighteen monitoring wells installed at five sites were sampled quarterly from March 1992 through January 1993. Increases in median concentrations of constituents relative to an upgradient well were used to determine the source of the nitrate at two sites. At these sites, increases in the median concentrations of nitrate as nitrogen in ground water in the vicinity of waste-disposal areas at these sites were: 5.4 mg/L for one chicken house; 9.0 mg/L for a second chicken house; 2.0 mg/L for a fallow field that received an application of litter; and, 2.0 mg/L for a dead-chicken pit. At the three remaining sites where the direction of local ground-water flow could not be ascertained, the sources of concentrations of nitrate and other constituents could not be determined. However, median nitrate concentrations in the vicinity of waste-disposal areas at these sites were: 45.5 mg/L for a set of two chicken houses; 3.0 mg/L for a stockpile area; and 2.1 mg/L for a hayfield that received an application of litter. The nitrate concentration in ground water in the vicinity of a field that had previously received heavy applications of litter increased from 3.0 mg/L to 105 mg/L approximately 4 months after receiving an application of commercial fertilizer. Increases in concentrations of organic nitrogen in ground water in the vicinity of waste-disposal areas may be related to the decomposition of litter and subsequent movement with downward percolating recharge water.

Florida↗

USGS2026

Variability and consistency in wildfire susceptibility: Insights from a national compilation

Background Wildfire risk in the United States is rising and remains a land management priority. The quantitative wildfire risk assessment (QWRA) framework integrates fuels, topography, weather and values at risk to estimate the potential change in value from wildfire. Within this, response functions (RFs) represent how values respond to fire intensity. These are often based on expert judgment, but variation across assessments is unclear. Aims This study uses data from the US Geological Survey (USGS) Wildfire Hazard and Risk Assessment Clearinghouse to characterize consistency and variation across categories and contexts. Methods We applied descriptive statistics to summarize RFs, using tables, box-and-whisker plots and heat maps stratified by highly valued resource or asset (HVRA) category and spatial scale. Key results RFs and value definitions vary, especially for ecosystem-related resources. Some functions, such as for buildings in the wildland–urban interface (WUI), translate well across contexts, while others require more input. Conclusions Some functions are broadly transferable, while others need customization. This analysis provides references and starting points for improvement to RFs in QWRAs. Interpretations Expanding the clearinghouse and dataset and building more transparency in expert elicitation can build trust among communities, agencies and end-users, and can support efficient use of limited resources to mitigate wildfire risk.

International Journal of Wildland Fire↗

USGS2025

Alteration mapping in granitic gneiss using handheld geophysical and geochemical instruments: Implications for iron oxide-apatite and rare earth elements exploration

The Adirondack Mountains of New York, U.S.A. contain iron oxide-apatite (IOA) mineral deposits with variable concentrations of rare earth elements (REE). The IOA mineral deposits are typically hosted in the Lyon Mountain Granite Gneiss and are spatially correlated with extensive Na metasomatism (albitization) of the surrounding country rocks, although some mineral deposits also occur in metagabbro, paragneiss, and anorthosite hosts. The location of albitization zones is key to finding new IOA mineral deposits and better understanding the mineralization processes associated with their genesis. However, the Na alteration zones are generally not visibly identifiable in outcrop or hand specimens because the color and textural changes are subtle and are thus difficult to map. Here, we discuss the results from testing two spectroscopic techniques (handheld, field gamma-ray spectroscopy, and portable X-ray fluorescence (pXRF)) to characterize albitization zones surrounding IOA mineral deposits. The gamma-ray and pXRF spectrometers successfully distinguished the relative intensity of alteration in the Lyon Mountain Granite Gneiss based on the K abundance. The measured K content decreases towards the IOA mineral deposits, and the magnitude and width of the gradient are similar along the strike of each mineral deposit. Elevated Th and U values are present in host rocks adjacent to REE-bearing IOA mineral deposits. The pXRF and gamma-ray spectrometer K values are remarkably consistent with laboratory-based, whole-rock XRF compositional data and, therefore, useful for semi-quantitative analysis. Notably, albitization aureoles are consistent around REE-rich and REE-poor mineral deposits, suggesting that saline fluids are essential for the petrogenesis of IOA mineral deposits but may not be critical to REE mineralization. Ultimately, this study demonstrates the utility of handheld gamma-ray and pXRF spectrometry for identifying otherwise cryptic albitization gradients associated with IOA mineral deposits in granitic gneiss.

New York↗

USGS2024

The 3D Elevation Program—Supporting New Hampshire’s economy

Introduction The topography of New Hampshire ranges from the Coastal Lowlands to the Eastern New England Upland to the White Mountains region. High-quality statewide elevation data are useful in managing this very diverse landscape. For example, the short coastline, including the Great Bay estuary and the Hampton-Seabrook marshes, is of disproportionately high value to New Hampshire’s tourist economy. The vulnerability of the coast to the effects of sea-level rise underscores the need for accurate, high-quality nearshore topographic elevation data and offshore bathymetric data to effectively manage the coast’s valuable resources, which include important fisheries, habitat, and infrastructure. Another important use for accurate elevation data in New Hampshire is in the evaluation of flood hazards and their potential environmental and infrastructure effects. This evaluation includes mapping of inundation and sediment transport, and assessing the associated costs of flooding. Addressing this challenge requires detailed knowledge of both surface topography and inland bathymetry. Other important activities having a substantial economic element and needing accurate elevation data include geologic resource assessment and hazard mitigation, urban and regional planning, infrastructure and construction management, and cultural resources preservation and management. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional model of the Earth’s surface and aboveground features.

New Hampshire↗

USGS1996

Analysis of nutrients in the surface waters of the Georgia–Florida Coastal Plain study unit, 1970–91

During the early phase of the Georgia-Florida National Water Quality Assessment study, existing information on nutrients was compiled and analyzed in order to evaluate the nutrient concentrations within the 61,545 square mile study unit. Evaluation of the nutrient concentrations collected at surface-water sites between October 1, 1970, and September 30, 1991, utilized the environmental characteristics of land resource provinces, land use, and nonpoint and point-source discharges within the study unit. Long-term trends were investigated to determine the temporal distribution of nutrient concentrations. In order to determine a level of concern for nutrient concentrations, the U.S. Environmental Protection Agency (USEPA) guidelines were used: (1) for nitrate concentrations, the maximum contaminant level in public-drinking water supplies (10 mg/L); (2) for ammonia concentrations, the chronic exposure of aquatic organisms to un-ionized ammonia (2.1 mg/L); (3) for total-phosphorus concentrations, the recommended concentration in flowing water to discourage excessive growth of aquatic plants (0.1 mg/L); and (4) for kjeldahl concentrations, however, no guidelines were available. For sites within the 10 major river basins, median nutrient concentrations were enerally below USEPA guidelines, except for total-phosphorus concentrations where 45 percent of the medians exceeded the guideline. The only median ammonia concentration that exceeded the guideline occurred at the Swift Creek site (3.4 mg/L), in the Suwannee River basin, perhaps due to wastewater discharges. For all sites within the Withlacoochee, Aucilla, and St. Marys River basins, median concentrations of nitrate, ammonia, and total phosphorus were below the USEPA guidelines. Nutrient data at each monitoring site within each major basin were aggregated for comparisons of median nutrient concentrations among major basins. The Ochlockonee and Hillsborough River basins had the highest median nutrient concentrations, the Aucilla River basin had the lowest. Median concentrations of nitrate and ammonia among all major basins were below USEPA guidelines. The median total-phosphorus concentrations for the following river basins exceeded the USEPA guideline: Hillsborough, St. Johns, Suwannee, Ochlockonee, Satilla, Altamaha, and Ogeechee. Although nutrient concentrations within the study unit were low, long-term increasing trends were found in all four nutrients. All 18 study-unit wide nitrate trends had increasing slopes ranging from less than 0.01 to 0.07 (mg/L)/yr. The range in slope for the 13 ammonia trends was -0.03 to 0.01 (mg/L)/yr with 6 increasing trends in the northern part of the study unit. Of the 17 total-phosphorus trends found in the study unit, 10 were found at sites where the median concentration exceeded the USEPA guideline. At these 10 sites, 4 sites had increasing trends with slopes ranging from less than 0.01 to 0.07 (mg/L)/yr, 5 sites had decreasing trends with slopes ranging from -0.01 to -0.24 (mg/L)/yr, and one site showed a seasonal concentration trend. Median nutrient concentrations were significantly different among the four land resource provinces: Southern Piedmont, Southern Coastal Plain, Coastal Flatwoods, and Central Florida Ridge. As a result, nutrient concentrations among basins with similar nutrient inputs but located within different land resource provinces are not expected to be the same due to differences in the combination of factors such as soil permeability, runoff rates, and stream channel slopes. This concept is an important consideration in designing a surface-water quality network within the study area. For the most part, the Coastal Flatwoods showed the lowest median nutrient concentrations and the Southern Coastal Plain had the highest median nutrient concentrations. Lower median nitrate concentrations in surface-water basins were associated with the forest/wetland land-use category and higher median concentrations of nitrate and ammonia with the urban category when land-use percentages were classified into four land-use categories (agriculture, forest/wetland, mixed, and urban). These results were reasonable based on expected high nutrient inputs from urban areas and low inputs from forested and wetland areas. However, the lack of association between high nutrient concentrations and the agricultural land-use category was not expected since high nutrient inputs are generally needed for agriculture production.

Florida, Georgia↗

USGS2025

Global maps of critical mineral production in 2023

Introduction The global production of many mineral commodities, especially critical minerals, is concentrated in a few countries that have mineral resources and the infrastructure necessary to mine and process those resources. For this reason, the type and amount of mineral production differ by country. For example, many countries produce such metallic ores as gold and silver, whereas only a few countries produce magnesium, niobium, platinum-group metals, and rare earths. The concentration of mining and processing in certain countries necessitates the existence of a global supply chain. A mineral supply chain is the sequence of mining and processing of minerals and manufacturing of products. Mineral supply chains are global in scale, complex, and dynamic. Supply chain data can be used to understand how a country’s mineral resources and various economic, technical, and environmental factors affect the complexity of global supply chains. This fact sheet summarizes the world’s leading countries (those accounting for 5 percent or more of a commodity’s global production in 2023) for production of select mineral commodities (mainly critical minerals) in the mining and processing stages. These countries and the minerals they produce are synthesized on global maps to communicate the status of, and potential risk to, mineral commodity supply chains from geographic production concentration. Trade data from United Nations Statistics Division (2025) is used to support assessments of the observed production data.

Fact Sheet↗

USGS2026

The Great Lakes Geologic Mapping Coalition—Working collaboratively to understand the geology of the Great Lakes Region

Introduction The Great Lakes Geologic Mapping Coalition (GLGMC), commonly referred to as the “Coalition,” is a partnership between the U.S. Geological Survey (USGS), the U.S. States of Illinois, Indiana, Michigan, Minnesota, New York, Ohio, Pennsylvania, and Wisconsin and the Canadian province of Ontario. The member States receive funding for geologic mapping work from the USGS National Cooperative Geologic Mapping Program (NCGMP), whereas Ontario participates as a nonfunded partner. The mission of the GLGMC is to produce three-dimensional (3D) geologic maps that depict unconsolidated sediments and near-surface bedrock in the Great Lakes region of North America. Geologic maps are the basis of most earth science investigations and help support resource exploration (energy, minerals, groundwater), natural hazard mitigation, infrastructure development, and land-use planning, all of which can be used to advance economic development and strengthen national security in the Great Lakes region. During the last few million years, the Great Lakes region has experienced repeated glacial advances and retreats, leaving behind extensive sediments, abundant natural resources, and widespread effects on the underlying bedrock geology (Swezey and others, 2022). Linked by shared histories of past glaciations, industrial agriculture, and legacy automotive, coal, steel, and manufacturing industries, the GLGMC member States collaborate to improve the understanding of the 3D distribution of the sediments overlying the region’s bedrock (fig. 1). Developing a comprehensive subsurface 3D framework of this glaciated terrain can provide earth science data to policymakers at all levels. These insights facilitate informed decisions on the exploration, use, and protection of vital resources, such as critical minerals, industrial materials, and aquifers, thereby supporting economic prosperity and the well-being of the citizens of this region. Since its inception in 1998, the Coalition has completed more than 100 geologic mapping projects across the Great Lakes region. Each project aims to deliver geologic maps, 3D datasets, and other information that improves understanding of the geology of the Great Lakes region, with an emphasis on economic and water resources. Key deliverables include 3D geologic maps and models typically portraying sediment thickness, often derived from top-of-bedrock and borehole data. These products are developed through a combination of fieldwork, subsurface modeling, and the collection and analysis of rock and sediment cores. To support Coalition goals, member States collaborate with scientists working on related STATEMAP, EDMAP, and FEDMAP projects. Coalition scientists also engage with Tribal Nations in the Great Lakes region to ensure that Tribal interests pertaining to Coalition work are addressed. Through this collaboration, the Coalition unites the efforts of State, Federal, and Tribal Nation stakeholders to advance geologic data production and enhance understanding of the geologic resources of the Great Lakes region.

Illinois, Indiana, Michigan, Minnesota, New York, ↗

USGS1998

Ground-water flow in the surficial aquifer system and potential movement of contaminants from selected waste-disposal sites at Cecil Field Naval Air Station, Jacksonville, Florida

As part of the Installation Restoration Program, Cecil Field Naval Air Station, Jacksonville, Florida, is considering remedialaction alternatives to control the possible movement of contaminants from sites that may discharge to the surface. This requires a quantifiable understanding of ground-water flow through the surficial aquifer system and how the system will respond to any future stresses. The geologic units of interest in the study area consist of sediments of Holocene to Miocene age that extend from land surface to the base of the Hawthorn Group. The hydrogeology within the study area was determined from gamma-ray and geologists' logs. Ground-water flow through the surficial aquifer system was simulated with a seven-layer, finite-difference model that extended vertically from the water table to the top of the Upper Floridan aquifer. Results from the calibrated model were based on a long-term recharge rate of 6 inches per year, which fell in the range of 4 to 10 inches per year, estimated using stream hydrograph separation methods. More than 80 percent of ground-water flow circulates within the surficial-sand aquifer, which indicates that most contaminant movement also can be expected to move through the surficial-sand aquifer alone. The surficial-sand aquifer is the uppermost unit of the surficial aquifer system. Particle-tracking results showed that the distances of most flow paths were 1,500 feet or less from a given site to its discharge point. For an assumed effective porosity of 20 percent, typical traveltimes are 40 years or less. At all of the sites investigated, particles released 10 feet below the water table had shorter traveltimes than those released 40 feet below the water table. Traveltimes from contaminated sites to their point of discharge ranged from 2 to 300 years. The contributing areas of the domestic supply wells are not very extensive. The shortest traveltimes for particles to reach the domestic supply wells from their respective contributing areas ranged from 70 to 200 years.

Florida↗

USGS2025

Comparison of hydrologic data and water budgets between 2003–08 and 2018–23 for the eastern part of the Arbuckle-Simpson aquifer, south-central Oklahoma

The Arbuckle-Simpson aquifer is divided spatially into three parts (eastern, central, and western). The largest groundwater withdrawals are from the eastern part of the Arbuckle-Simpson aquifer, which provides water to approximately 39,000 people in Ada and Sulphur, Oklahoma, and surrounding areas. The Arbuckle-Simpson aquifer, including the eastern part, is designated a sole source aquifer for its service area. Based primarily on data collected between 2003 and 2008, a series of comprehensive hydrologic studies of the Arbuckle-Simpson aquifer was published to provide the information necessary to perform groundwater-flow model simulations so that the Oklahoma Water Resources Board could determine how much water could be withdrawn from the aquifer while maintaining flow to springs and streams. As part of the Phase 1 studies, an aquifer water budget was developed from a numerical model for the period 2003–08. For this report, Phase 1 refers to the 2003–08 data collection period, although for some of the analyses, data collected prior to 2003 were used to inform model development work. Allocation of water from this aquifer was then established by the Oklahoma Water Resources Board in 2013. Additional well-spacing rules were also established by the Oklahoma Water Resources Board for sensitive sole source groundwater basins. To determine how the water budget for the eastern part of the Arbuckle-Simpson aquifer has changed over time, recently collected hydrologic data (2018–23) were compared to data collected during 2003–08. The analysis of changes in the aquifer water budget from 2003–08 to 2018–23 could help resource managers better understand changes in the overall balance of water in storage and the potential effects on streamflow, changes in groundwater levels, and the effects of different water uses in the aquifer area on available water in the eastern part of the Arbuckle-Simpson aquifer and streams overlying the eastern part of the Arbuckle-Simpson aquifer.

Oklahoma↗

USGS2025

Prospectivity mapping for geologic hydrogen

Geologic, or naturally occurring, hydrogen has the potential to become a new, low-carbon, primary energy resource. Often referred to as “white” or “gold” hydrogen, this gas occurs naturally in the Earth’s subsurface, similar to petroleum resources. However, unlike petroleum, which releases carbon dioxide when burned, burning hydrogen only produces water as a byproduct. Exploration for geologic hydrogen remains in an early stage and discoveries of high concentrations of subsurface hydrogen are still relatively rare. To facilitate research and exploration for this potential resource, this report presents the first publicly available prospectivity map of geologic hydrogen accumulations in the conterminous United States. Prospective regions are those regions in which all major components necessary for a hydrogen accumulation likely are present—a source of sufficient hydrogen generation, porous reservoirs for storage, and seals to prevent leakage. The midcontinent region of the United States and the central California coast are revealed as having high prospectivity. This analysis also identifies previously unrecognized prospective regions that may be favorable due to long distance lateral migration of subsurface hydrogen, such as the offshore eastern seaboard of the United States, and can provide a linkage between surface observations of hydrogen degassing and far-field source regions. The methodology developed to create this map is expandable and flexible and may be adapted to incorporate new concepts in the hydrogen system and for application to other regions of the world.

conterminous United States↗

USGS1995

Water quality of the Boca Raton canal system and effects of the Hillsboro Canal inflow, southeastern Florida, 1990-91

The City of Boca Raton in southeastern Palm Beach County, Florida, is an urban residential area that has sustained a constant population growth with subsequent increase in water use. The Boca Raton network of canals is controlled to provide for drainage of excess water, to maintain proper coastal ground-water levels to prevent saltwater intrusion, and to recharge the surficial aquifer system from which the city withdraws potable water. Most of the water supplied to the Boca Raton canal system and the surficial aquifer system, other than rainfall and runoff, is pumped from the Hillsboro Canal. The Biscayne aquifer, principal hydrogeologic unit of the surficial aquifer system, is highly permeable and there is a close relation between water levels in the canals and the aquifer. The amount of water supplied by seepage from the conservation areas is unknown. Because the Hillsboro Canal flows from Lake Okeechobee and Water Conservation Areas 1 and 2, which are places of more highly mineralized ground water and surface water, the canal is a possible source of contamination. Water samples were collected at 10 canal sites during wet and dry seasons and analyzed for major inorganic ions and related characteristics, nutrients, and trace elements. All concentrations were generally within or less than the drinking-water standards established by the Florida Department of Environmental Protection. The high concentrations of sodium and chloride that were detected in samples from the Boca Raton canal system are probably from the more mineralized water of the Hillsboro Canal. Other water-quality data, gathered from various sources from 1982 through 1991, did not indicate any significant changes nor trends. The data include pesticide and metal analyses of water samples and bottom sediments collected at four canal sites in the Boca Raton study area by the U.S. Geological Survey during 1982-84. The effects of the Hillsboro Canal on the water quality of the Boca Raton canal system are indicated by increased concentrations of sodium, chloride, dissolved solids, and total organic carbon. Concentrations of the constituents in the canal water generally decrease with distance from the Hillsboro Canal pumping station and are the result of dilution by receiving canal waters.

Florida↗

USGS1996

Technique for estimating magnitude and frequency of peak flows in Maryland

A convenient and reliable technique for estimating flood magnitudes is required for effective flood-plain management and for the efficient design of bridges, culverts, embankments, and flood-protection structures. Methods are presented for estimating peak-flow magnitudes of selected frequencies, ranging from 2 to 500 years, for all nontidal drainage basins in Maryland. The methods were developed by generalized least-squares regression techniques using data from 219 gaged basins in and near Maryland. The State is divided into five hydrologic regions: the Appalachian Plateaus and Allegheny Ridges region, the Blue Ridge and Great Valley region, the Piedmont region, the Western Coastal Plain region, and the Eastern Coastal Plain region. These regions correspond to the physiographic provinces of the State, with the exceptions that (1) the Coastal Plain Province is divided into two hydrologic regions, and (2) there is no distinct hydrologic region corresponding to the Valley and Ridge Province as it is divided into its constituent Allegheny Ridges and Great Valley subdivisions. Sets of equations for calculating peak discharges based on physical basin characteristics are provided for each of the regions. Based on the peak-flow equations, methods for estimating peak flows are presented for ungaged and gaged streams in Maryland. The methods and equations are supported by generalized least-squares analysis of basin and flood-frequency characteristics data from 219 drainage basins in and near Maryland. estimates for each of the five regions are calculated using combinations of the fol-lowing basin characteristics: drainage area, forest cover, basin relief, carbonate rock coverage, storage, and runoff-curve number. Drainage area contributes to the estimate in all five study regions. Carbonate rock coverage is used only in the Blue Ridge and Great Valley region. Storage and runoff-curve number are used solely in the Eastern Coastal Plain region. All other basin characteristics are used in two or more regions. Standard errors of estimate for the regression equations range from 19 to 31 percent in the Appalachian Plateaus and Allegheny Ridges region, 34 to 47 percent in the Blue Ridge and Great Valley region, 33 to 48 percent in the Piedmont region, 45 to 64 percent in the Western Coastal Plain region, and 36 to 42 percent in the Eastern Coastal Plain region.

Maryland↗