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1,228 records · Page 2Linked to original sources
USGS2025

Refinements to the attenuated propagation of local earthquake shaking (APPLES) ground-motion-based earthquake early warning algorithm

We refined the Attenuated ProPagation of Local Earthquake Shaking (APPLES) ground-motion-based earthquake early warning (EEW) approach, and directly compare APPLES performance with that of the source-characterization-based U.S. ShakeAlert EEW system for a suite of historical earthquakes in the U.S. West Coast and Japan. APPLES is an extension of the Propagation of Local Undamped Motion (PLUM) algorithm in which observed shaking intensity at seismic stations is used to forward-predict intensity distributions to surrounding areas using an attenuation model derived from an intensity prediction equation. We test new configuration options within APPLES, such as using the second highest estimated ground motion rather than the maximum, to better match median ground-motion observations and reduce alerts for small magnitude earthquakes, both of which are key alerting priorities within ShakeAlert. We evaluate these configurations alongside ShakeAlert by comparing the ground-motion estimation accuracy and available warning times relative to station observations and ShakeMap distributions. Our preferred APPLES configuration produces accurate ground-motion estimates and corresponds better with median observations compared to ShakeAlert’s estimates. This preferred configuration substantially reduces alert issuance for M < 5.0 earthquakes compared to the previous APPLES configuration, and alert-release criteria can further restrict alerts to primarily M ≥ 5.5 earthquakes without requiring magnitude estimation. Prioritizing matching median-observed ground motions may reduce APPLES warning times compared to configurations that were tuned to avoid missed alerts (such as those that use the maximum estimated ground motions), which can lead to shorter warning times compared to ShakeAlert for the same alert threshold. However, station-based warning time assessments demonstrate that APPLES can outperform ShakeAlert for high target thresholds. APPLES is a simple, independent EEW approach that may improve the robustness of EEW for the West Coast of the U.S.

California, Oregon, Washington↗
USGS2025

Gulf Coast Basin CORE-CM initiative final report

The Bureau of Economic Geology at the University of Texas at Austin (UT-BEG) is leading the Gulf Coast Carbon Ore, Rare Earth, and Critical Minerals (CORE-CM) Initiative to assess the potential to produce critical minerals (CMs), including rare earth elements (REEs) from coal, coal ash, and produced water related to oil and gas production, and related materials (alumina processing waste [red mud], heavy mineral sands, graphite, and zeolite) within the Gulf Coast Basin. This project represents the first phase in a long-term program and provides reconnaissance data that will be foundational for future work by assessing resources and suggesting plans to be conducted in future work and expanding stakeholder engagement. The project includes several tasks designed to identify, characterize, and assess several necessary aspects for development of CMs and REEs in the Gulf Coast Basin.

Gulf Coast basin↗
USGS2021

Remote sensing-based actual evapotranspiration assessment in a data-scarce area of Brazil: A case study of the Urucuia Aquifer System

The large groundwater reserves of the Urucuia Aquifer System (UAS) enabled agricultural development and economic growth in the western Bahia State, in northeastern Brazil. Over the last several years, concern has grown around the aquifer’s diminishing water levels, and water balance (WB) studies are in demand. Considering the lack of measured actual evapotranspiration (ET a ), a major component of the water cycle, this work uses the Operational Simplified Surface Energy Balance (SSEBop) model to estimate ET a , and compares it to basin-scale estimates from the Soil Moisture Accounting Procedure (SMAP) monthly model and from an annual WB closure method, based on gridded meteorological data and the Gravity Recovery and Climate Experiment (GRACE) product. Additionally, a comparative assessment of different versions of the SSEBop parameterization was performed. Moderate Resolution Imaging Spectroradiometer (MODIS) imagery was used to implement eight different versions of the SSEBop algorithm over the UAS between 2000 and 2013. SSEBop and SMAP ET a yielded similar seasonal patterns, with correlation coefficient (r) up to 0.65, mean difference (MD) of 0.8 mm/month and mean absolute difference (MAD) of 18.5 mm/month. Comparison of SSEBop annual ET a estimates to annual SMAP and WB closure estimates yielded low MD (12.1 and −7.3 mm/year, respectively) and MAD (82.5 and 82.8 mm/year, respectively), but also low r values (0.00 and 0.37, respectively). The comparison of the different SSEBop versions indicated the need to incorporate a calibration step of the aerodynamic heat resistance (r ah ) parameter. SSEBop results were also used for land cover and drought monitoring. Analysis indicates that agriculture, associated with an increasing trend of atmospheric evaporative demand, is responsible for the decrease in groundwater levels and streamflow in the studied time period.

Urucuia Aquifer System↗
USGS2026

Regional characterization of coal resources in the Gulf Coast Coal Region—In support of coal as a potential source for critical minerals and rare earth elements

There is increasing interest in extracting critical minerals (CM), including rare earth elements (REE), from coals in the United States to address the overreliance on imported REE. The Gulf Coast and the Fort Union regions are the two major lignite-bearing regions within the United States. Recent REE and CM studies of the lignite in these regions have indicated that the coals may be a viable source material for REE and CM extraction. To evaluate in-place coal as a potential source of REE and CM, the coal resources need to be quantified. This study presents the results of a regional analysis of Gulf Coast Coal Region lignite and bituminous coal resources that might be available as potential sources of REE and CM. The resource analysis used kriging methods to develop isopleth maps of cumulative coal thickness throughout the region using data from drill holes and measured mine and outcrop sections for a total of 31,181 data points. The estimated total remaining coal resource in the Gulf Coast Coal Region is about 83 billion metric tons in the upper 90 meters (approximately 300 feet) of the subsurface. The current estimate of remaining coal resources includes approximately 1.88 billion metric tons of coal that have been extracted in the region since 1983. Texas accounted for 39 percent (32 billion metric tons) of the remaining total resource, followed by Mississippi (24 percent, 20 billion metric tons ), Louisiana (14 percent, 12 billion metric tons), Tennessee (10 percent, 8.5 billion metric tons), and Arkansas (6 percent, 5.1 billion metric tons). Alabama, Georgia, Kentucky, and Missouri each accounted for less than 5 percent of the total resource; Georgia had the smallest resource estimated at 7 million metric tons. Here we report the first known statewide lignite resource estimates for Georgia, Kentucky (820 million metric tons), and Missouri (1,800 million metric tons). A comparison of the results of this study with those of previous Gulf Coast Coal Region and Fort Union Coal Region resource studies is difficult because each study used different data sources, assessment methodologies, overburden depths, and qualifying coal thicknesses.

Alabama, Arkansas, Florida, Georgia, Illinois, Lou↗
USGS2026

Metallurgical coal—Deposits, production, resources, market dynamics, and supply chain risks

Plain Language Summary Metallurgical coal (met coal; consumed to produce coke for steelmaking) must meet specific chemical and physical specifications. In 2023, the conterminous United States produced 66 million short tons (mst) of met coal, consumed 15.85 mst domestically, exported 51.1 mst, and imported 0.7 mst. Most met coal was produced in the Appalachian Basin, but there are also resources that meet the specifications for met coal in the Western United States.

conterminous United States↗
USGS2026

Geochemical geodatabase of sedimentary strata (coal, coal-adjacent rocks, tuffaceous oil shale, phosphate-rich rocks) and produced water in the Uinta region, Utah and Colorado

The Geochemical Geodatabase of Sedimentary Strata (Coal, Coal-adjacent Rocks, Tuffaceous Oil Shale, Phosphate-rich Rocks) and Produced Water in the Uinta Region, Utah and Colorado, consists of compiled datasets acquired as part of the Carbon Ore, Rare Earth, and Critical Mineral (CORE-CM) Uinta Region assessment funded by the U.S. Department of Energy (DEFE0032046, 2021–2024; Birgenheier et al., 2024). The CORE-CM assessment focused on providing comprehensive geological and geochemical characterization of current and prospective sedimentary-hosted resources including coal, oil shale, phosphatic limestone, and produced water from oil and gas targets present in eastern Utah and northwestern Colorado (Figure 1). This Data Series includes a geodatabase that consists of analytical geochemical data collected September 2021 through December 2024 via portable X-ray fluorescence (pXRF), and laboratory measured analyses produced by inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma optical emission spectroscopy (ICP-OES). The coal-related geochemical data are derived primarily from the Cretaceous Blackhawk Formation and Ferron Sandstone of Utah, and the Mesaverde Group of Colorado. Additional non-coal resources assessed include oil shale-bearing strata of the Eocene upper Green River Formation (Utah and Colorado), phosphate-rich limestone of the Permian Park City Formation (Utah) and produced water from oil and gas-bearing strata of the Eocene Green River and Wasatch Formations (Uinta Basin) and the Pennsylvanian Paradox Formation (Paradox Basin) (Table 1). The CORE-CM assessment included a wide range of lithologies present in the coal, oil shale, and phosphate geologic resource systems whether or not the specific lithology has current economic value. Geochemical analyses of produced water from oil and gas wells focused on current and emerging hydrocarbon targets in the central Uinta Basin and northern Paradox Basin. A total of 13,092 geochemical analyses from these geologic systems is provided in the included geodatabase. A series of coal quality data (e.g., composition and maceral analyses) is also included in the database and was digitized from archived coal samples from the Utah Geological Survey (Appendix A).

Colorado, Utah↗
USGS2025

Regional characterization of coal resources in the U.S. Gulf Coast

There is increasing interest in extracting critical minerals (CM), including rare earth elements (REE), from coals in the United States to address the overreliance on imported REE. The U.S. Gulf Coast and the Williston basins are the two major lignite-bearing basins within the country. Recent REE and CM studies of the lignite in these basins have indicated that the coals may be a viable source material for REE and CM extraction. To evaluate in-place coal as a potential source of REE and CM, the coal resources need to be quantified. This study presents the results of a regional analysis of the U.S. Gulf Coast lignite and bituminous coal resources that might be available as potential sources of REE and CM. The resource analysis used kriging methods to develop isopleth maps of cumulative coal thickness throughout the region using data from 31,181 drill holes and other data points. The estimated total coal resource in the Gulf Coast is about 83 billion metric tons in the upper 90 m (~ 300 ft) of the subsurface. Texas accounted for 40 percent (32 billion metric tons) of the total resource, followed by Mississippi (24 %, 20 billion metric tons), Louisiana (14 %, 12 billion metric tons), Tennessee (10 %, 8.5 billion metric tons), and Arkansas (6 %, 5.1 billion metric tons). The remaining states each accounted for less than 5 percent of the total resource. Georgia had the smallest resource estimated at 7 million metric tons. Here we report the first known state-wide lignite resource estimates for Georgia, Kentucky (820 million metric tons), and Missouri (1,800 million metric tons). A comparison of the results of this study with those of previous Gulf Coast and Williston Basin resource studies is difficult because each study used different data sources, assessment methodologies, overburden depths, and qualifying coal thicknesses. Coal-power electric generation has sharply decreased in past decades and mining of these coals for CM and REE could provide additional co-products such as activated carbon and other uses such as fertilizer (soil enhancer).

EarthArXiv↗
USGS2026

Remote sensing enables basin-scale inventories of coal mine methane

Underground coal mines are important global sources of methane, but emission estimates are uncertain. We show that emission estimates for individual mines from aircraft remote-sensing surveys in the United States agree within 40% with direct measurements used for national emission reporting (IPCC Tier 3 estimate). Such direct measurements are unavailable in most countries, which rely on estimated emission factors (EFs) applied to coal-production rates. We find that EFs from IPCC Tier 1 and the Model for Calculating Coal Mine Methane (MC2M) methods overestimate U.S. emissions 3-fold due to incorrect dependence on mine depth. An IPCC Tier 2 method using measured basin-specific mine gas content agrees with direct emission measurements but does not account for gob well emissions and requires gas content data that are generally unavailable. We show that aircraft remote sensing for a small sample of mines can successfully estimate basin-specific EFs for ventilation shafts and gob wells, enabling estimates of basin- and national-scale emissions. We discuss how the method can be applied with satellite remote sensing to quantify coal emissions worldwide.

Alabama, Colorado, Kentucky, New Mexico, Ohio, Pen↗
USGS2025

Waning greenhouse gas emissions from U.S. Federal lease coal production by the mid-21st century

This study presents estimates of future years (2024–2051) United States Federal lease coal production and the resulting greenhouse gas (GHG) emissions from the combustion, transport, and mining of that fuel. Results from the coal production estimate indicate a decline in production from Federal leases; with known production of 240 million short tons (mtn) in 2023 and a projected decline to 34.0 mtn by 2051, which represents a reduction to 14.2% of the 2023 value. In parallel with this projection, total GHG emissions are estimated to decrease from 402.2 million metric tons of carbon dioxide equivalent (MMT CO 2 eq.) in 2024 to 55.0 MMT CO 2 eq. in 2051, a decline to 13.7% of 2024 emissions estimates. The reductions in coal production and emissions are mainly the result of planned coal combustion power plant closures, with major projected closures in 2037 and 2048. However, GHG emissions estimates for future years can be uncertain as they rely heavily on coal production estimates from operators' public business plans and other publicly available resources. Forward looking plans of this type are subject to significant changes if economic and political factors deviate from current information. Results suggest that average GHG emissions over the time series breakout to 95% end point combustion, 3.7% transportation combustion emissions, and 1.3% fugitive emissions, although there is uncertainty associated with these figures. Uncertainty stemming from production projections, sector distributions, and emissions factors on the future emissions estimates increases with time, ranging from −28% to +48% within the 2024–2051 timeframe.

Alabama, Colorado, Montana, North Dakota, Utah, Wy↗
USGS2026

Spatio-temporal modeling for assessing geoenergy resources: A workflow applied to gas in place variation in coal beds

The ability to estimate spatio-temporal changes in hydrocarbon reservoir properties and energy resources within pore volumes is essential for optimizing production, reservoir management, geologic energy storage, and safety in underground mining operations. In coal seams, predicting remaining methane gas-in-place (GIP) is critical for quantifying producible gas and improving mine safety and productivity through effective ventilation planning. Although such changes are commonly evaluated using physics-based numerical simulation models, these approaches often require extensive data, calibration effort, and time. This study presents a spatio-temporal geostatistical modeling approach that bridges the gap between purely spatial models and full numerical simulations. The method is applied to a case study of coal seam degasification in the Mary Lee coal group, Black Warrior Basin, Alabama, USA, to estimate GIP evolution over time within a selected mining district. The analysis uses published data from prior natural gas production history-matching of degasification using vertical wells. Empirical spatial and temporal statistics were calculated for reservoir pressure and water saturation, and spatio-temporal variogram models were fitted to experimental variograms. These models provided the structural basis for spatio-temporal kriging, integrated with spatial estimates of time-invariant parameters (porosity, density, and thickness) to estimate GIP. This approach enabled estimation of GIP changes over time, including periods without data. Boxplots of GIP estimates indicated systematic depletion and decreasing spatial variability, reflecting the impacts of degasification. Comparison with cumulative gas production from empirical well records showed approximately 85% agreement based on a relative similarity metric. Spatio-temporal GIP estimates were also used to estimate methane emissions to longwall ventilation systems and compared with reported emissions from the U.S. EPA Greenhouse Gas Reporting Program, showing similar distributions (≈80%) given data limitations. Overall, this integrated modeling approach provides time-dependent GIP estimates with broader implications for resource assessment applications.

Alabama↗
USGS2026

Detecting snow avalanche activity using infrasound: Hooker Valley, New Zealand

Snow avalanches pose considerable hazards to people and infrastructure in alpine environments. Traditional avalanche monitoring relies on meteorological data and visual observations, which can be limited in scope and timeliness. Infrasound offers a promising complementary monitoring tool by detecting the low-frequency sound waves generated by avalanches. Here, we present infrasound and camera observations during a 50-day field campaign in the Hooker Valley of Aoraki/Mount Cook National Park, New Zealand. Our study detected seven avalanches with the cameras, whereas the infrasound system identified only one of these events, which was the largest and occurred under conditions that likely favoured infrasound propagation. The infrasound system recorded numerous other events not captured by the cameras, indicating the benefit of further investigation to determine their sources. These findings highlight the potential of infrasound technology for detecting avalanches and providing broad spatial coverage, capturing events in areas not monitored by cameras, while also showcasing limitations in infrasound capabilities. The limited detection of smaller avalanches underscores the opportunity for further research to enhance detection capabilities and understand environmental influences such as snow cover and wind noise. Overall, this study emphasises the utility of multidisciplinary monitoring techniques to improve avalanche detection in alpine environments.

Hooker Valley↗
USGS2025

Temporal and spatial comparison of coal mine ventilation methane emissions and mitigation quantified using PRISMA satellite data and on-site measurements

Emission monitoring at the facility level (bottom-up, BU) is key for accurate reporting of coal mine methane (CMM) emissions. Recent advances in aerial and satellite observations (top-down, TD) indicate that these methods have the potential to support CMM emissions monitoring and reporting of, as well as track the effectiveness of, mitigation actions. That said, studies have shown discrepancies between BU and TD estimations. Performing TD monitoring with concurrent BU measurements at the same mines may help address the observed discrepancies and improve quantification methods to narrow the gap between BU and TD data. This paper presents a comparison of concurrent BU-TD methane emission fluxes monitored from two ventilation shafts at a southwestern Virginia, USA, longwall mine to complement the existing body of studies on satellite-based monitoring of coal mines by incorporating continuous ground-based monitoring with concurrent TD monitoring of methane emission fluxes to address the gap and provide valuable insights into temporal emission patterns. The shafts were monitored on multiple dates between 2020 and 2023. BU monitoring was performed at the exhaust fans, while TD quantifications used PRISMA hyperspectral satellite data and two different wind reanalysis datasets (i.e., GEOS-FP and ERA5). This mine also offered a unique opportunity for BU-TD comparisons before and after ventilation air methane (VAM) oxidizer operation, which was installed at one of the shafts in 2022. The results showed that TD-estimated mean fluxes were generally lower than BU data, which were attributed to quantification difficulties associated with the low albedo caused by heavy vegetation and the terrain of the area. However, despite the discrepancies in mean emissions, both the interquartile range and the data range of the distributions generally overlapped, and the estimates correctly showed the emission trends.

Virginia↗
USGS2026

Subsurface vertical connectivity shapes solute transport to montane streams: Insights from watershed-scale geophysics-informed modeling

Headwater catchments provide essential water and nutrients to downstream ecosystems. The timing and evolution of their transport is shaped in part by the “invisible” subsurface structure but have been largely unexplored at the watershed scale. This raises a fundamental question: how and to what extent does subsurface structure influence streamflow and solute transport in montane watersheds? Here, we test controls of three-dimensionally resolved subsurface structure on solute transport, which reflects source waters and water residence time. We integrate the geophysically mapped architecture of Coal Creek, a headwater catchment in the Colorado River Basin, into numerical flow-transport models. Our results reveal greater vertical connectivity elongates flow paths and enhances deep groundwater contributions to streams, therefore substantially influencing the timing and magnitude of solute transport. In contrast, watershed-integrated outlet discharge can be predicted without high-resolution subsurface information. These findings demonstrate incorporating subsurface architecture is critical for predicting ecosystem health and contaminant transport.

Colorado↗
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, ↗
USGS2025

Review: The hydrogeology of critical mineral resources relevant to the energy transition

Attaining the goals of the international treaty on climate change (the Paris Agreement) will greatly increase the demand for the critical minerals required to implement clean-energy technologies. This poses both challenges and opportunities to the hydrogeologic community from several perspectives. Here, important insights that the hydrogeological sciences have to offer for mineral exploration, mineral production, and addressing environmental issues related to mining and mine decommissioning are summarized. This study focuses on copper, cobalt, lithium, and rare earths to represent the broad spectrum of critical minerals and illustrate their relevance by referring to projected demands and production rates. The current understanding of the hydrogeologic processes that form major deposits of these minerals are then summarized. Ore is defined as the naturally occurring material from which minerals of economic value can be extracted, where most ore deposits are the products of complex hydrogeologic couplings between fluid flow, heat transport, solute transport, chemical reactions, and mechanical deformation. Exploration models for the discovery of deeper, hidden deposits are potentially informed by hydrogeologic theory and hydrogeochemical processes. Hydrogeologic understanding and methods are also essential to production and recovery. Longstanding challenges are mine dewatering and (conversely) mine water supply, as well as mineral-extraction practices such as spoil heap leaching and in situ mining. New challenges arise from element extraction from subsurface brines. Finally, the quantity of water use and potential environmental impacts of mining on water quality are at the core of ‘social license’: the approval and acceptance of society to mining activities.

Hydrogeology Journal↗
USGS2026

Statewide surficial geologic map of Nebraska underscores Quaternary landscape evolution from the High Plains to the Central Lowland

Surficial geologic mapping in Nebraska has been conducted primarily at the 1:24,000 scale since the mid-1990s, although there have also been limited efforts to map generalized Quaternary and surficial geology within the state and the region. We compiled and evaluated disparate maps (1:24,000–1:1,000,000) and datasets—including geologic, soil and soil parent material, and geomorphic maps as well as LiDAR derivatives—to produce a single 1:500,000 scale surficial geologic map of Nebraska that is the first of its kind. This new map provides a coarse-scale surficial geologic map that will be incorporated into a nationwide U.S. Geological Survey Quaternary geologic map. It also reflects the variation and uniqueness of physical landscapes in the state, where the Great Plains and Central Lowland physiographic provinces meet, further developing a richer interdisciplinary understanding of regional geomorphology in the heart of North America.

Nebraska↗
USGS2025

A crosswalk of the 2015 World Terrestrial Ecosystems to the International Union for the Conservation of Nature Global Ecosystem Typology Framework

To support ecosystem mapping and accounting applications, we aligned the 2015 U.S. Geological Survey/Esri/The Nature Conservancy-World Terrestrial Ecosystems (WTEs) with the International Union for Conservation of Nature Global Ecosystem Typology (GET) framework. This process, known as “crosswalking,” enabled the development of a global map of GET level 3 Ecosystem Functional Groups (EFGs) at a 250-meter spatial resolution. Crosswalking involved manually assigning 1,781 biogeographically stratified WTEs to their most probable EFG based on similarities in climate, terrain, vegetation, and geographic distribution. We compared attributes of the WTE dataset with summary characteristics of the EFGs. The resulting crosswalked global map of International Union for Conservation of Nature GET ecosystems is intended to be useful for standardizing ecosystem classification and reporting under frameworks such as the Kunming-Montreal Global Biodiversity Framework and the United Nations System of Environmental-Economic Accounting. We discuss key challenges in reconciling non-identical classifications, such as many-to-one relationships and variation in data quality.

Open-File Report↗
USGS2025

Systematic approach to prioritize wells for effective groundwater monitoring and management in the Arkansas Headwaters Basin, Colorado, USA

Study region The Arkansas Headwaters Basin, an intermountain basin in the Southern Rocky Mountains of North America. Study focus Our specific focus is choosing a set of wells to support a possible future regional groundwater-surface water model that would support water management. We present a three-step process using multiple criteria to score, predict, and choose prioritized wells that capture the full distribution of data including extremes. The three-step process provides accessible visualizations, fiscally efficient well prioritization, and screening useful for subsequent groundwater modeling. The novelty of the proposed methodology is the systematic approach integrating a scoring and a predictive approach to support a selection path. The systematic approach may be broadly adapted for other basins. New hydrological insights for the region Understanding regional hydrology hinges on efficient collection of hydrologic data that captures the relevant dynamics including extremes. The present study, a case study for a particular basin in the Southern Rocky Mountains, is the first use of a scripted (R software) strategy to select an economical and representative set of monitoring wells. Our findings suggest caution when using proximity as a proxy for correlation, because proximal wells in the same geologic formation and similar depths are not always correlated. In the Arkansas Headwaters Basin, subsurface geology may be less influential on groundwater elevations than broader hydrologic influences, such as regional drought.

Colorado↗