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Trends and environmental impacts of virtual water trade

Virtual water describes water embedded in the production of goods and offers meaningful insights about the complex interplay between water, trade and sustainability. In this Review, we examine the trends, major players, traded products and key drivers of virtual water trade (VWT). Roughly 20% of water used in global food production is traded virtually rather than domestically consumed. As such, agriculture dominates VWT, with livestock products, wheat, maize, soybean, oil palm, coffee and cocoa contributing over 70% of total VWT. These products are also driving VWT growth, the volume of which has increased 2.9 times from 1986 to 2022. However, the countries leading VWT contributions (with China, the United States, the Netherlands, Germany and India accounting for 34% of the global VWT in 2022) have remained relatively stable over time, albeit with China becoming an increasingly important importer. VWT can mitigate the effects of water scarcity and food insecurity, although there are concerns about the disconnect between consumers and the environmental impacts of their choices, and unsustainable resource exploitation. Indeed, approximately 16% of unsustainable water use and 11% of global groundwater depletion are virtually traded. Future VWT analyses must consider factors such as water renewability, water quality, climate change impacts and socioeconomic implications.

Nature Reviews Earth & Environment

Simulation of the impacts of spring diversions on streamflow in the Strawberry Creek watershed, San Bernardino County, California, using an integrated hydrological model

The Strawberry Creek watershed, situated in the San Bernardino Mountains of southern California, features a group of natural springs known as Arrowhead Springs that have been augmented with diversions in the form of sub-horizontal borings and tunnels. Understanding the impact of these structures on streamflow through groundwater capture is crucial for managing surface-water resources in this watershed. In this study we constructed the Strawberry Creek integrated hydrological model (SCIHM) to increase this understanding. The SCIHM is an integrated surface runoff and groundwater model that uses the coupled groundwater and surface-water flow model (GSFLOW), which is based on the integration of the precipitation-runoff modeling system (PRMS) and the modular groundwater flow model commonly called MODFLOW, version MODFLOW-2005 software to simulate surface runoff and infiltration and groundwater flow. The model has three layers, 263 rows, and 176 columns. The model area includes the Strawberry Creek and four adjacent watersheds. The PRMS model was calibrated using two streamflow gaging stations and the GSFLOW model was calibrated to reported spring diversion discharge and a sparse number of groundwater-level measurements. The SCIHM was run with and without diversions active and simulated streamflow was compared, finding that in the headwaters of Strawberry Creek about 35 percent of the diversion flow was captured from base flow.

EarthArXiv

Spatial distribution of API gravity and gas/oil ratios for petroleum accumulations in Upper Cretaceous strata of the San Miguel, Olmos, and Escondido Formations of the south Texas Maverick Basin—Implications for petroleum migration and charge history

The Maverick Basin of south Texas is currently undergoing active exploration and production of gas and oil from tight sandstone reservoirs. The most productive tight sandstones in the basin are in the Upper Cretaceous San Miguel, Olmos, and Escondido Formations. These units are second only to the Eagle Ford Shale in terms of cumulative production volumes. The structural history of the Maverick Basin, from rifting to subsidence to exhumation, has had a profound effect on the characteristics of these reservoirs and the petroleum resources contained therein. This U.S. Geological Survey review of the production history of these strata reflects a recent shift from conventional production to horizontal drilling (unconventional) that exploits low permeability reservoirs in previously overlooked areas of existing oil and gas fields in southern Texas, typically outside of established field boundaries. To investigate the physical properties of the Maverick Basin hydrocarbon accumulations, this case study compiled American Petroleum Institute (API) gravity measurements and calculated cumulative gas/oil ratios (GOR) for thousands of producing wells from the San Miguel, Olmos, and Escondido Formations. Maps were generated from the compiled well production data to show the spatial heterogeneity of API gravity and GOR values for the three formations within the Maverick Basin and immediately outside the basin to the northeast. Within the Maverick Basin, the spatial patterns of API gravity values indicate lighter oils downdip towards the southern basin edge. GOR values indicative of wet and dry gases within the basin are seen interspersed, with values that correspond to black and heavy oils. Differences in the spatial patterns of the petroleum properties within the Maverick Basin are interpreted as effects of Eocene basin inversion caused by Laramide orogenic deformation, and the resulting reservoir exhumation of basin strata. East of the Maverick Basin, spatial distributions of API gravity and GOR values show progressively heavier oils updip to the northwest, grading to dry gases downdip to the southeast, which correlates to the oil and gas windows of the underlying Eagle Ford Shale. Correlation of API gravity and GOR values from the San Miguel, Olmos, and Escondido Formations with thermal maturity data from the Eagle Ford Shale suggests that the Eagle Ford Shale is the petroleum source, and that petroleum migration was approximately vertical for areas to the east of the Maverick Basin. The discontinuity of API gravity and GOR properties within the Maverick Basin implies a complex petroleum charge history, possibly involving the remigration of petroleum and the addition of petroleum from other source intervals in Mexico, to the southwest. Depressurization of exhumed, overpressured reservoirs of the San Miguel, Olmos, and Escondido Formations can explain the intermittent occurrence of gas production throughout the southern Maverick Basin by exsolution of gas from formation brines and the resulting dry gas flushing of hydrocarbon-charged reservoirs. The introduction of dry gas through flushing can, in turn, explain why the patterns of API gravity and GOR values are so dissimilar in the Maverick Basin. This process has implications for possible future production of unconventional resources from undiscovered tight-gas reservoirs in strata of the San Miguel, Olmos, and Escondido Formations, and a different approach to petroleum exploration may be needed in the Maverick Basin relative to exploration techniques applied in other basins within the northern Gulf of Mexico.

Texas

USGS Geochron—A database of geochronological and thermochronological dates and data—Technical documentation

Geochronological and thermochronological data are essential for constraining the timing and rates of geological processes, supporting geologic mapping, natural hazard assessment, and resource exploration. The U.S. Geological Survey (USGS) Geochron Database is a centralized, relational database that integrates USGS and State geological survey data in accordance with the National Geologic Mapping Act of 1992 and its reauthorizations. This report documents the structure and development of the database, including its standardized schema, controlled vocabularies, and protocols for compiling legacy and newly published data. The database is designed to adhere to FAIR (Findable, Accessible, Interoperable, and Reusable) data principles and currently (2026) includes data from a wide range of geochronological and thermochronological methods. Public access is provided through the USGS Geochron Database Explorer, a browser-based geographic information system (GIS) interface, and through versioned data releases available on ScienceBase, which provide sample-level summary data and detailed analytical information. The USGS Geochron Database is structured to be extensible, supporting the inclusion of additional methods and data types as they are compiled. This format ensures long-term utility and aligns with the Mapping Act’s directive to create a national archive of geochronological information that adds interpretive value to geologic map data. Its design reflects a commitment to data transparency, scientific reproducibility, and national geoscience priorities.

Data Report

The projected exposure and response of a natural barrier island system to climate-driven coastal hazards

Accelerating sea level rise (SLR) and changing storm patterns will increasingly expose barrier islands to coastal hazards, including flooding, erosion, and rising groundwater tables. We assess the exposure of Cape Lookout National Seashore, a barrier island system in North Carolina (USA), to projected SLR and storm hazards over the twenty-first century. We estimate that with 0.5 m of SLR, 47% of current subaerial barrier island area would be flooded daily, and the 1-year return period storm would flood 74%. For 20-year return period storms, over 85% is projected to be flooded for any SLR. The modelled groundwater table is already shallow (< 2 m deep), and while projected to shoal to the land surface with SLR, marine flooding is projected to overtake areas with emergent groundwater. Projected shoreline retreat reaches an average of 178 m with 1 m of SLR and no interventions, which is over 60% of the current island width at narrower locations. Compounding these hazards is subsidence, with one-third of the study area currently lowering at > 2 mm/yr. Our results demonstrate the difficulty of managing natural barrier systems such as those managed by federal park systems tasked with maintaining natural ecosystems and protecting cultural resources.

North Carolina

A methods framework for evaluating measurement consistency across spectrometers for multispectral uncrewed aerial system vegetation mapping applications

The U.S. Geological Survey collects remote sensing data to support national scientific assessments of natural resources, hazards, and landscape change. Spectrometers and spectroradiometers are essential for gathering point-based spectral measurements used in applications such as uncrewed aerial systems (UAS) multispectral image calibration, validation, and analysis. Evaluating how different instruments perform in laboratory and field environments helps determine whether they provide consistent, interoperable measurements. Such verification can expand access to spectral ground data during UAS operations by allowing scientists to use alternative instruments when budgets, logistics, or field conditions limit options. We propose and test a methodological framework for evaluating spectrometers for measurement consistency during UAS multispectral vegetation mapping applications. There are three central evaluation components to the framework: laboratory, field, and relative to UAS multispectral imagery. By evaluating the instruments in both relatively controlled and uncontrolled environments, we thoroughly examine measurement consistency and when/why measurements may differ. We opportunistically selected two instruments for a case study in a coastal marsh setting: a compact laboratory spectrometer we modified for field use and a field-ready spectroradiometer. The instruments produced consistent measurements in both environments. We found differences between the field spectra and UAS spectra that likely reflect the perspectives of ground vs. aerial data and indicate that further radiometric calibration may be needed.

Massachusetts

Drone-based radiometric surveys provide high-resolution mine waste characterization

Airborne radiometric surveys use passive geophysical techniques to characterize geochemical variations at or near earth’s surface. These methods have been used for a variety of mapping applications, including mineral resource evaluation. However, detailed characterization of smaller geologic targets, including mine waste features, requires flying at lower altitudes and with tighter line spacing than is feasible with traditional aircraft. Here, a small uncrewed aircraft system (sUAS) equipped with a radiometric sensor was used to acquire high-resolution gamma-spectrometry over small mine waste features and a low-grade stockpile in southwestern New Mexico. The sUAS radiometric system mapped local variability within each survey area and revealed ~2–10 m wide zones where radioelements K, Th, and U may be elevated 2–10× the surrounding material. Additionally, the sUAS radiometric data revealed radioelement variability across survey sites, which correlated reasonably well with variability seen in geochemical samples at each survey site, even though samples collected from individual sites showed high local variability. The sUAS data characterized local heterogeneity within mine waste and other small geologic targets at scales of a few meters to tens of meters, which is not possible with traditional crewed aircraft, and with continuity of coverage that is not possible with ground surveys, thus filling a key gap in geophysical survey spatial resolution.

New Mexico

Spatially referenced watershed models for the binational Red–Assiniboine River Basin: Bayesian vs frequentist comparison

Excess nutrient loading remains a leading cause of declining water quality in lakes, estuaries, and coastal waters worldwide, with global economic costs of US$200 billion – US$2 trillion annually from impacts on fisheries, tourism, freshwater resources, and water treatment. Our study focuses on total phosphorus (TP) in Lake Winnipeg and its binational Red-Assiniboine River Basin, where nutrient inputs have degraded water quality and increased cyanobacterial blooms. These changes pose ecological, public health, and economic risks. We applied a spatially referenced watershed model with a hybrid statistical-mechanistic structure partitioning annual nutrient loads into land-use export, land-to-water delivery, and in-reservoir decay. Bayesian and traditional frequentist model calibrations were compared. In the frequentist model, coefficients for agricultural inputs, forests /wetlands, stream channels, precipitation, and reservoir losses were statistically significant, whereas coefficient for wastewater was not. In contrast, all variables were successfully calibrated using the Bayesian approach. Model results delineate TP-export hotspots across the basin, showing that 54–62% of TP originates from the U.S., with agricultural sources ranging 62–72%—highlighting the importance of agriculture-focused Best Management Practices. Given the global relevance of nutrient-driven water-quality challenges, our results highlight Bayesian calibration for robust risk assessment and adaptive nutrient management.

Red–Assiniboine River Basin

Assessing natural recharge in Indian Wells Valley, California: A Basin Characterization Model case study

The communities in Indian Wells Valley (IWV), in the northern Mojave Desert in California, rely on groundwater for domestic and agricultural use. Mountain front recharge from the surrounding Sierra Nevada is the main source of natural recharge to the valley. Increased urbanization, agricultural development, and groundwater pumping during recent decades put IWV in a state of critical overdraft. The U.S. Geological Survey Basin Characterization Model, version 8 (BCMv8) was used to evaluate historical and future climate and hydrologic conditions in IWV. The BCMv8 estimated natural recharge in IWV at 10.7 million cubic meters (Mm 3 ) per year for the period from 1981 to 2010. Future patterns of water balance variables using three future climate scenarios, hot-wet, hot-dry, and warm-moderately wet, were calculated for mid-century (2040–69) and end-of-century (2070–99) periods. Results for both wet models projected an increase in recharge in both periods, whereas the hot-dry model projected a decrease in recharge in both periods. All models reported a large increase in seasonal variability in recharge, indicating more future availability and frequent occurrences of drought years. All climate scenarios projected an increase in climatic water deficit in both periods. These increases in irrigation demand and variability of water supply highlight the importance of strategic management planning for the sustainability of water resources in IWV.

California

Geophysical characterization of an alkaline‑carbonatite complex using gravity and magnetic methods at Magnet Cove, Arkansas, USA

The Magnet Cove alkaline‑carbonatite complex (MCC), located in the Ouachita Mountains of south-central Arkansas in the United States, hosts an extensive variety of rare rock types and critical mineral resources with physical properties (density and magnetization) that contrast significantly with the sedimentary rocks into which they have intruded. Newly acquired ground-based gravity and magnetic data were used to develop two-dimensional and three-dimensional geophysical models of the Cretaceous-aged Magnet Cove intrusive complex. The models reveal that the MCC: (1) widens out at middle crustal depths to as much 22 km across, and may reach a depth of 20 km; (2) has a total volume (exposed and subsurface) that may be over 800 km 3 ; (3) is likely connected at depth to other intrusions in the Arkansas alkaline province; and (4) has a geometry that is aligned with pre-existing structures such as the Reelfoot rift and the Ouachita orogenic belt, some of which were likely structurally controlled by the Precambrian crystalline basement and the continent-ocean transition zone buried beneath the Ouachita orogen. For the first time, the magnetic models of the MCC account for the presence of strong remanent magnetization. This results in a geophysical workflow necessary to accurately interpret magnetic anomalies over the much larger Arkansas alkaline province, its geologic and structural framework, and critical mineral potential.

Arkansas

Data gap analysis for estimation of agricultural return flows in the Upper Gunnison River Basin, Colorado

The Gunnison River and many tributaries in the Upper Gunnison River Basin provide water to irrigate agricultural crops. The application of irrigation water can recharge some aquifers locally by water percolating below the root zone and eventually flowing back to the stream or river through the subsurface. Diverting surface water for irrigation reduces streamflow during the irrigation season but can provide temporary storage of water and supplement streamflow after the snowmelt runoff season. Understanding the timing and quantity of agricultural return flows could help resource managers make informed decisions and adapt to potential changes in water management and availability that could affect irrigation practices. In 2024, the U.S. Geological Survey, in cooperation with the Upper Gunnison River Water Conservancy District, began a study to characterize agricultural return flows in the Upper Gunnison River Basin by using endmember mixing analysis and developing a groundwater model. Both approaches require data from multiple sources, but data gaps exist in the East River study reach and other reaches of interest (Ohio Creek, Tomichi Creek, and Cochetopa Creek). The East River Basin, which is the initial focus of the study, has fewer data gaps than the other basins. Data gaps could be addressed by installing additional surface water and groundwater monitoring sites, making regular streamflow measurements on tributaries, and completing tests to characterize local aquifer properties.

Colorado

New Hampshire and Landsat

At its widest point, a mere 80 miles separate the eastern and western borders of New Hampshire. Its northern and southern borders are just 175 miles apart. Even so, few States can boast as much rugged natural beauty per mile as the Nation’s fifth smallest. Nestled within New Hampshire are 93 State parks teeming with moose, Ursus americanus (Pallas, 1780; black bears), coyotes, beavers, river otters, and foxes. The largest section of White Mountain National Forest cuts across north-central New Hampshire, drawing visitors to its lakes, streams, mountain peaks, and hardwood forests. New Hampshire also is home to Lake Winnipesaukee, the State’s largest lake, notable for its floating post offices, the annual “ice-out” contest that sees residents vying to guess the date its surface ice dissipates, and its supporting role in films such as “On Golden Pond” and “What About Bob?” However, the scenic forests of New Hampshire face challenges in the form of invasive species such as Lymantria dispar (Linnaeus, 1758; spongy moth), Adelges piceae (balsam woolly adelgid), and Agrilus planipennis (emerald ash borer). In recent years, New Hampshire’s lakes and streams have seen more cyanobacterial blooms as well. The U.S. Geological Survey Landsat Program offers a consistent, reliable, and historically unmatched source of Earth observations that can aid in the mapping, monitoring, and management of New Hampshire’s land and water resources. Here are a few ways Landsat data have been used in the Granite State.

New Hampshire

A new water temperature modeling approach to predict thermal habitat suitability for nonnative cichlids in Florida rivers

As global temperatures increase, the spatiotemporal arrangement of thermal habitats in Florida rivers may shift, creating the potential for greater dispersal and establishment of nonnative tropical freshwater fishes. To understand how water temperature changes may affect the spatial distribution of these nonnative species, more effective water temperature prediction models are necessary. Currently, most models employ either a generalized air–water temperature relationship or require expensive and complicated tools to measure hydrometeorological factors (e.g. groundwater input). Thus, we developed a novel modeling approach that is accurate, accessible, and cost-effective in allowing fisheries managers to project water temperatures in rivers across Central and North Florida. To characterize the potential for nonnative fishes to spread northward, we evaluated two hardy and abundant species currently found primarily in South Florida: Mayan Cichlid ( Mayaheros urophthalmus ) and Oscar ( Astronotus ocellatus ). Our results show an increase in thermally suitable winter days for both species in 10 of 11 rivers studied, consistent with predicted water temperature warming under 16 climate-change scenarios spanning different levels of air temperature warming (+1 °C, +2 °C, +3 °C, +4 °C) and precipitation/groundwater thermal sensitivity (0, 0.33, 0.66, 1). Considering resource limitations, fisheries managers can use our water temperature modeling approach to predict effects of climate change on Mayan Cichlid and Oscar survival, growth, and dispersal and take actions to manage potential northward movement of these species.

Florida

Gaps in water quality modeling of hydrologic systems

This review assesses gaps in water quality modeling, emphasizing opportunities to improve next-generation models that are essential for managing water quality and are integral to meeting goals of scientific and management agencies. In particular, this paper identifies gaps in water quality modeling capabilities that, if addressed, could support assessments, projections, and evaluations of management alternatives to support ecosystem health and human beneficial use of water resources. It covers surface water and groundwater quality modeling, dealing with a broad suite of physical, biogeochemical, and anthropogenic drivers. Modeling capabilities for six constituents (or constituent categories) are explored: water temperature, salinity, nutrients, sediment, geogenic constituents, and contaminants of emerging concern. Each constituent was followed through the coupled atmospheric-hydrologic-human system, with prominent modeling gaps described for a diverse array of relevant inputs, processes, and human activities. Commonly identified modeling gaps primarily fall under three types: (1) model gaps, (2) data gaps, and (3) process understanding gaps. In addition to potential solutions for addressing specific individual modeling limitations, some broad approaches (e.g., enhanced data collection and compilation, machine learning, reduced-complexity modeling) are discussed as ways forward for tackling multiple gaps. This gap analysis establishes a framework of diverse approaches that may support improved process representation, scale, and accuracy of models for a wide range of water quality issues.

Water

Estimating domestic self-supplied water use in Rhode Island, 2014–21

Water withdrawal from private groundwater wells is often unaccounted for in water planning studies, and water from private wells can be a source of exposure to environmental contaminants. The sizes of populations that depend on private wells for domestic water use and the amounts of water that are withdrawn from these wells are generally poorly represented in data collection efforts because of the challenges of locating, metering, or gathering withdrawal information from individual property owners. To address this problem, the U.S. Geological Survey, in cooperation with the Rhode Island Water Resources Board, estimated the volume of water withdrawn from domestic self-supply wells and the populations who use them for the State of Rhode Island at a 30-meter pixel spatial resolution and one-month temporal resolution between July 2014 and June 2021. The number of people reliant on domestic self-supply wells has increased in Rhode Island over the study period; however, the statewide estimate of total water withdrawal has not statistically increased. Withdrawals from private wells are largest in the inland areas of the western part of the State, and the towns of Scituate and Charlestown have the highest estimated withdrawals. Statewide monthly withdrawals ranged from 3.987 million gallons per day in March 2018 to 7.767 million gallons per day in September 2016. The median per capita domestic water use rate was 46.0 gallons per capita per day.

Rhode Island

Review and synthesis of the applications of machine learning to coalbed methane recovery

Over the last 30 years, a substantial literature has evolved on the use of machine learning (ML) to assess, predict, and improve the efficiency of coalbed methane (CBM) recovery. In the United States, the production of CBM declined as shale gas production matured, but CBM continues to be an important energy resource in other parts of the world. ML applications that have the potential to improve CBM reservoir management and production forecasts, and to increase exploration and operational efficiency, are still of significant interest. The integration of geostatistical techniques into the CBM ML applications has been largely absent but represents an opportunity for improvement. The literature demonstrates the widespread interest in, and applicability of, ML algorithms applied to CBM problems, and that they continue to result in improvements in predictive performance. However, (1) much of the research is more academic than operational, (2) many results are based on simulations, or small or proprietary datasets, (3) ML performance information can be inconsistent and sometimes entirely omitted, (4) most methodologies are unique to the specific CBM situation and likely not generalizable, (5) no standard data repositories are available to directly compare the performance of competing algorithms, and (6) the spatial component is often omitted. Finally, relatively new ML protocols involving causality analysis and reinforced learning, as well as hybrid workflows combining both supervised and unsupervised learning, are anticipated to dominate the future investigations. Integration of geostatistical and geospatial analysis with ML should enhance performance.

Book chapter

Seismic tomography 2023

Seismic tomography is the most abundant source of information about the internal structure of the Earth at scales ranging from a few meters to thousands of kilometers. It constrains the properties of active volcanoes, earthquake fault zones, deep reservoirs and storage sites, glaciers and ice sheets, or the entire globe. It contributes to outstanding societal problems related to natural hazards, resource exploration, underground storage, and many more. The recent advances in seismic tomography are being translated to nondestructive testing, medical ultrasound, and helioseismology. Nearly 50 yr after its first successful applications, this article offers a snapshot of modern seismic tomography. Focused on major challenges and particularly promising research directions, it is intended to guide both Earth science professionals and early‐career scientists. The individual contributions by the coauthors provide diverse perspectives on topics that may at first seem disconnected but are closely tied together by a few coherent threads: multiparameter inversion for properties related to dynamic processes, data quality, and geographic coverage, uncertainty quantification that is useful for geologic interpretation, new formulations of tomographic inverse problems that address concrete geologic questions more directly, and the presentation and quantitative comparison of tomographic models. It remains to be seen which of these problems will be considered solved, solved to some extent, or practically unsolvable over the next decade.

Bulletin of the Seismological Society of America

Geologic map of the Greater Antilles and Virgin Islands

Introduction The geologic map of the Greater Antilles and Virgin Islands is a compilation of information from the literature, integrated to provide a seamless geologic map of the region. This map was prepared to serve as a base map for a mineral resource assessment of the region. Several small-scale regional geologic maps of the region have been prepared in the past. This report supersedes an earlier version of the geologic map of the Greater Antilles and the Virgin Islands that was released as U.S. Geological Survey (USGS) Open-File Report 2019–1036. For this report, the regional geologic overview shown on sheet 1 covers Cuba; the island of Hispaniola, which includes Haiti and Dominican Republic; Jamaica; the Cayman Islands; Puerto Rico; and the U.S. and British Virgin Islands. Sheet 2 shows the geology of Cuba and Cayman Islands, sheet 3 the geology of Jamaica, sheet 4 the geology of Hispaniola, and sheet 5 the geology of Puerto Rico and Virgin Islands. Accompanying the maps are three tables: table 1 lists the map units (in alphabetical order by map-unit label), their ages, and the countries or territories in which they can be found. These are listed in alphabetical order for ease in locating unit names from the symbols on the maps. Table 2 is a list of sources for the geologic map compilation of Puerto Rico. Table 3 shows formations in the Devil’s Race Course Group of Jamaica.

Greater Antilles, Virgin Islands