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USGS1996

The nature, distribution, and origin of gas hydrate in the Chile Triple Junction region

A bottom simulating reflector (BSR) is regionally distributed throughout much of the Chile Triple Junction (CTJ) region. Downhole temperature and logging data collected during Ocean Drilling Program (ODP) Leg 141 suggest that the seismic BSR is generated by low seismic velocities associated with the presence of a few percent free gas in a ??? 10 m thick zone just beneath the hydrate-bearing zone. The data also indicate that the temperature and pressure at the BSR best corresponds to the seawater/methane hydrate stability field. The origin of the large amounts of methane required to generate the hydrates is, however, problematic. Low total organic carbon contents and low alkalinities argue against significant in situ biogenic methanogenesis, but additional input from thermogenic sources also appears to be precluded. Increasing thermal gradients, associated with the approach of the spreading ridge system, may have caused the base of the hydrate stability field to migrate 300 m upwards in the sediments. We propose that the upward migration of the base of the stability field has concentrated originally widely dispersed hydrate patches into the more continuous hydrate body we see today. The methane can be concentrated if the gas hydrates can form from dissolved methane, transported into the hydrate zone via diffusion or fluid advection. A strong gradient may exist in dissolved methane concentration across the BSR leading to the steady reabsorbtion of the free gas zone during the upward migration of the BSR even in the absence of fluid advection.

Earth and Planetary Science Letters↗

USGS2018

Tracing enhanced oil recovery signatures in casing gases from the Lost Hills oil field using noble gases

Enhanced oil recovery (EOR) and hydraulic fracturing practices are commonly used methods to improve hydrocarbon extraction efficiency; however the environmental impacts of such practices remain poorly understood. EOR is particularly prevalent in oil fields throughout California where water resources are in high demand and disposal of high volumes of produced water may affect groundwater quality. Consequently, it is essential to better understand the fate of injected (EOR) fluids in California and other subsurface petroleum systems, as well as any potential effect on nearby aquifer systems. Noble gases can be used as tracers to understand hydrocarbon generation, migration, and storage conditions, as well as the relative proportions of oil and water present in the subsurface. In addition, a noble gas signature diagnostic of injected (EOR) fluids can be readily identified. We report noble gas isotope and concentration data in casing gases from oil production wells in the Lost Hills oil field, northwest of Bakersfield, California, and injectate gas data from the Fruitvale oil field, located within the city of Bakersfield. Casing and injectate gas data are used to: 1) establish pristine hydrocarbon noble-gas signatures and the processes controlling noble gas distributions, 2) characterize the noble gas signature of injectate fluids, 3) trace injectate fluids in the subsurface, and 4) construct a model to estimate EOR efficiency. Noble gas results range from pristine to significantly modified by EOR, and can be best explained using a solubility exchange model between oil and connate/formation fluids, followed by gas exsolution upon production. This model is sensitive to oil-water interaction during hydrocarbon expulsion, migration, and storage at reservoir conditions, as well as any subsequent modification by EOR.

California↗

USGS1998

Geospatial Technology Applications and Infrastructure in the Biological Resources Division

Executive Summary -- Automated spatial processing technology such as geographic information systems (GIS), telemetry, and satellite-based remote sensing are some of the more recent developments in the long history of geographic inquiry. For millennia, humankind has endeavored to map the Earth's surface and identify spatial relationships. But the precision with which we can locate geographic features has increased exponentially with satellite positioning systems. Remote sensing, GIS, thematic mapping, telemetry, and satellite positioning systems such as the Global Positioning System (GPS) are tools that greatly enhance the quality and rapidity of analysis of biological resources. These technologies allow researchers, planners, and managers to more quickly and accurately determine appropriate strategies and actions. Researchers and managers can view information from new and varying perspectives using GIS and remote sensing, and GPS receivers allow the researcher or manager to identify the exact location of interest. These geospatial technologies support the mission of the U.S. Geological Survey (USGS) Biological Resources Division (BRD) and the Strategic Science Plan (BRD 1996) by providing a cost-effective and efficient method for collection, analysis, and display of information. The BRD mission is 'to work with others to provide the scientific understanding and technologies needed to support the sound management and conservation of our Nation's biological resources.' A major responsibility of the BRD is to develop and employ advanced technologies needed to synthesize, analyze, and disseminate biological and ecological information. As the Strategic Science Plan (BRD 1996) states, 'fulfilling this mission depends on effectively balancing the immediate need for information to guide management of biological resources with the need for technical assistance and long-range, strategic information to understand and predict emerging patterns and trends in ecological systems.' Information sharing plays a key role in nearly everything BRD does. The Strategic Science Plan discusses the need to (1) develop tools and standards for information transfer, (2) disseminate information, and (3) facilitate effective use of information. This effort centers around the National Biological Information Infrastructure (NBII) and the National Spatial Data Infrastructure (NSDI), components of the National Information Infrastructure. The NBII and NSDI are distributed electronic networks of biological and geographical data and information, as well as tools to help users around the world easily find and retrieve the biological and geographical data and information they need. The BRD is responsible for developing scientifically and statistically reliable methods and protocols to assess the status and trends of the Nation's biological resources. Scientists also conduct important inventory and monitoring studies to maintain baseline information on these same resources. Research on those species for which the Department of the Interior (DOI) has trust responsibilities (including endangered species and migratory species) involves laboratory and field studies of individual animals and the environments in which they live. Researchboth tactical and strategicis conducted at the BRD's 17 science centers and 81 field stations, 54 Cooperative Fish and Wildlife Research Units in 40 states, and at 11 former Cooperative Park Study Units. Studies encompass fish, birds, mammals, and plants, as well as their ecosystems and the surrounding landscape. Biological Resources Division researchers use a variety of scientific tools in their endeavors to understand the causes of biological and ecological trends. Research results are used by managers to predict environmental changes and to help them take appropriate measures to manage resources effectively. The BRD Geospatial Technology Program facilitates the collection, analysis, and dissemination of data and informat

Information and Technology Report↗

USGS2003

Imaging spectroscopy: Earth and planetary remote sensing with the USGS Tetracorder and expert systems

Imaging spectroscopy is a tool that can be used to spectrally identify and spatially map materials based on their specific chemical bonds. Spectroscopic analysis requires significantly more sophistication than has been employed in conventional broadband remote sensing analysis. We describe a new system that is effective at material identification and mapping: a set of algorithms within an expert system decision‐making framework that we call Tetracorder. The expertise in the system has been derived from scientific knowledge of spectral identification. The expert system rules are implemented in a decision tree where multiple algorithms are applied to spectral analysis, additional expert rules and algorithms can be applied based on initial results, and more decisions are made until spectral analysis is complete. Because certain spectral features are indicative of specific chemical bonds in materials, the system can accurately identify and map those materials. In this paper we describe the framework of the decision making process used for spectral identification, describe specific spectral feature analysis algorithms, and give examples of what analyses and types of maps are possible with imaging spectroscopy data. We also present the expert system rules that describe which diagnostic spectral features are used in the decision making process for a set of spectra of minerals and other common materials. We demonstrate the applications of Tetracorder to identify and map surface minerals, to detect sources of acid rock drainage, and to map vegetation species, ice, melting snow, water, and water pollution, all with one set of expert system rules. Mineral mapping can aid in geologic mapping and fault detection and can provide a better understanding of weathering, mineralization, hydrothermal alteration, and other geologic processes. Environmental site assessment, such as mapping source areas of acid mine drainage, has resulted in the acceleration of site cleanup, saving millions of dollars and years in cleanup time. Imaging spectroscopy data and Tetracorder analysis can be used to study both terrestrial and planetary science problems. Imaging spectroscopy can be used to probe planetary systems, including their atmospheres, oceans, and land surfaces.

Journal of Geophysical Research E: Planets↗

USGS2002

A bibliography of terrain modeling (geomorphometry), the quantitative representation of topography: Supplement 4.0

Terrain modeling, the practice of ground-surface quantification, is an amalgam of Earth science, mathematics, engineering, and computer science. The discipline is known variously as geomorphometry (or simply morphometry), terrain analysis, and quantitative geomorphology. It continues to grow through myriad applications to hydrology, geohazards mapping, tectonics, sea-floor and planetary exploration, and other fields. Dating nominally to the co-founders of academic geography, Alexander von Humboldt (1808, 1817) and Carl Ritter (1826, 1828), the field was revolutionized late in the 20th Century by the computer manipulation of spatial arrays of terrain heights, or digital elevation models (DEMs), which can quantify and portray ground-surface form over large areas (Maune, 2001). Morphometric procedures are implemented routinely by commercial geographic information systems (GIS) as well as specialized software (Harvey and Eash, 1996; Köthe and others, 1996; ESRI, 1997; Drzewiecki et al., 1999; Dikau and Saurer, 1999; Djokic and Maidment, 2000; Wilson and Gallant, 2000; Breuer, 2001; Guth, 2001; Eastman, 2002). The new Earth Surface edition of the Journal of Geophysical Research, specializing in surficial processes, is the latest of many publication venues for terrain modeling. This is the fourth update of a bibliography and introduction to terrain modeling (Pike, 1993, 1995, 1996, 1999) designed to collect the diverse, scattered literature on surface measurement as a resource for the research community. The use of DEMs in science and technology continues to accelerate and diversify (Pike, 2000a). New work appears so frequently that a sampling must suffice to represent the vast literature. This report adds 1636 entries to the 4374 in the four earlier publications1. Forty-eight additional entries correct dead Internet links and other errors found in the prior listings. Chronicling the history of terrain modeling, many entries in this report predate the 1999 supplement. Coverage is representative from about 1800 through early–mid 2002. Papers increasingly are published exclusively or in duplicate on the Internet's World Wide Web; the dates given here for Web addresses (URLs) that lack a print publication indicate a Web site's last update or my last access of it. The bibliography is arranged alphabetically and thus is not readily summarized. This introduction cites about 500 entries, a third of them grouped under 24 morphometric topics, as a guide to the listing's contents. Continuing the practice of previous bibliographies in the series to provide more information on a few applications (see summary of past topics in Pike, 2000a), this report elaborates further on topographic data, putative new parameters, tectonic geomorphology/neo-orometry, biogeography, ice-cap morphometry, results from the Mars Global DEM, landslide-hazard mapping, terrain modeling as physics, Hack's law, and broad-scale computer visualization. The literature of some of these subjects is large, and none of the summaries is intended to more than introduce the topic and comment on some of the current contributions of terrain modeling. Closing the essay is a discussion of pre-1900 papers that trace the evolution of ridge-line and watercourse quantification by descriptive geometry, as well as comments on some new books and an on-line bulletin board.

Open-File Report↗

USGS2022

Modflow-setup: Robust automation of groundwater model construction

In an age of both big data and increasing strain on water resources, sound management decisions often rely on numerical models. Numerical models provide a physics-based framework for assimilating and making sense of information that by itself only provides a limited description of the hydrologic system. Often, numerical models are the best option for quantifying even intuitively obvious connections between human activities and water resource impacts. However, despite many recent advances in model data assimilation and uncertainty quantification, the process of constructing numerical models remains laborious, expensive, and opaque, often precluding their use in decision making. Modflow-setup aims to provide rapid and consistent construction of MODFLOW groundwater models through robust and repeatable automation. Common model construction tasks are distilled in an open-source, online code base that is tested and extensible through collaborative version control. Input to Modflow-setup consists of a single configuration file that summarizes the workflow for building a model, including source data, construction options, and output packages. Source data providing model structure and parameter information including shapefiles, rasters, NetCDF files, tables, and other (geolocated) sources to MODFLOW models are read in and mapped to the model discretization, using Flopy and other general open-source scientific Python libraries. In a few minutes, an external array-based MODFLOW model amenable to parameter estimation and uncertainty quantification is produced. This paper describes the core functionality of Modflow-setup, including a worked example of a MODFLOW 6 model for evaluating pumping impacts to a lake in central Wisconsin, United States.

Wisconsin↗

USGS1989

Multiple hydrothermal and metamorphic events in the Kidd Creek volcanogenic massive sulphide deposit, Timmins, Ontario: evidence from tourmalines and chlorites

Tourmaline and chlorite are the principal ferromagnesian silicate minerals in the Kidd Creek massive sulphide deposit. Tourmaline is most common in sphalerite-rich peripheral margins of the chalcopyrite stringer zone. Within the north orebody, samples typically contain <1% tourmaline, but small areas (hand-specimen scale) may have 10–20%. Chlorite is more widely distributed and in places constitutes 30–50% of rock volumes. Associated assemblages may include quartz, sulphides (principally chalcopyrite, sphalerite, and (or) pyrite), carbonate, albite, sericite, and rare fluorite, allanite, or zoisite(?).The tourmalines and chlorites record a series of multiple hydrothermal and metamorphic events. Paragenetic studies suggest that tourmaline was deposited during several discrete stages of mineralization, as evidenced by brecciation and cross-cutting relationships. Most of the tourmalines have two concentric growth zones defined by different colours (green, brown, blue, yellow). Some tourmalines also display pale discordant rims that cross-cut and embay the inner growth zones and polycrystalline, multiple-extinction domains. Late sulphide veinlets (chalcopyrite, pyrrhotite) transect the inner growth zones and pale discordant rims of many crystals. The concentric growth zones are interpreted as primary features developed by the main ore-forming hydrothermal system, whereas the discordant rims, polycrystalline domains, and cross-cutting sulphide veinlets reflect post-ore metamorphic processes.Detailed electron microprobe analyses of tourmalines show a wide compositional range, from Fe-rich dravite nearly to end-member schorl, with Fe/(Fe + Mg) ratios varying from 0.33 to 0.92; only minor amounts of Ca are present, yielding uniformly high Na/(Na + Ca) ratios of 0.84–0.99. Two sets of chemical zoning trends are identified in the tourmalines, involving systematic changes in Fe/(Fe + Mg), Na/(Na + Ca), Al, and Ti that are believed to reflect internal coupled substitutions (e.g., ⁮ + Ti = Na + Al) and local mineral equilibria (e.g., tourmaline–chlorite). Analyses of the pale discordant reaction rims show consistent depletion of Fe, Ca, and Ti, presumably by fluid–solid reactions during post-ore metamorphism.Chlorites also show an extensive range in composition, from ripidolite nearly to end-member daphnite, with Fe/(Fe + Mg) ratios of 0.43–0.98 and Si cation values of 5.00–5.39. Chlorites from the fringes of the footwall stringer zone have narrow compositional ranges, whereas chlorites near footwall rhyolite sills in the core of the stringer zone display major variations in Fe/(Fe + Mg) ratios, including one sample with a range of 0.68–0.95. The former group of chlorites has Fe/(Fe + Mg) ratios that correlate well with those of coexisting tourmalines (exclusive of late reaction rims). Data for the latter group, in contrast, fall off equilibrium K D curves, indicating that the tourmalines and chlorites within these samples are not in chemical equilibrium. The chlorites are believed to have been altered (overprinted) by Fe-rich hydrothermal fluids apparently generated during intrusion of the rhyolite sills. The tourmalines, however, are unaffected and retain primary chemical signatures.Variations in mineral proportions and mineral chemistry within the deposit mainly depend on fluctuations in temperature, pH, water/rock ratios, and amounts of entrained seawater. The major proposed control is mixing between high-temperature, Fe-rich end-member hydrothermal fluids and cold, Mg-rich entrained seawater. Fe/(Fe + Mg) variations in footwall tourmalines (and equilibrium chlorites) are believed to largely reflect the progressive infiltration of Mg-rich seawater into the margins and top of the hydrothermal system. The more Fe-rich compositions of Kidd Creek tourmalines relative to those from sediment-hosted massive sulphide deposits (e.g., Sullivan, British Columbia) may be related to the preferential generation of end-member hydrothermal fluids in proximal volcanic environments like that at Kidd Creek.

Ontario↗

USGS2019

Reimagining the potential of Earth observations for ecosystem service assessments

The benefits nature provides to people, called ecosystem services, are increasingly recognized and accounted for in assessments of infrastructure development, agricultural management , conservation prioritization, and sustainable sourcing. These assessments are often limited by data, however, a gap with tremendous potential to be filled through Earth observations (EO), which produce a variety of data across spatial and temporal extents and resolutions. Despite widespread recognition of this potential, in practice few ecosystem service studies use EO. Here, we identify challenges and opportunities to using EO in ecosystem service modeling and assessment. Some challenges are technical, related to data awareness, processing, and access. These challenges require systematic investment in model platforms and data management. Other challenges are more conceptual but still systemic; they are byproducts of the structure of existing ecosystem service models and addressing them requires scientific investment in solutions and tools applicable to a wide range of models and approaches. We also highlight new ways in which EO can be leveraged for ecosystem service assessments, identifying promising new areas of research. More widespread use of EO for ecosystem service assessment will only be achieved if all of these types of challenges are addressed. This will require non-traditional funding and partnering opportunities from private and public agencies to promote data exploration, sharing, and archiving. Investing in this integration will be reflected in better and more accurate ecosystem service assessments worldwide.

Science of the Total Environment↗

USGS2010

Early Pleistocene origin of reefs around Lanai, Hawaii

A sequence of submerged terraces (L1–L12) offshore Lanai was previously interpreted as reefal, and correlated with a similar series of reef terraces offshore Hawaii island, whose ages are known to be <500 ka. We present bathymetric, observational, lithologic and 51 87 Sr/ 86 Sr isotopic measurements for the submerged Lanai terraces ranging from −300 to −1000 m (L3–L12) that indicate that these terraces are drowned reef systems that grew in shallow coral reef to intermediate and deeper fore-reef slope settings since the early Pleistocene. Age estimates based on 87 Sr/ 86 Sr isotopic measurements on corals, coralline algae, echinoids, and bulk sediments, although lacking the precision (&sim;±0.23 Ma) to distinguish the age–depth relationship and drowning times of individual reefs, indicate that the L12–L3 reefs range in age from &sim;1.3–0.5 Ma and are therefore about 0.5–0.8 Ma older than the corresponding reefs around the flanks of Hawaii. These new age data, despite their lack of precision and the influence of later-stage submarine diagenesis on some analyzed corals, clearly revise the previous correlations between the reefs off Lanai and Hawaii. Soon after the end of major shield building (&sim;1.3–1.2 Ma), the Lanai reefs initiated growth and went through a period of rapid subsidence and reef drowning associated with glacial/interglacial cycles similar to that experienced by the Hawaii reefs. However, their early Pleistocene initiation means they experienced a longer, more complex growth history than their Hawaii counterparts.

Hawai'i↗

USGS2016

Bayesian estimation of magma supply, storage, and eruption rates using a multiphysical volcano model: Kīlauea Volcano, 2000–2012

Estimating rates of magma supply to the world's volcanoes remains one of the most fundamental aims of volcanology. Yet, supply rates can be difficult to estimate even at well-monitored volcanoes, in part because observations are noisy and are usually considered independently rather than as part of a holistic system. In this work we demonstrate a technique for probabilistically estimating time-variable rates of magma supply to a volcano through probabilistic constraint on storage and eruption rates. This approach utilizes Bayesian joint inversion of diverse datasets using predictions from a multiphysical volcano model, and independent prior information derived from previous geophysical, geochemical, and geological studies. The solution to the inverse problem takes the form of a probability density function which takes into account uncertainties in observations and prior information, and which we sample using a Markov chain Monte Carlo algorithm. Applying the technique to Kīlauea Volcano, we develop a model which relates magma flow rates with deformation of the volcano's surface, sulfur dioxide emission rates, lava flow field volumes, and composition of the volcano's basaltic magma. This model accounts for effects and processes mostly neglected in previous supply rate estimates at Kīlauea, including magma compressibility, loss of sulfur to the hydrothermal system, and potential magma storage in the volcano's deep rift zones. We jointly invert data and prior information to estimate rates of supply, storage, and eruption during three recent quasi-steady-state periods at the volcano. Results shed new light on the time-variability of magma supply to Kīlauea, which we find to have increased by 35–100% between 2001 and 2006 (from 0.11–0.17 to 0.18–0.28 km 3 /yr), before subsequently decreasing to 0.08–0.12 km 3 /yr by 2012. Changes in supply rate directly impact hazard at the volcano, and were largely responsible for an increase in eruption rate of 60–150% between 2001 and 2006, and subsequent decline by as much as 60% by 2012. We also demonstrate the occurrence of temporal changes in the proportion of Kīlauea's magma supply that is stored versus erupted, with the supply “surge” in 2006 associated with increased accumulation of magma at the summit. Finally, we are able to place some constraints on sulfur concentrations in Kīlauea magma and the scrubbing of sulfur by the volcano's hydrothermal system. Multiphysical, Bayesian constraint on magma flow rates may be used to monitor evolving volcanic hazard not just at Kīlauea but at other volcanoes around the world.

Hawai'i↗

USGS2022

Weakly supervised spatial deep learning for Earth image segmentation based on imperfect polyline labels

In recent years, deep learning has achieved tremendous success in image segmentation for computer vision applications. The performance of these models heavily relies on the availability of large-scale high-quality training labels (e.g., PASCAL VOC 2012). Unfortunately, such large-scale high-quality training data are often unavailable in many real-world spatial or spatiotemporal problems in earth science and remote sensing (e.g., mapping the nationwide river streams for water resource management). Although extensive efforts have been made to reduce the reliance on labeled data (e.g., semi-supervised or unsupervised learning, few-shot learning), the complex nature of geographic data such as spatial heterogeneity still requires sufficient training labels when transferring a pre-trained model from one region to another. On the other hand, it is often much easier to collect lower-quality training labels with imperfect alignment with earth imagery pixels (e.g., through interpreting coarse imagery by non-expert volunteers). However, directly training a deep neural network on imperfect labels with geometric annotation errors could significantly impact model performance. Existing research that overcomes imperfect training labels either focuses on errors in label class semantics or characterizes label location errors at the pixel level. These methods do not fully incorporate the geometric properties of label location errors in the vector representation. To fill the gap, this article proposes a weakly supervised learning framework to simultaneously update deep learning model parameters and infer hidden true vector label locations. Specifically, we model label location errors in the vector representation to partially reserve geometric properties (e.g., spatial contiguity within line segments). Evaluations on real-world datasets in the National Hydrography Dataset (NHD) refinement application illustrate that the proposed framework outperforms baseline methods in classification accuracy.

ACM Transactions on Intelligent Systems and Techno↗

USGS2020

Seismic and geodetic progression of the 2018 summit caldera collapse of Kīlauea Volcano

The 2018 eruption of Kīlauea volcano, Hawaiʻi, resulted in a major collapse of the summit caldera along with an effusive eruption in the lower East Rift Zone. The caldera collapse comprised 62 highly similar collapse cycles of strong ground deformation and earthquake swarms that ended with a magnitude 5 collapse event and one partial cycle that did not end with a collapse event. We analyzed geodetic and seismic data to better understand how the caldera collapse progressed over 3 months of activity, focusing on the cyclical activity. We identified 3 main phases of collapse: initial ring-fault activation and small explosions (Phase 1), an eastward shift in activity and freeing of the central piston (Phase 2), and a recoupling of the piston to the reservoir followed by relatively steady behavior until the eruption’s end (Phase 3). Additionally, we observed geodetic evidence of tangential motion from the localization of the main ring fault (Phase 2) and the formation of a major peripheral ring fault on the eastern side of the collapse caldera during Phase 3. Both geodetic and seismic parameters suggest that the collapse may have had an eastward-component of motion after the ring fault system had formed. The cyclical seismic and geodetic parameters show no obvious signs that the collapse was coming to an end, with the only notable change being a significant increase in the ratio of cyclical displacement to co-collapse displacement observed during the last complete cycle on GNSS stations outside the caldera region.

Hawaii↗

USGS2021

A novel automatic phenology learning (APL) method of training sample selection using multiple datasets for time-series land cover mapping

The long record of Landsat imagery, which is the cornerstone of Earth observation, provides an opportunity to monitor land use and land cover (LULC) change and understand the interactions between the climate and earth system through time. A few change detection algorithms such as Continuous Change Detection and Classification (CCDC) have been developed to utilize all available Landsat images for change detection and characterization at local or global scales. However, the reliable, rapid, and reproducible collection of training samples have become a challenge for time series land cover classification at a large scale. To meet the challenge, we proposed an automatic phenology learning (APL) method with the assumption that the temporal profiles of samples within the same land cover type are the same or similar at a local scale to generate evenly distributed training samples automatically. We designed the method to build land cover patterns for each category based on consensus samples derived from multiple existing scientific datasets including LANDFIRE's (LF) Existing Vegetation Type (EVT), USGS National Land Cover Database (NLCD), National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL), and National Wetlands Inventory (NWI). Then we calculated the Time-Weighted Dynamic Time Warping (twDTW) distance between any undefined samples and land cover patterns in the same geographical region as prior knowledge. Finally, we selected the optimal land cover category for each undefined sample from the land cover products based on the designed criteria iteratively using the twDTW distance as an indicator. The method was applied in the footprint of 10 selected Landsat Analysis Ready Data (ARD) tiles in the eastern and western conterminous United States (CONUS) to produce annual land cover maps from 1985 to 2017. The accuracy assessment and visual comparison revealed that the APL method can generate reliable training samples without any manual interpretation, producing better land cover results especially for the grass/shrub and wetland land cover classes. Applying the APL method, the overall accuracy of the annual land cover maps was improved by 2% over the accuracy of Land Change Monitoring, Assessment, and Projection (LCMAP) Collection 1.0 Science Products in the research regions. Our results also indicate that the APL method provides an approach for best use of different land cover products and meets the requirement of intensive sampling for training data collection.

Remote Sensing of Environment↗

USGS2021

Impact of precipitation and increasing temperatures on drought trends in eastern Africa

In eastern Africa droughts can cause crop failure and lead to food insecurity. With increasing temperatures, there is an a priori assumption that droughts are becoming more severe. However, the link between droughts and climate change is not sufficiently understood. Here we investigate trends in long-term agricultural drought and the influence of increasing temperatures and precipitation deficits. Using a combination of models and observational datasets, we studied trends, spanning the period from 1900 (to approximate pre-industrial conditions) to 2018, for six regions in eastern Africa in four drought-related annually averaged variables: soil moisture, precipitation, temperature, and evaporative demand ( E 0 ). In standardized soil moisture data, we found no discernible trends. The strongest influence on soil moisture variability was from precipitation, especially in the drier or water-limited study regions; temperature and E 0 did not demonstrate strong relations to soil moisture. However, the error margins on precipitation trend estimates are large and no clear trend is evident, whereas significant positive trends were observed in local temperatures. The trends in E 0 are predominantly positive, but we do not find strong relations between E 0 and soil moisture trends. Nevertheless, the E 0 trend results can still be of interest for irrigation purposes because it is E 0 that determines the maximum evaporation rate. We conclude that until now the impact of increasing local temperatures on agricultural drought in eastern Africa is limited and we recommend that any soil moisture analysis be supplemented by an analysis of precipitation deficit.

Earth Systems Science Dynamics↗

USGS2024

Unlearning Racism in Geoscience (URGE): Summary of U.S. Geological Survey URGE pod deliverables

The U.S. Geological Survey (USGS) is in a unique position to be a leader in diversity, equity, inclusion, and accessibility in the Earth sciences. As one of the largest geoscience employers, the USGS wields significant community influence and has a responsibility to adopt and implement robust, unbiased policies so that the science it is charged to deliver is better connected to the diverse communities it serves. Meaningful and effective improvements in implementation of diversity, equity, inclusion, and accessibility principles made within the USGS will be seen across the geoscience community. Despite this opportunity, however, the community, including the USGS, has struggled to diversify the geoscience workforce, which does not reflect the Nation’s diversity. This disparity suggests that the implementation of past policies did not achieve their desired outcomes in sustainable ways. The persistent lack of diversity across the geosciences and the racial justice protests of 2020 motivated a group of geoscience scholars to launch a global, virtual initiative known as Unlearning Racism in Geoscience (URGE) in the winter of 2021. The 16-week facilitated URGE curriculum was designed to highlight existing literature, share expert opinions, and foster discussion within groups (pods) around the world to build action plans for affecting change within their home institutions ( https://urgeoscience.org/ ). Whereas most of the approximately 4,500 participants were university faculty and students or from professional societies and nonprofit organizations, 6 pods totaling over 120 participants from the USGS joined the program—the largest participation of any Federal science agency. Summarizing the recommendations of over 100 USGS employees across the USGS who participated in URGE, this Circular represents a grassroots plan for making the USGS workforce more diverse and inclusive. To identify how peer-reviewed best practices could be implemented at the USGS, participants read existing literature, reviewed USGS policies and procedures, explored new and existing demographic data, and listened to and discussed primary interviews with scholars, all facilitated by the URGE program. This Circular leverages the efforts and momentum of the USGS URGE participants to catalyze and support positive, systemic change throughout the organization in a holistic way that represents an achievable departure from past policies that fell short of success. These recommendations are starting points. Reflecting the overall lack of diversity in the USGS workforce, the USGS URGE participants were predominantly White, meaning recommendations in this document can and should continue to evolve to include the lived perspectives and input from the broader USGS community. Finally, this summary document only highlights some of the key findings of these working groups. Additional details that may be more suitable to specific USGS Centers and programs can be found in the primary documents developed by each USGS URGE pod; a list of all registered pods can be found at https://urgeoscience.org/pods/ .

Circular↗

USGS2016

Ordinary kriging as a tool to estimate historical daily streamflow records

Efficient and responsible management of water resources relies on accurate streamflow records. However, many watersheds are ungaged, limiting the ability to assess and understand local hydrology. Several tools have been developed to alleviate this data scarcity, but few provide continuous daily streamflow records at individual streamgages within an entire region. Building on the history of hydrologic mapping, ordinary kriging was extended to predict daily streamflow time series on a regional basis. Pooling parameters to estimate a single, time-invariant characterization of spatial semivariance structure is shown to produce accurate reproduction of streamflow. This approach is contrasted with a time-varying series of variograms, representing the temporal evolution and behavior of the spatial semivariance structure. Furthermore, the ordinary kriging approach is shown to produce more accurate time series than more common, single-index hydrologic transfers. A comparison between topological kriging and ordinary kriging is less definitive, showing the ordinary kriging approach to be significantly inferior in terms of Nash–Sutcliffe model efficiencies while maintaining significantly superior performance measured by root mean squared errors. Given the similarity of performance and the computational efficiency of ordinary kriging, it is concluded that ordinary kriging is useful for first-order approximation of daily streamflow time series in ungaged watersheds.

Hydrology and Earth System Sciences↗

USGS2002

Environmental variation, vegetation distribution, carbon dynamics and water/energy exchange at high latitudes

The responses of high latitude ecosystems to global change involve complex interactions among environmental variables, vegetation distribution, carbon dynamics, and water and energy exchange. These responses may have important consequences for the earth system. In this study, we evaluated how vegetation distribution, carbon stocks and turnover, and water and energy exchange are related to environmental variation spanned by the network of the IGBP high latitude transects. While the most notable feature of the high latitude transects is that they generally span temperature gradients from southern to northern latitudes, there are substantial differences in temperature among the transects. Also, along each transect temperature co-varies with precipitation and photosynthetically active radiation, which are also variable among the transects. Both climate and disturbance interact to influence latitudinal patterns of vegetation and soil carbon storage among the transects, and vegetation distribution appears to interact with climate to determine exchanges of heat and moisture in high latitudes. Despite limitations imposed by the data we assembled, the analyses in this study have taken an important step toward clarifying the complexity of interactions among environmental variables, vegetation distribution, carbon stocks and turnover, and water and energy exchange in high latitude regions. This study reveals the need to conduct coordinated global change studies in high latitudes to further elucidate how interactions among climate, disturbance, and vegetation distribution influence carbon dynamics and water and energy exchange in high latitudes.

Journal of Vegetation Science↗

USGS2026

Understanding the resource potential of natural hydrogen on Earth: Scientific gaps, uncertainties and recommendations

A comprehensive scientific research roadmap is essential to bridge knowledge gaps and deepen the understanding of key geological, geochemical, and geophysical aspects of natural hydrogen (H 2 ) as a potential new energy resource. This paper reviews major scientific uncertainties on natural H 2 , suggesting research priorities, as a guide for defining exploration strategies, techniques, and data interpretation. The uncertainties concern all phases of the natural H 2 cycle, from generation (source rocks) through migration (advection and diffusion) and accumulation (reservoir and cap rocks) to the application and interpretation of subsurface and surface geochemical and geophysical exploration techniques. Understanding H 2 sources and generation rates (the amount of H 2 generated by a given volume of rock over time) is crucial for determining whether a geological H 2 system operates as a short-term dynamic system with rapid H 2 production and release, or as a conventional gas system with long-term accumulations, analogous to petroleum reservoirs. Preliminary estimates for serpentinisation, radiolysis, and organic matter degradation suggest that H 2 generation is not inherently fast, especially for non-hydrothermal continental systems (crystalline basement of shields, ophiolites, peridotite massifs, sedimentary basins), and long-term accumulations, like those of fossil natural gas systems, represent the most likely scenario. The mechanisms of H 2 migration through geological formations require application of fundamental principles of fluid-flow physics, distinguishing advection and diffusion, as well as their forms (from gas-phase, bubble flows to aqueous solutions). Additional studies of H 2 accumulation and retention in subsurface reservoirs could improve understanding of mechanisms of H 2 migration by focusing on the rock fluid-bearing properties and the factors affecting H 2 preservation, such as the presence of cap rocks impermeable to H 2 , pressure conditions, residence times, and microbial or abiotic consumption. Advanced techniques, including reservoir modelling, flow simulations, 3D imaging (micro-CT) of H 2 -bearing rocks, and extraction and analysis of gas occluded in rocks, can provide insights into the stability and potential recoverability of H 2 accumulations. The interpretation of surface exploration techniques, including gas geochemistry, geophysics, and remote sensing, long employed in mineral and energy resource exploration, is now being adapted for natural H 2 studies, but challenges remain in the data interpretation. Distinguishing H 2 seepage due to geological degassing from H 2 produced near the surface by modern microbial processes or artificial sources, such as hammering or drilling for soil-gas sampling, drilling into aquifers, and corrosion in boreholes, is an essential step in exploration. The simple detection of H 2 in soils, even in morphological structures like sub-circular depressions or “fairy circles”, cannot be cursorily interpreted as a signal of natural H 2 seepage from a deep source. A holistic geochemical approach, including isotopic analyses of gases associated with H 2 , is recommended to distinguish among the variety of possible H 2 origins. Observations of H 2 in wells should be interrogated to rule out possible artifacts such as corrosion and drill bit metamorphism. The integration of multiple geophysical methods, including seismic, gravimetric, magnetic, and electro-magnetic surveys, is recommended to mitigate interpretation ambiguities regarding the structure of a subsurface H 2 system (source and reservoir rocks, including fluid and gas storage), due to the non-uniqueness of rock-specific physical properties.

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