Search USGS⌕ Search

SEARCH · Search USGS

Results for “Earth Surface Processes and Landforms”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

1,665 records · Page 8Linked to original sources
USGS2026

A framework for integrating spatiotemporal deep learning methods with landsat for annual land cover and impervious surface mapping

Land cover information is essential for understanding Earth’s surface dynamics and how vegetation, water, soil, climate, and terrain interact. The National Land Cover Database (NLCD) has been the authoritative source for consistent U.S. land cover mapping. To extend NLCD’s temporal resolution and reduce production latency, we developed the Land Cover Artificial Mapping System (LCAMS)—a prototype spatiotemporal deep learning framework piloted as the foundation for the new Annual NLCD. LCAMS builds on concepts from legacy NLCD and the U.S. Geological Survey Land Change Monitoring, Assessment, and Projection (LCMAP) initiatives. It employs a loosely coupled two-stage architecture consisting of independent but functionally interdependent spatial and temporal models. Spatial models extract per-year information from Landsat data, while the temporal models refine the spatial outputs to enforce inter-annual consistency—critical for reliable land change monitoring. LCAMS produces annual 30 m resolution land cover and impervious surface outputs, with region-specific fine-tuning to generalize across diverse landscapes and temporal dynamics. Validation was conducted using an independent dataset of 1925 randomly sampled plots from five U.S. Landsat Analysis Ready Data (ARD) tiles spanning 1985-2021, selected for spatial and temporal variability. This dataset was used consistently to evaluate LCAMS, Legacy NLCD, and LCMAP. Using the NLCD legend, LCAMS achieved 72.1 ± 1.60% overall agreement, compared to 71.1 ± 1.7% agreement for Legacy NLCD. Using the LCMAP legend, LCAMS achieved 83.4 ± 1.22% agreement, compared to 84.6 ± 1.11% agreement for LCMAP. Overall, LCAMS delivers comparable accuracy while offering higher thematic resolution, longer temporal coverage, and automated production of annual 30 m CONUS land cover.

Remote Sensing of Environment↗
USGS2025

Zircon as a pathfinder to REE mineralization

Carbonatites and alkaline silicate rocks are major primary sources of the rare earth elements (REE) and other critical metals, such as Nb. Despite the economic significance of these rocks, their formation and the processes of REE enrichment are poorly understood. Here, statistical analysis of a global dataset demonstrates that zircon geochemistry is a powerful recorder of REE metallogenesis and a potential pathfinder for REE deposits. Zircons from REE and Nb fertile intrusions lack Eu anomalies and have elevated Gd/Yb and Th/Yb, indicating they crystallised from magmas that originated from deep, oxidised and enriched mantle sources. Complexes with Nb enrichment have low U/Nb, reflecting an enriched mantle source, whereas high U/Nb in REE-only fertile intrusions suggest a subduction-metasomatised mantle source. Machine learning models demonstrate high accuracy in classifying zircon from barren and fertile deposits. Classification of detrital zircons shows that REE-enriched deposits correlate with supercontinent assembly, whereas Nb fertile complexes are associated with supercontinent breakup. This approach offers a new, mineral to global scale, petrologic and exploration tool that enhances understanding of REE metallogenesis.

Geochemical Perspectives Letters↗
USGS2024

Wave propagation in layered soil deposits

Recent advances in the general theory of viscoelastic waves and rays in layered media provide a rigorous mathematical framework for site-specific, soil-response models used for earthquake resistant design. The advances provide general closed-form anelastic solutions for the classic problems of the response of a stack of soil layers to S and P waves, ray theory for reflected and refracted waves, Rayleigh- and Love-Type surface waves, and head waves. These general solutions valid for anelastic media regardless of the amount of material damping yield new insights regarding the characteristics of seismic waves and their ray paths that are not provided by conventional models. They provide corresponding numerical ground-response models and ray-tracing computation algorithms that account for changes in velocity and attenuation of anelastic waves associated with changes in inhomogeneity of the waves induced by anelastic soil and soil-rock boundaries. These anelastic effects manifest themselves as variations in amplitude response, amplitude attenuation, raypath location, and travel time as observed at the Earth’s surface. Implications of these anelastic effects for soil-response models used for earthquake resistant design are provided herein.

Conference Paper↗
USGS2024

Tungsten skarn quantitative mineral resource assessment and gold, rare earth elements, graphite, and uranium qualitative assessments of the Kuldjuktau and Auminzatau Ranges, in the central Kyzylkum region, Uzbekistan

A new quantitative mineral resource assessment for tungsten skarn was conducted for the Auminzatau and Kuldjuktau mountain ranges in Central Uzbekistan, along with qualitative assessments of orogenic gold, rare earth elements (REEs), amorphous graphite, and uranium. By integrating a variety of geological, geochemical, geophysical, and remote sensing data sets, estimates of undiscovered tungsten skarn deposits in permissive tracts are combined with grade and tonnage distributions of known deposits to generate probabilistic estimates of undiscovered resources. Undiscovered deposits in Auminzatau are estimated to contain median resources of 98 thousand metric tons (kt) of WO 3 with a 70 percent (%) probability of at least 28 kt and a 10% probability of at least 468 kt, of which 16 kt to 293 kt may be economic to extract. In Kuldjuktau, the undiscovered deposits are estimated to contain median resources of 27 kt of WO 3 with a 60% probability of at least 12 kt and a 10% probability of at least 208 kt, of which 5 kt to 132 kt may be economic to extract. Our results suggest that the Auminzatau–Kuldjuktau Mountains area is highly prospective for additional discovery of significant Au and U resources and has low prospectivity for discovery of significant REE and graphite resources.

Minerals↗
USGS2025

Wetlands, groundwater and seasonality influence the spatial distribution of stream chemistry in a low-relief catchment

Evaluating stream water chemistry patterns provides insight into catchment ecosystem and hydrologic processes. Spatially distributed patterns and controls of stream solutes are well-established for high-relief catchments where solute flow paths align with surface topography. However, the controls on solute patterns are poorly constrained for low-relief catchments where hydrogeologic heterogeneities and river corridor features, like wetlands, may influence water and solute transport. Here, we provide a data set of solute patterns from 58 synoptic surveys across 28 sites and over 32 months in a low-relief wetland-rich catchment to determine the major surface and subsurface controls along with wetland influence across the catchment. In this low-relief catchment, the expected wetland storage, processing, and transport of solutes is only apparent in solute patterns of the smallest subcatchments. Meanwhile, downstream seasonal and wetland influence on observed chemistry can be masked by large groundwater contributions to the main stream channel. These findings highlight the importance of incorporating variable groundwater contributions into catchment-scale studies for low-relief catchments, and that understanding the overall influence of wetlands on stream chemistry requires sampling across various spatial and temporal scales. Therefore, in low-relief wetland-rich catchments, given the mosaic of above and below ground controls on stream solutes, modeling efforts may need to include both surface and subsurface hydrological data and processes.

Michigan↗
USGS2024

Exploring the uncertainty of machine learning models and geostatistical mapping of rare earth element potential in Indiana coals, USA

Rare earth elements and yttrium (REEs) have a wide range of applications in high- and low-carbon technologies. The strategic significance of REEs has grown due to their expanding applications in manufacturing industries and the constrained availability of these essential resources. This research explores the applicability of machine learning models and their uncertainty for assessing the REE potential in coal beds using various coal parameters as inputs. The work focuses on developing a predictive model based on geological variables, excluding considerations related to potential shifts in the commodities market. The Indiana Coal Quality Database was used as the data source. The promising and unpromising indicators derived from the outlook coefficient of samples from the database were used as the REE potential indicator for machine learning classification models. The filter-based approach with bootstrap was used to evaluate the importance of the coal parameters and their prediction uncertainties. Four machine learning methods (linear discriminant analysis (LDA), random forest (RF), support vector machine (SVM), and artificial neural networks (ANN), a data balancing and augmentation approach (Synthetic Minority Over-sampling Technique), and bootstrap resampling techniques were used for building the models and evaluating their prediction capabilities under uncertainty. It was determined that the SVM bootstrap model with ten-times balanced and augmented data provided superior results compared with other models. Finally, stochastic spatial maps of the REE potential within the coal basin were generated using sequential indicator simulation. The spatial maps of the REE potential showed that a 29% area of the Indiana section of the Illinois coal basin has economic potential of REEs, with 90% confidence.

Indiana↗
USGS2024

Mafic alkaline magmatism and rare earth element mineralization in the Mojave Desert, California: The Bobcat Hills connection to Mountain Pass

Occurrences of alkaline and carbonatite rocks with high concentrations of rare earth elements (REE) are a defining feature of Precambrian geology in the Mojave Desert of southeastern California. The most economically important occurrence is the carbonatite stock at Mountain Pass, which constitutes the largest REE deposit in the United States. A central scientific goal is to understand the genesis of the carbonatite ore body in the context of widespread REE-rich igneous activity. A swarm of mafic alkaline (shonkinite) dikes has been mapped and sampled at Bobcat Hills, 65 km southeast of the Mountain Pass mine. Whole-rock geochemistry and zircon geochronology demonstrate a clear affinity to the ca. 1.4 Ga Mountain Pass intrusive system. Bobcat Hills dikes have comparably high REE concentrations (La ∼1,000× chondritic) and an error-weighted mean 207 Pb/ 206 Pb zircon crystallization age of 1,426 ± 2 Ma (2 σ ). Unlike the alkaline intrusions at Mountain Pass, which have abundant inherited zircon from Paleoproterozoic basement rocks and crustally influenced oxygen isotope compositions (δ 18 O zircon = 6.5–7.5‰), the Bobcat Hills dikes lack any evidence of crustal assimilation and have oxygen isotope values that overlap a mantle range (Bobcat Hills average δ 18 O zircon = 5.6 ± 0.3‰). The dikes were a high-temperature, early center of mafic alkaline magmatism in the Mojave Desert that serve as a snapshot of melt generation from a spatially extensive, metasomatized mantle source. We propose that modification of the crust over many tens of Myr at Mountain Pass created an environment that favored crustal assimilation and enabled ascent of late-stage, REE-rich carbonatite magmas.

California↗
USGS2000

Use of a ground-penetrating radar system to detect pre- and post-flood scour at selected bridge sites in New Hampshire, 1996-98

Ground-penetrating radar was used to measure the depth and extent of existing and infilled scour holes and previous scour surfaces at seven bridges in New Hampshire from April 1996 to November 1998. Ground-penetrating-radar survey techniques initially were used by the U.S. Geological Survey to study streambed scour at 30 bridges. Sixteen of the 30 bridges were re-surveyed where floods exceeded a 2-year recurrence interval. A 300-megahertz signal was used in the ground-penetrating radar system that penetrated through depths as great as 20 feet of water and as great as 32 feet of streambed materials. Existing scour-hole dimensions, infilled thickness, previous scour surfaces, and streambed materials were detected using ground-penetrating radar. Depths to riprap materials and pier footings were identified and verified with bridge plans. Post data-collection-processing techniques were applied to assist in the interpretation of the data, and the processed data were displayed and printed as line plots. Processing included distance normalization, migration, and filtering but processing was kept to a minimum and some interference from multiple reflections was left in the record. Of the 16 post-flood bridges, 22 ground-penetrating-radar cross sections at 7 bridges were compared and presented in this report. Existing scour holes were detected during 1996 (pre-flood) data collection in nine cross sections where scour depths ranged from 1 to 3 feet. New scour holes were detected during 1998 (post-flood) data collection in four cross sections where scour depths were as great as 4 feet deep. Infilled scour holes were detected in seven cross sections, where depths of infilling ranged from less than 1 to 4 feet. Depth of infilling by means of steel rod and hammer was difficult to verify in the field because of cobble and boulder streambeds or deep water. Previous scour surfaces in streambed materials were identified in 15 cross sections and the depths to these surfaces ranged from 1 to 10 feet below the streambed. Riprap materials or pier footings were identified in all cross sections. Calculated record depths generally agree with bridge plans. Pier footings were exposed at two bridges and steel pile was exposed at one bridge. Exposures were verified by field observations.

New Hampshire↗
USGS2026

Utilization of multiple geochronology techniques to constrain the age of laterization and mineralization of the world-class Mount Weld rare earth element deposit, Western Australia

Pervasive chemical weathering on stable cratons may form thick regoliths and elemental enrichment, but constraining the age of regolith formation is challenging. In this study we utilize multiple geochronological techniques on different minerals from the world-class Mount Weld rare earth element (REE) deposit, formed by lateritic weathering of a carbonatite, to constrain the age of formation and provide insight into landscape evolution. The oldest dates, ca. 100 to 38 Ma, are from Lu-Hf dating of churchite [HREE(PO 4 )·2(H 2 O)], a heavy REE phosphate mineral. Growth bands on individual minerals show a younging outwards. 40 Ar/ 39 Ar geochronology of cryptomelane [K(Mn 4+ ,Mn 2+ )₈O₁₆] yielded dates from ca. 40 to 27 Ma. Similarly, (U-Th)/He geochronology of goethite [FeO(OH)] yielded dates ranging from ca. 45 to 19 Ma. Integrating results into regional constraints, suggests 1) churchite formed by mineral saturation in a karst-like setting below the water table from ca. 100 to 40 Ma, 2) with minor uplift and erosion, cryptomelane and goethite formed at or near the water table between ca. 45 and 19 Ma, 3) after ca. 15 to 10 Ma chemical weathering within the profile had ended. Other studies document that the region experienced minimal uplift and a wet, warm climate from ca. 100 Ma to 15 Ma. These conditions and the high carbonate content of the carbonatite promote extensive chemical weathering, a deep weathering profile, and the preservation of the weathered section. This study highlights the use of multiple geochronological techniques utilizing different minerals to provide insight into how laterites form and to constrain the timing and history of the formation of this important mineral deposit.

Western Australia↗
USGS2025

Dynamic baseflow storage estimates and the role of topography, geology and evapotranspiration on streamflow recession characteristics in the Neversink Reservoir Watershed, New York

Estimates of dynamic groundwater volumes supplying baseflow to streams are important for water availability projections during extended periods of drought. The primary goals of this study were to provide dynamic storage volume estimates, inferred from streamflow recession analysis, for baseflow regimes within seven gaged catchments within the Neversink Reservoir Watershed (NRW), a critical municipal water source for New York City. Additionally, geomorphological properties, surficial geology and hydro-meteorological processes were quantified and described in relation to time and spatially variable recession behaviour and storage estimates across the NRW. To explore these relationships, we (1) evaluated seasonal trends in streamflow recession behaviour in relation to modelled potential evapotranspiration (PET) and catchment runoff rates, (2) derived empirical streamflow models for cool-season runoff using both linear and nonlinear reservoir assumptions for baseflow and (3) calculated metrics related to the geology and geomorphology of each catchment and compared these metrics to area normalised baseflow dynamic storage estimates. Results show that baseflow recession behaves as a nonlinear reservoir, and applying linear groundwater reservoir assumptions may underestimate the total dynamic storage volumes compared to what would be predicted for a nonlinear reservoir. Increases in PET caused decreases in storage conditions that resulted in increased recession rates and nonlinearity in streamflow recession during the growing season. Additionally, we found that while no single physical catchment characteristic solely predicted catchment storage dynamics, sediment volume and stream gradients were stronger predictors of normalised storage volumes than catchment surface area or surface topography alone. Within the NRW, catchments with the highest sediment volume exhibited the lowest recession rates and higher dynamic storage volumes, while the smallest catchment, mostly devoid of sediment, had the fastest recession rate and lowest dynamic storage volume.

New York↗
USGS2025

Stable isotope composition and geochemistry of calcite and dolomite in the Mountain Pass carbonatite: A lens into petrogenesis

Carbonatites host most of the global rare earth element (REE) deposits. The petrogenesis of these rocks, including magmatic and post-magmatic processes, are poorly understood but critical in forming and upgrading these deposits. The Mountain Pass carbonatite, which hosts the only active REE mine in North America, is lithologically variable but consistently contains >50% calcite and/or dolomite. Multiple generations of carbonates are evident, suggesting bulk analysis of carbonate minerals would generate a mixed isotopic and geochemical signature. In-situ stable carbon and oxygen isotopes, combined with geochemical analysis and petrography, distinguish carbonate generations, trace the source region of the carbonatite magma, and link carbonate genesis to REE mineralization throughout the intrusion. Primary carbon and oxygen isotope values outside the accepted mantle range may suggest a subduction-related carbon and oxygen source in the mantle. Deformation textures in primary calcite indicate syn- or post-crystallization ductile flow. Carbonates with secondary textures and heavy δ 13 C and δ 18 O values are associated with ore mineralization, suggesting fluid mobilization was important in concentrating REE and upgrading of the Mountain Pass deposit.

California↗
USGS2026

Rare earth element potential in coal and coal ash in the U.S. Gulf Coast

United States heavy reliance on imports of critical minerals (CMs), including rare earth elements (REEs), underscores the importance of development of domestic sources. The study objective was to quantify CM and REE concentrations in coal and coal ash in the US Gulf Coast region. CM and REE concentrations were measured for 118 samples from outcrops and 14 mines in the Gulf Coast. Results show that total REE + Yttrium (REY) concentrations (dry coal basis) are comparable to those of the upper continental crust (UCC) with localized hot spots, such as the Texas Gibbons Creek mine (REY ≤ ~ 2860 ppm). When normalized to UCC REY concentration (169 ppm, dry coal basis), REY to UCC ratios for Gulf Coast coal samples range from 0.1 to 17 (median ratio 0.6). REE extractability from lignites is high (median: 63%–93%) using environmentally benign weak acid. In addition to raw coal, coal ash from power plants could also serve as an REE source with a median ratio of REY in ash relative to coal of 4; however, extractability from coal ash is generally much lower (≤ 5% using the same weak acid as in coal). The median basket price for extracted REY as oxides from coal, assuming 70% extractability, is $3.2 per tonne of coal and $186 billion based on 58 billion metric tonnes of dry coal in the Gulf Coast. REEs important for magnets (Pr + Nd + Tb + Dy) account for ~ 80% of the total value. The corresponding median basket price for extracted REY as oxides from coal ash, assuming ~ 30% extractability, is ~$4.4 per tonne of ash and $1.2 billion based on 258 million tonnes of ash. REE production from coal would likely require co-products, such as activated carbon or humic acids, to attain economic viability. Production of REEs from coal ash could offset remediation costs related to potential water contamination. This reconnaissance study shows the potential for REE production from coal and coal ash in the Gulf Coast; however, carbon coproducts and/or societal benefits would likely be required for socioeconomic viability.

Alabama, Florida, Louisiana, Mississippi, Texas↗
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↗
USGS2025

Assessing flood water infiltration and storage in a restored floodplain

In urban areas, floodplain restoration is gaining prominence as a strategy for restoring the natural functions of floodplain ecosystems and reducing flood risk. This has spurred research into potential interactions between floodwaters, the hyporheic zone, and the floodplain aquifer. An urban restored stream in Wisconsin, USA, was used as a case study to examine four methods to estimate floodplain infiltration and storage during overbank floods. We characterised flood-related infiltration over a 4-year period from 2018 through 2021 by simultaneously and continuously measuring groundwater levels and vertical temperature profiles with stream water levels linked to high-resolution flood inundation maps. High-resolution topographic data helped to quantify surface floodplain storage and the unsaturated soil volume relative to flood stage. Infiltration estimates from the simple methods align well with those from the more complex methods; however, the complex methods provide additional insights about the factors influencing infiltration. Results from all methods indicate that the volume of water that vertically infiltrates during floods is likely small relative to the total volume of the flood, with 0.08%–0.52% of flood water infiltrating into the floodplain, on average. Spatially variable vertical hydraulic gradients, driven by flood depth, groundwater level, and permeability, imply heterogeneous patterns of infiltration across the floodplain. Gradients favourable for infiltration typically occurred during the onset of flooding but, over the study period, were mostly (98% of the time) favourable for groundwater discharge to the channel (non-flood periods). These findings highlight the importance of considering surface-groundwater dynamics, floodplain soils, and unsaturated floodplain volume in defining the benefits of floodplain infiltration for flood attenuation.

Wisconsin↗
USGS2026

A roadmap for identifying and interpreting physical processes and national water model prediction bias associated with baseflow index regimes across the contiguous United States

Understanding how groundwater–surface water interactions shape streamflow variability is critical for diagnosing low flow behavior and prediction bias in continental scale hydrologic models. We present a process informed framework that links observed baseflow (BF) dynamics, watershed attributes, and National Water Model (NWM) performance across the contiguous United States. Using daily observed streamflow from 797 reference quality streamgages, we developed monthly baseflow index (BFI) signatures using a streamgage specific, calibrated digital filter. Hierarchical clustering of these signatures identified seven distinct BFI regimes capturing regional and seasonal variability. We evaluated NWM v3.0 retrospective streamflow performance within each regime using multiple hydrograph and flow duration curve-based metrics. Model skill varied systematically across regimes: mixed flow systems were simulated most accurately, while predominantly BF dominated and quickflow dominated regimes exhibited substantially poorer performance. Across nearly all regimes, the NWM underestimated observed BFI magnitude and frequently failed to reproduce seasonal BF patterns, indicating systematic biases in simulated low flow contributions. To relate these regimes to potential process controls, we trained a Random Forest classifier using static watershed attributes and applied Shapley Additive Explanations to identify features most strongly associated with each regime. Results highlight regionally varying influences, including the dominant role of snow fraction and seasonal runoff timing in snow dominated basins and the importance of evapotranspiration and aridity in quickflow dominated systems. Collectively, these findings demonstrate how hydrologic signatures combined with interpretable machine learning can diagnose regime specific model biases and generate process-based hypotheses about limitations in large scale hydrologic prediction systems.

contiguous United States↗
USGS2026

A review and synthesis of post-wildfire shifts in hydrologic processes and streamflow generation mechanisms

Critical water supply watersheds in the western United States (WUS) are impacted by wildfires, with potential negative effects on water quality and quantity. Scientific understanding is currently insufficient to deliver estimates of wildfire consequences for water quantity that are regionally accurate. Regional variability in the directionality and magnitude of post-wildfire shifts in streamflow generation fuels uncertainty in estimates of wildfire effects on water supply. In this work we provide a narrative review of wildfire effects on hydrologic processes and the resulting changes in streamflow generation mechanisms with a focus on the WUS, incorporating other global regions when pertinent. A conceptual model summary of wildfire effects on streamflow generation emphasizes: (1) precipitation seasonality, (2) synchrony of precipitation and potential evapotranspiration, (3) net shifts in interception, evaporation, and transpiration relative to total annual precipitation, (4) vegetation changes, including compensatory uptake and type conversion, (5) degree of overlap in rainfall rates and infiltration, (6) fire extent and severity, (7) burn scar positioning (e.g. in headwaters or proximal to watershed outlet), (8) scale-dependent groundwater leakage, (9) near-surface water storage reduction, and (10) soil to groundwater connectivity. Ongoing gaps and challenges include separating the influences of precipitation variability, water withdrawals, and post-fire land management; compound and overlapping disturbances; and lack of pre-fire data. Notable future opportunities include: harnessing ever-improving gridded and remotely sensed precipitation and fire-effects data; linking geophysical, isotopic tracer, and geochemical signatures to diagnose hydrologic changes; leveraging physically based and data-driven model advancements; and analyzing streamflow generation recovery trajectories across diverse watersheds.

western United States↗
USGS2025

Triple-oxygen isotopic evidence of prolonged direct bioleaching of pyrite with O2

Sulfate is often touted as containing atmospheric oxygen whose isotopic signature can constrain redox, environmental conditions, and biological activity. Yet, the amount and isotopic fractionation associated with air-O 2 incorporation during sulfate formation is still debated, making its verification difficult. In this study, we identify a distinct, microbially dominated environment with the potential to preserve maximum signals of air-O 2 in sulfate. We report triple-oxygen isotope data for sulfate produced from pyrite oxidation in microbial and abiotic experiments, and from natural dissolved sulfate from the Rio Tinto, Spain, an acid mine drainage site. The oxygen isotope systematics of sulfate in these environments define a unique kinetic isotope effect associated with initial stage pyrite oxidation by Acidithiobacillus ferrooxidans that preserves >80 % oxygen from air-O 2 in sulfate. Unlike experiments, which evolve toward water-oxygen dominated sulfate on short time scales, Rio Tinto, Spain hosts a microbe rich environment with distinct geochemistry that maintains high O 2 -oxygen in sulfate. Therefore, in addition to containing isotopic records from water and air, sulfates can also contain a biosignature that is promising for understanding conditions on Mars and early Earth.

Earth and Planetary Science Letters↗
USGS2024

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

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

New Hampshire↗