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1,748 records · Page 83Linked to original sources
USGS2023

An inventory of three-dimensional geologic models—U.S. Geological Survey, 2004–22

A database of spatial footprints and characteristics of three-dimensional geological models that were constructed by the U.S. Geological Survey between 2004 and 2022 was compiled as part of ongoing development of subsurface geologic information by the USGS National Cooperative Geologic Mapping Program. This initial inventory resulted in the compilation of 38 three-dimensional geological models that vary widely in their spatial extent, the type and purpose of the model, the number of subsurface units characterized by the model, and the software platforms used to create the model. This Data Report provides the scientific rationale and explanation of the contents of a companion USGS digital data release of spatial data and attributes associated with each three-dimensional model.

Data Report↗
USGS2023

Sediment thickness map of United States Atlantic and Gulf Coastal Plain Strata, and their influence on earthquake ground motions

With the recent successful accounting of basin depth ground-motion adjustments in seismic hazard analyses for select areas of the western United States, we move toward implementing similar adjustments in the Atlantic and Gulf Coastal Plains by constructing a sediment thickness model and evaluating multiple relevant site amplification models for central and eastern United States seismic hazard analyses. We digitize and combine existing sediment thickness data sets into a composite surface that delineates the base of Cretaceous sediments under the Atlantic Coastal Plain and the base of Mesozoic sediments under the Gulf Coastal Plain. Amplification models dependent on sediment thickness, site natural period, and source-to-site path length are compared with data sets of observed ground motions to evaluate the ability of the new models to improve ground motion estimates. We find that the amplification models can account for observed trends in sediment-thickness and period-dependent residuals, but some tuning is required. For example, the model of Chapman and Guo requires a reference V S 30 , the time-averaged shear-wave velocity within 30 m of the Earth’s surface, for non-Coastal Plain sites, which we estimate to be between about 1 and 2 km/s. Along with our sediment thickness model, we estimate a velocity profile for application to the Harmon et al. site-natural-period-based model in order to best match the Chapman and Guo period dependence for a broad range of sediment thicknesses. The Next Generation of Attenuation models for the eastern United States Gulf Coast path-based adjustment models can also account for seismic attenuation in the Coastal Plain sediments and reduce the standard deviation of total residuals. If enacted in the U.S. Geological Survey National Seismic Hazard Model, these amplification models will reduce predicted short-period (<1 s) and increase predicted long-period (>1 s) ground motions in the Coastal Plains appreciably.

Earthquake Spectra↗
USGS2023

Reconnaissance basement geology and tectonics of North Zealandia

New rock dredge samples supply key information to establish the tectonic and geological framework of the northern two-thirds of the 95% submerged Zealandia continent. The R/V Investigator voyage IN2016T01 to the Fairway Ridge, Coral Sea, obtained poorly sorted poly-lithologic pebbly to cobbly sandstones, well sorted fine grained sandstones, mudstones, bioclastic limestones, and basaltic lavas. Post-cruise analytical work comprised petrography, whole rock geochemical and Sr and Nd isotopic analyses, and U-Pb zircon, Rb-Sr, and Ar-Ar geochronology. A Fairway Ridge cobbly sandstone has a ∼95 Ma (early Late Cretaceous) depositional age; two biotite granite cobbles are 111 ± 1 and 128 ± 1 Ma in age, and some volcanic pebbles are also likely Early Cretaceous. Fairway Ridge basalts have intraplate alkaline chemistry and are of Late Eocene age (∼40–36 Ma). By analogy with South Zealandia, we interpret strong positive continental magnetic anomalies of North Zealandia to mainly result from Late Cretaceous to Cenozoic intraplate basalts, many of them rift-related lavas. A new basement geological map of North Zealandia shows the position of the Mesozoic Gondwana magmatic arc axis (Median Batholith) and other major geological units. This study completes onland and offshore reconnaissance geological mapping of the entire 5 Mkm 2 Zealandia continent.

Tectonics↗
USGS2023

Stratigraphic notes—Volume 1, 2022

This is the first volume in the U.S. Geological Survey (USGS) series of reports on stratigraphy entitled “Stratigraphic Notes,” which consists of short papers that highlight stratigraphic studies, changes in stratigraphic nomenclature, and explanations of stratigraphic names and concepts used on published geologic maps. “Stratigraphic Notes” is a long-term (multiyear), multivolume publication containing articles that address updates or revisions to stratigraphic nomenclature (and whose content ultimately will be incorporated by National Geologic Map Database personnel into Geolex, https://ngmdb.usgs.gov/Geolex/ ). We welcome papers for the “Stratigraphic Notes” series from geoscientists of the USGS, of State Geological Surveys, and from academicians. Papers can be submitted for publication in “Stratigraphic Notes” by contacting the USGS Geologic Names Committee ( gnc@usgs.gov ). As new “Stratigraphic Notes” volumes are published, links to the volumes will be posted at https://doi.org/10.3133/pp1879 . This first volume ("Stratigraphic notes—Volume 1, 2022") includes articles that provide guidance for those who wish to submit papers to “Stratigraphic Notes,” as well as information on how to make your manuscripts compliant for geologic names reviews and how to organize your paper’s content to facilitate inclusion of new or revised names in Geolex. This volume also includes some specific guidance on conducting geologic names reviews of geologic and hydrogeologic reports.

Professional Paper↗
USGS2023

Evaluation of models for estimating hydraulic conductivity in glacial aquifers from NMR logging

Nuclear magnetic resonance (NMR) logging is a promising method for estimating hydraulic conductivity ( K ). During the past ∼60 years, NMR logging has been used for petroleum applications, and different models have been developed for deriving estimates of permeability. These models involve calibration parameters whose values were determined through decades of research on sandstones and carbonates. We assessed the use of five models to derive estimates of K in glacial aquifers from NMR logging data acquired in two wells at each of two field sites in central Wisconsin, USA. Measurements of K , obtained with a direct push permeameter (DPP), K DPP , were used to obtain the calibration parameters in the Schlumberger-Doll Research, Seevers, Timur-Coates, Kozeny-Godefroy, and sum-of-echoes (SOE) models so as to predict K from the NMR data; and were also used to assess the ability of the models to predict K DPP . We obtained four well-scale calibration parameter values for each model using the NMR and DPP measurements in each well; and one study-scale parameter value for each model by using all data. The SOE model achieved an agreement with K DPP that matched or exceeded that of the other models. The Timur-Coates estimates of K were found to be substantially different from K DPP . Although the well-scale parameter values for the Schlumberger-Doll, Seevers, and SOE models were found to vary by less than a factor of 2, more research is needed to confirm their general applicability so that site-specific calibration is not required to obtain accurate estimates of K from NMR logging data.

Wisconsin↗
USGS2023

Oligocene–Miocene northward growth of the Tibetan Plateau: Insights from intermontane basins in the West Qinling Belt, NW China

Growth of the Tibetan Plateau, Earth’s broadest and highest elevation collisional system, shapes orographic barriers, reorganizes drainage networks, and influences surface erosion and sediment delivery, whose changes in space and provenance feed back to intracontinental tectonic processes. Studies of interior basins within the northern Tibetan Plateau provide new sediment accumulation, provenance, paleodrainage, and deformation timing data that enable a reconstruction of the far-field tectono-geomorphic evolution of the rising Tibetan Plateau. Along the northern plateau margin, topographic growth in the West Qinling Belt is inferred to have initiated in the Eocene, nearly coeval with the India-Asia collision, as well as in the late Miocene. However, geological knowledge about the intervening period remains at present enigmatic, and the kinematics and dynamics are uncertain. This study presents a multidisciplinary data set from the intermontane Anhua-Huicheng Basin (AHB; Gansu Province, China) to fill this gap. Magnetostratigraphic dating, regional mapping, and sedimentological analysis imply that contractional deformation and thrust-top basin systems formed within the West Qinling Belt in the Oligocene (not later than ca. 24 Ma). A combination of observations including paleocurrent changes, detrital zircon U-Pb age variations, and appearance of growth strata along the Anhua-Huicheng Basin reveal the rapid uplift of the West Qinling Belt at ca. 15 Ma. Sedimentation in the intermontane basins ended after the late Miocene (ca. 8 Ma), when the region experienced intrabasinal deformation, uplift, and erosion with the establishment of an external drainage system. Since the late Miocene, the growth of the West Qinling Belt reached a climax with the lack of substantial contractional deformation in Cenozoic sequences heralding the onset of the modern kinematic regime and attainment of high elevation. Observed transitions in the tectonostratigraphy and paleodrainage define different phases of deformation and plateau-wide shifts in stress reorganization, which led to the northward growth and later lateral expansion of the Tibetan Plateau.

GSA Bulletin↗
USGS2023

Slow slip detectability in seafloor pressure records offshore Alaska

In subduction zones worldwide, seafloor pressure data are used to observe tectonic deformation, particularly from megathrust earthquakes and slow slip events (SSEs). However, such measurements are also sensitive to oceanographic circulation-generated pressures over a range of frequencies that conflate with tectonic signals of interest. Using seafloor pressure and temperature data from the Alaska Amphibious Community Seismic Experiment, and sea surface height data from satellite altimetry, we evaluate the efficacy of various seasonal and oceanographic pressure signal proxy corrections and conduct synthetic tests to determine their impact on the timing and amplitude prediction of ramp-like signals typical of SSEs. We find that subtracting out the first mode of the complex empirical orthogonal functions of the pressure records on either the shelf or slope yields signal root-mean-square error (RMS) reductions up to 73% or 80%, respectively. Additional correction with proxies that exploit the depth-dependent spatial coherence of pressure records provides cumulative variance reductions up to 83% and 93%, respectively. Our detectability tests show that the timing and amplitude of synthetic SSE-like ramps can be well constrained for ramp amplitudes ≥4 cm on the shelf and ≥2 cm on the slope, using a fully automated detector. The principal limits on detectability are residual abrupt changes in pressure that occur as part of the transition to and from summer to winter conditions but are not adequately characterized by our seasonal corrections, as well as the inability to properly account for instrumental drift, which is not readily separated from the seasonal signal.

Alaska↗
USGS2023

WellSTIC: A cost-effective sensor for performing point dilution tests to measure groundwater velocity in shallow aquifers

Many individual measurement points are required to characterize groundwater velocity within an aquifer. Groundwater velocity is most commonly measured using a network of >5 cm diameter monitoring wells, which, if not already present at a site, are expensive and labor-intensive to install. Drive-point piezometers—simple, cost-effective wells that can be installed by hand—are a common tool for sampling groundwater in shallow, alluvial aquifers, but most groundwater velocity measurement techniques require equipment that is too large for these narrow (usually <2 cm inside diameter) piezometers. In this technical note, we introduce a low-cost sensor and well packer system (<$90 USD) for performing point dilution tests in narrow piezometers. Field data show that the magnitude of groundwater velocity measured with this technique agrees with velocities computed from natural gradient tracer tests. Additionally, with proper calibration, these sensors can be used to continuously monitor in-well specific conductance, either during inter-well tracer tests with saline tracers or for water quality monitoring. This system is a viable tool for rapid assessment of the magnitude of groundwater velocity in shallow aquifers.

Water Resources Research↗
USGS2023

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

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

Geothermal Resources Council Transactions↗
USGS2023

Don’t Let Negatives Hold You Back: Accounting for Underlying Physics and Natural Distributions of Hydrothermal Systems When Selecting Negative Training Sites Leads to Better Machine Learning Predictions

Selecting negative training sites is an important challenge to resolve when utilizing machine learning (ML) for predicting hydrothermal resource favorability because ideal models would discriminate between hydrothermal systems (positives) and all types of locations without hydrothermal systems (negatives). The Nevada Machine Learning project (NVML) fit an artificial neural network to identify areas favorable for hydrothermal systems by selecting 62 negative sites where the research team had confidence that no hydrothermal resource exists. Herein, we compare the implications of the expert selection of negatives (i.e., the NVML strategy) with a random sample strategy, where it is assumed that areas outside the favorable structural ellipses defined by NVML are negative. Because hydrothermal systems are sparse, it is highly probable that, in the absence of a favorable geological structure, hydrothermal favorability is low. We compare three training strategies: 1) the positive and negative labeled examples from NVML; 2) the positive examples from NVML with randomly selected negatives in equal frequency as NVML; and 3) the positive examples from NVML with randomly selected negatives reflecting the expected natural distribution of hydrothermal systems relative to the total area. We apply these training strategies to the NVML feature data (input data) using two ML algorithms (XGBoost and logistic regression) to create six favorability maps for hydrothermal resources. When accounting for the expected natural distribution of hydrothermal systems, we find that XGBoost performs better than the NVML neural network and its negatives. Model validation was less reliable using F1 scores, a common performance metric, than comparing probability estimates at known positives, likely because of the extreme natural class imbalance and the lack of negatively labeled sites. This work demonstrates that expert selection of negatives for training in NVML likely imparted modeling bias. Accounting for the sparsity of hydrothermal systems and all the types of locations without hydrothermal systems allows us to create better models for predicting hydrothermal resource favorability.

Geothermal Resources Council Transactions↗
USGS2023

Advancing subsurface investigations beyond the borehole with passive seismic horizontal-to-vertical spectral ratio and electromagnetic geophysical methods at transportation infrastructure sites in New Hampshire

The U.S. Geological Survey (USGS), in cooperation with the New Hampshire Department of Transportation (NHDOT), surveyed transportation infrastructure sites using rapidly deployable geophysical methods to assess benefits added to a comprehensive site characterization with traditional geotechnical techniques. Horizontal-to-vertical spectral-ratio (HVSR) passive-seismic and electromagnetic-induction (EMI) methods were applied at 4 sites including a roadway-stream crossing, roadway-bridge rail-trail crossing, commuter-parking expansion, and a railroad-adjacent river-cutbank slope-failure site. Additionally, ground-penetrating-radar (GPR) was used at the slope-failure site. Typically, subsurface geotechnical properties are determined from boring data; however, borings are often spaced hundreds of feet apart, potentially missing important spatial variability between boreholes. Geotechnical site characterization including geophysical surveys helped provide a more accurate characterization by using continuous or near continuous profiling. Three-component ambient noise measured with HVSR methods were used to determine resonance frequency and estimate sediment thickness. The method works when there is a strong shear-wave acoustic impedance contrast (> 2:1) between sediment and bedrock. Sediment thickness estimates from HVSR measurements were combined with boring data to make detailed maps of the bedrock surface altitude. The bulk electrical conductivity of the subsurface was indirectly measured with EMI methods and was used to identify lithologic variations, shallow bedrock, and conductive groundwater. Ground penetrating radar, which transmits pulses of electromagnetic energy into the subsurface and records the amplitude and timing of reflected signals, was used to identify bedding and changes in lithology or water content. By combining geophysical and boring data analyses, transportation projects produced more spatially comprehensive representations of geotechnical subsurface conditions than would be determined using conventional borings alone.

New Hampshire↗
USGS2023

Connecting flood-related fluvial erosion and deposition with vulnerable downstream road-stream crossings

Fluvial erosion is increasingly responsible for infrastructure and building damages associated with floods as the intensity of extreme rainfalls hit rural and urban rivers in a variety of climate settings across the United States. Extreme floods in 2016 and 2018 caused widespread culvert blockages and road failures, including extensive damage along steep tributaries and ravines in the Marengo River, Wisconsin, watershed during 2016 and 2018. A study conducted by the U.S. Geological Survey (USGS), Wisconsin Wetlands Association (WWA), Ashland County, and the Northwest Wisconsin Regional Planning Commission (NWRPC) investigated the special concern of fluvial erosion hazards (FEHs) associated with gullying, streamside landslides, and the loss of wetland storage in headwaters. In 2019, a pilot study was begun to map and classify ephemeral and perennial streams and wetlands in terms of their sensitivity to FEHs. This study combined data from field-based rapid geomorphic assessments (RGAs) coupled with a stream network-wide geographic information system (GIS) approach for mapping stream segments, referred to as fluvial process zones (FPZ), sensitive to erosion, deposition, and channel change. The GIS approach used nationally available 10-meter (m) resolution topology and an extended stream network to map FPZs based on Strahler stream order, stream power, channel slope, presence of adjacent steep valley sides and headwater flats, and adjacent landform setting. Bankfull channel widths derived from RGA-based hydraulic geometry curves combined with drainage areas, an estimate of bankfull flow, and channel slope were used to calculate specific stream power for the FPZs. Lastly, the FPZs were characterized by their location within three major landform settings that affect erosion potential. The resulting vulnerability maps provided a screening framework to identify FPZs that are sensitive to incision, gullying and mass wasting along steep headwater ephemeral channels, as well as downstream perennial channels that have the potential for valley-side landslides, coarse sediment deposition, and channel change. Lastly, each FPZ was characterized in terms of hydrologic alteration associated with ditching. The vulnerability mapping products and rankings of sensitivity of FPZs will ultimately be used by Ashland County and their collaborators to prioritize natural flood management projects that mitigate FEHs, restore hydrology, and reconnect channels with adjacent wetlands and floodplains.

Wisconsin↗
USGS2023

Hidden system identification: Basin modeling as a tool for examining sedimentary geothermal resource potential

Three-dimensional (3D) geologic and temperature models have been developed for the onshore U.S. Gulf Coast. The results from these models identify areas of moderate- to high-temperature (90°-150°C and >150°C; respectively) geothermal resources at depths <6 km. This modeling study addresses the fundamental challenge of predicting where opportune temperature and lithology coincide. Unlike traditional geothermal systems with surface expressions of hydrothermal circulation (e.g., hot springs, fumaroles, sinter), sedimentary geothermal systems (SGS) are generally hidden. Historically, simplified efforts to predict subsurface temperatures in sedimentary basins have focused on linear temperature extrapolation that does not consider the variable thermal properties of different lithologies or lithologic changes with depth (e.g., compaction, lithification). Therefore, the need to understand basin architecture and predict temperatures in 3D within SGS is paramount to identifying geothermal resources and determining economic feasibility. Basin modeling software has long been used to characterize the subsurface conditions of sedimentary basins, including temperature, in the pursuit of finding hydrocarbons. This tool can also be adapted to evaluate the potential of geothermal resources in a sedimentary basin by predicting the confluence of desirable temperatures and reservoir lithologies. In this work, PetroMod basin modeling software was used to create a regional geologic model of the onshore U.S. Gulf Coast, covering over 500,000 km 2 calibrated to temperature data from wells. Inputs include structural surfaces from commercial databases, lithology information derived from published literature, and corrected bottom-hole temperatures (BHT) from over 6,000 wells. The resulting 3D geologic model can be used to predict temperatures throughout the basin. Maps were exported showing the depth, depositional unit, and reservoir lithology at which temperatures of 90°C and 150°C were reached, revealing over 400,000 km 2 of moderate- to high-temperature resources at depths <6 km. These maps function as a first-order screening tool to identify areas where low-, moderate-, or high-grade resource potential may exist, based on temperature and if optimal reservoir lithologies or depositional units of interest are present. Depending on the success criteria of a project, the same maps can be exported for any isotherm or incorporate other 1407 Gardner and Birdwell subsurface properties. The methodology employed in this work can be applied in any sedimentary basin with available subsurface data. Further calibration incorporating other data, including pressure and porosity, can expand the utility of basin modeling for geothermal evaluations. Basin modeling is a powerful but underutilized tool for identifying prospective geothermal resources in sedimentary basins.

Conference Paper↗
USGS2022

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↗
USGS2022

U-Pb scheelite ages of tungsten and antimony mineralization in the Stibnite-Yellow Pine district, central Idaho

The Stibnite-Yellow Pine district contains the largest antimony resource in the United States, as well as significant gold, and is a historic producer of tungsten. Application of in situ laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) direct dating of scheelite from two Au-Sb-W ore deposits, Yellow Pine and Hangar Flats, yielded an older group of U-Pb ages in the range of 60.0 ± 2.8 to 57.0 ± 1.1 Ma and a younger U-Pb age for scheelite intergrown with stibnite of 47.4 ± 1.1 Ma. These in situ analyses were calibrated by isotope dilution-thermal ionization mass spectrometry (ID-TIMS) U-Pb lower intercept ages of two coarsely crystalline scheelite samples that yielded ages of 57.52 ± 0.22 and 56.62 ± 0.16 Ma. Scheelite of the latter age is of sufficient quality to serve as a primary reference material for LA-ICP-MS scheelite U-Pb geochronology. The group of older U-Pb scheelite ages agrees with 40 Ar/ 39 Ar ages of 56.9 ± 1.2 to 56.38 ± 0.54 Ma on adularia from Yellow Pine and Hangar Flats, whereas the younger U-Pb scheelite age is similar to an 40 Ar/ 39 Ar age of 46.00 ± 0.40 Ma on adularia from an epithermal gold-silver deposit in the adjacent Thunder Mountain caldera. Our results indicate that the main stage of tungsten mineralization occurred at ca. 57 Ma, whereas the main stage of antimony mineralization occurred at ca. 47 Ma—thereby providing first-time age constraints for antimony and tungsten mineralization in the Stibnite-Yellow Pine district.

Idaho↗
USGS2022

South Carolina and Landsat

South Carolina, the eighth State admitted to the union, transcends its size with its deep, rich history; striking beauty; vast natural resources; and extensive cultural diversity. Home to part of the Blue Ridge Mountains of the Central Appalachians, the Upstate is graced with more than 100 waterfalls, while the Lowcountry borders the Atlantic Ocean with 187 miles of coastline and 35 barrier islands. Forests cover two-thirds of the State, and forestry and agriculture together, as agribusiness, make up South Carolina’s leading industry. Two historic crops—cotton and tobacco—still rank in the top 10 commodities, though corn and soybeans now rank higher. Poultry, cattle, peanuts, and flowers also make the list. South Carolina’s population totals more than five million. Other residents include a variety of wildlife, bird, reptile, and fish species, including Ursus americanus (black bears), Alligator mississippiensis (American alligators), and Tursiops truncatus (bottlenose dolphins). More than 100 tree species also reside in South Carolina, which pays homage to one with its “The Palmetto State” nickname. South Carolina’s subtropical climate, long coastline, and lower elevations make it highly susceptible to tornado and hurricane activity and coastal flooding. Projected sea-level rise is a growing concern. A view from space can help monitor and manage natural resources on the land and in rivers, marshes, and the coast. Landsat reveals not just what an area looks like now, but also insights from decades ago.

South Carolina↗
USGS2022

Waters divided: A history of alluvial fan research and a view of its future

Flows exiting confined valleys tend to deposit sediment in fan-shaped landforms. Where deposition is wholly or largely by the tractive forces of flowing water, these landforms are called alluvial fans. They are the product of the progressive division of water and sediment downfan, from slopes that may exceed 0.10 to distal slopes that may be below 0.01. Channel depths also tend to decline, from values that approach one to several meters at steep fanheads, to a few decimeters at distal fan margins. The result is a radiating, depositional ramp where confined or unconfined flows transport sediment from source basins to bounding streams, subsiding basins, or stable platforms. Where streams or subsiding basins consume the sediment supply from the source basin, the fan may approach a steady form whose extent and distal slope are set by stream location or subsidence rate. Where boundary conditions do not remove sediment, the fan may prograde out to long distances and low slopes (<0.01). Theoretical and experimental work over the past several decades support the notion that alluvial fan long-profiles become steeper as sediment supply increases or transport capacity decreases, and increasingly concave upward as the rate of bed material deposition decreases downfan. Grainsize distributions of alluvial fans seem to span the range observed in alluvial rivers, with no processes that uniquely identify them, apart from the distributary pattern of deposition. Bed sand cover tends to increase downfan in arid-region fans, with an absence of systematic downfan fining of coarser grain sizes. Surficial mapping and geochronology have demonstrated that fan deposition varies greatly through time, arguably from climate variations that alter hillslope sediment supply. The combination of surficial mapping and hydraulic modeling with high-resolution topography can now produce detailed flood susceptibility maps. The effective use of these maps to protect lives and property, however, depends on answering many of the enduring questions about the mechanics of how water and sediment divide down alluvial fans.

Book chapter↗
USGS2021

Critical review of mercury methylation and methylmercury demethylation rate constants in aquatic sediments for biogeochemical modeling

Mercury is a toxin that causes neurological impairments in adults, is particularly harmful for fetuses and children, and is deadly in severe cases, making it a worldwide health concern. Methylmercury (MeHg) is the environmentally relevant form of mercury (Hg) because it biomagnifies along the food chain. Methylmercury is mainly produced in aquatic sediments via methylation of inorganic Hg (Hg(II)) and transformed back via demethylation. Because transformation rates determine MeHg concentrations, quantification of methylation and demethylation rates is needed to inform management of MeHg. Published rate constants for Hg(II) methylation ( 𝑘 𝑚 ) and MeHg demethylation ( 𝑘 𝑑 ) vary greatly, stemming partly from differences in experimental methods. We conducted a comprehensive review of rate laws, evaluated published rate constants, and performed biogeochemical simulations to assess variability in reported 𝑘 𝑚 and 𝑘 𝑑 . Based on selected studies employing the same pseudo-first-order rate law and similar experimental methods, we found that 𝑘 𝑚 = 0.04 ± 0.03 d −1 is a reasonable range for wetland sediments. Over a number of environments, maximum 𝑘 𝑑 was smaller at sites without Hg source ( 𝑘 𝑑 = 0.5 d −1 ) than at sites with identified Hg source ( 𝑘 𝑑 = 1.8 d −1 ). Larger variability and higher uncertainty in 𝑘 𝑑 compared to 𝑘 𝑚 highlight the need for more research on MeHg demethylation rates. This critical review: (a) aids the design of future experimental studies of 𝑘 𝑚 and 𝑘 𝑑 ; (b) provides guidance for comparing rate constants from different studies; (c) presents a biogeochemical reaction model to assess rate constants; and (d) informs selection of 𝑘 𝑚 and 𝑘 𝑑 values from the literature for use in model simulations.

Critical Reviews in Environmental Science and Tech↗