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USGS2016

Potentiometric surfaces of the Arnold Engineering Development Complex Area, Arnold Air Force Base, Tennessee, May and September 2011

Arnold Air Force Base occupies about 40,000 acres in Coffee and Franklin Counties, Tennessee. The primary mission of Arnold Air Force Base is to provide risk-reduction information in the development of aerospace products through test and evaluation. This mission is achieved in part through test facilities at Arnold Engineering Development Complex (AEDC), which occupies about 4,000 acres in the center of Arnold Air Force Base. Arnold Air Force Base is underlain by gravel and limestone aquifers, the most productive of which is the Manchester aquifer. Several volatile organic compounds, primarily chlorinated solvents, have been identified in the groundwater at Arnold Air Force Base. In 2011, the U.S. Geological Survey, in cooperation with the U.S. Air Force, Arnold Air Force Base, completed a study of groundwater flow focused on the Arnold Engineering Development Complex area. The Arnold Engineering Development Complex area is of particular concern because within this area (1) chlorinated solvents have been identified in the groundwater, (2) the aquifers are dewatered around below-grade test facilities, and (3) there is a regional groundwater divide. During May 2011, when water levels were near seasonal highs, water-level data were collected from 374 monitoring wells; and during September 2011, when water levels were near seasonal lows, water-level data were collected from 376 monitoring wells. Potentiometric surfaces were mapped by contouring altitudes of water levels measured in wells completed in the shallow aquifer, the upper and lower parts of the Manchester aquifer, and the Fort Payne aquifer. Water levels are generally 2 to 14 feet lower in September compared to May. The potentiometric-surface maps for all aquifers indicate a groundwater depression at the J4 test cell. Similar groundwater depressions in the shallow and upper parts of the Manchester aquifer are within the main testing area at the Arnold Engineering Development Complex at dewatering facilities.

Tennessee↗

USGS2022

Assessing the seasonal evolution of snow depth spatial variability and scaling in complex mountain terrain

Dynamic natural processes govern snow distribution in mountainous environments throughout the world. Interactions between these different processes create spatially variable patterns of snow depth across a landscape. Variations in accumulation and redistribution occur at a variety of spatial scales, which are well established for moderate mountain terrain. However, spatial patterns of snow depth variability in steep, complex mountain terrain have not been fully explored due to insufficient spatial resolutions of snow depth measurement. Recent advances in uncrewed aerial systems (UASs) and structure from motion (SfM) photogrammetry provide an opportunity to map spatially continuous snow depths at high resolutions in these environments. Using UASs and SfM photogrammetry, we produced 11 snow depth maps at a steep couloir site in the Bridger Range of Montana, USA, during the 2019–2020 winter. We quantified the spatial scales of snow depth variability in this complex mountain terrain at a variety of resolutions over 2 orders of magnitude (0.02 to 20 m) and time steps (4 to 58 d) using variogram analysis in a high-performance computing environment. We found that spatial resolutions greater than 0.5 m do not capture the complete patterns of snow depth spatial variability within complex mountain terrain and that snow depths are autocorrelated within horizontal distances of 15 m at our study site. The results of this research have the potential to reduce uncertainty currently associated with snowpack and snow water resource analysis by documenting and quantifying snow depth variability and snowpack evolution on relatively inaccessible slopes in complex terrain at high spatial and temporal resolutions.

Montana↗

USGS2015

Complex Topographic Feature Ontology Patterns

Semantic ontologies are examined as effective data models for the representation of complex topographic feature types. Complex feature types are viewed as integrated relations between basic features for a basic purpose. In the context of topographic science, such component assemblages are supported by resource systems and found on the local landscape. Ontologies are organized within six thematic modules of a domain ontology called Topography that includes within its sphere basic feature types, resource systems, and landscape types. Context is constructed not only as a spatial and temporal setting, but a setting also based on environmental processes. Types of spatial relations that exist between components include location, generative processes, and description. An example is offered in a complex feature type ‘mine.’ The identification and extraction of complex feature types are an area for future research.

Conference Paper↗

USGS2012

Managing inherent complexity for sustainable walleye fisheries in Lake Erie

In Lake Erie, Walleye ( Sander vitreus vitreus ) is king. The naturally occurring species is the foundation of commercial fishing operations on the Canadian side of the lake and is a much-prized sport fish on the American side. Management of Lake Erie walleye fisheries is complex and takes place in an inter-jurisdictional setting composed of resource agencies from the states of Michigan (MDNR), Ohio (ODNR), Pennsylvania (PFBC), and New York (NYDEC) and the province of Ontario (OMNR). The complexity of walleye management is exacerbated by interactions among environmental and ecological changes in Lake Erie, complex life-history characteristics of the species, public demand for walleye, and cultural/governance differences among managing groups and their respective constituents. Success of future management strategies will largely hinge upon our ability to understand these inherent complexities and to employ tactics that successfully accommodate stock productivity and human demand in a highly dynamic environment. In this report, we review the history of Lake Erie walleye management, outline the multi-jurisdictional process for international management of walleye, and discuss strategies to address challenges facing managers.

Book chapter↗

USGS1997

Field guide to the Mesozoic accretionary complex along Turnagain Arm and Kachemak Bay, south-central Alaska

Turnagain Arm, just east of Anchorage, provides a readily accessible, world-class cross section through a Mesozoic accretionary wedge. Nearly continuous exposures along the Seward Highway, the Alaska Railroad, and the shoreline of Turnagain Arm display the two main constituent units of the Chugach terrane: the McHugh Complex and Valdez Group. In this paper we describe seven bedrock geology stops along Turnagain Arm, and two others in the Chugach Mountains just to the north (Stops 1-7 and 9), which will be visited as part of the May, 1997 field trip of the Alaska Geological Society. Outcrops along Turnagain Arm have already been described in two excellent guidebook articles (Clark, 1981; Winkler and others 1984), both of which remain as useful and valid today as when first published. Since the early 1980's, studies along Turnagain Arm have addressed radiolarian ages of chert and conodont ages of limestone in the McHugh Complex (Nelson and others, 1986, 1987); geochemistry of basalt in the McHugh Complex (Nelson and Blome, 1991); post-accretion brittle faulting (Bradley and Kusky, 1990; Kusky and others, 1997); and the age and tectonic setting of gold mineralization (Haeussler and others, 1995). Highlights of these newer findings will described both in the text below, and in the stop descriptions. Superb exposures along the southeastern shore of Kachemak Bay show several other features of the McHugh Complex that are either absent or less convincing along Turnagain Arm. While none of these outcrops can be reached via the main road network, they are still reasonably accessible - all are within an hour by motorboat from Homer, seas permitting. Here, we describe seven outcrops along the shore of Kachemak Bay that we studied between 1989 and 1993 during geologic mapping of the Seldovia 1:250,000- scale quadrangle. These outcrops (Stops 61-67) will not be part of the 1997 itinerary, but are included here tor the benefit of those who may wish to visit them later.

Alaska↗

USGS2015

Copper toxicity and organic matter: Resiliency of watersheds in the Duluth Complex, Minnesota, USA

We estimated copper (Cu) toxicity in surface water with high dissolved organic matter (DOM) for unmined mineralized watersheds of the Duluth Complex using the Biotic Ligand Model (BLM), which evaluates the effect of DOM, cation competition for biologic binding sites, and metal speciation. A sediment-based BLM was used to estimate stream-sediment toxicity; this approach factors in the cumulative effects of multiple metals, incorporation of metals into less bioavailable sulfides, and complexation of metals with organic carbon. For surface water, the formation of Cu-DOM complexes significantly reduces the amount of Cu available to aquatic organisms. The protective effects of cations, such as calcium (Ca) and magnesium (Mg), competing with Cu to complex with the biotic ligand is likely not as important as DOM in water with high DOM and low hardness. Standard hardness-based water quality criteria (WQC) are probably inadequate for describing Cu toxicity in such waters and a BLM approach may yield more accurate results. Nevertheless, assumptions about relative proportions of humic acid (HA) and fulvic acid (FA) in DOM significantly influence BLM results; the higher the HA fraction, the higher calculated resiliency of the water to Cu toxicity. Another important factor is seasonal variation in water chemistry, with greater resiliency to Cu toxicity during low flow compared to high flow. Based on generally low total organic carbon and sulfur content, and equivalent metal ratios from total and weak partial extractions, much of the total metal concentration in clastic streambedsediments may be in bioavailable forms, sorbed on clays or hydroxide phases. However, organicrich fine-grained sediment in the numerous wetlands may sequester significant amount of metals, limiting their bioavailability. A high proportion of organic matter in waters and some sediments will play a key role in the resiliency of these watersheds to potential additional metal loads associated with future mining operations.

Minnesota↗

USGS2017

Controls of multi-modal wave conditions in a complex coastal setting

Coastal hazards emerge from the combined effect of wave conditions and sea level anomalies associated with storms or low-frequency atmosphere-ocean oscillations. Rigorous characterization of wave climate is limited by the availability of spectral wave observations, the computational cost of dynamical simulations, and the ability to link wave-generating atmospheric patterns with coastal conditions. We present a hybrid statistical-dynamical approach to simulating nearshore wave climate in complex coastal settings, demonstrated in the Southern California Bight, where waves arriving from distant, disparate locations are refracted over complex bathymetry and shadowed by offshore islands. Contributions of wave families and large-scale atmospheric drivers to nearshore wave energy flux are analyzed. Results highlight the variability of influences controlling wave conditions along neighboring coastlines. The universal method demonstrated here can be applied to complex coastal settings worldwide, facilitating analysis of the effects of climate change on nearshore wave climate.

California↗

USGS2019

Spatial sampling bias and model complexity in stream-based species distribution models: A case study of Paddlefish (Polyodon spathula) in the Arkansas River basin, USA

Leveraging existing presence records and geospatial datasets, species distribution modeling has been widely applied to informing species conservation and restoration efforts. Maxent is one of the most popular modeling algorithms, yet recent research has demonstrated Maxent models are vulnerable to prediction errors related to spatial sampling bias and model complexity. Despite elevated rates of biodiversity imperilment in stream ecosystems, the application of Maxent models to stream networks has lagged, as has the availability of tools to address potential sources of error and calculate model evaluation metrics when modeling in nonraster environments (such as stream networks). Herein, we use Maxent and customized R code to estimate the potential distribution of paddlefish ( Polyodon spathula ) at a stream-segment level within the Arkansas River basin, USA, while accounting for potential spatial sampling bias and model complexity. Filtering the presence data appeared to adequately remove an eastward, large-river sampling bias that was evident within the unfiltered presence dataset. In particular, our novel riverscape filter provided a repeatable means of obtaining a relatively even coverage of presence data among watersheds and streams of varying sizes. The greatest differences in estimated distributions were observed among models constructed with default versus AIC C -selected parameterization. Although all models had similarly high performance and evaluation metrics, the AIC C -selected models were more inclusive of westward-situated and smaller, headwater streams. Overall, our results solidified the importance of accounting for model complexity and spatial sampling bias in SDMs constructed within stream networks and provided a roadmap for future paddlefish restoration efforts in the study area.

Arkansas, Colorado, Kansas, Missouri, Nebraska, Ne↗

USGS2001

U-Pb age of the Diana Complex and Adirondack granulite petrogenesis

U-Pb isotopic analyses of eight single and multi-grain zircon fractions separated from a syenite of the Diana Complex of the Adirondack Mountains do not define a single linear array, but a scatter along a chord that intersects the Concordia curve at 1145 ± 29 and 285 ± 204 Ma. For the most concordant analyses, the 207 Pb/ 206 Pb ages range between 1115 and 1150 Ma. Detailed petrographic studies revealed that most grains contained at least two phases of zircon growth, either primary magmatic cores enclosed by variable thickness of metamorphic overgrowths or magmatic portions enclosing presumably older xenocrystic zircon cores. The magmatic portions are characterized by typical dipyramidal prismatic zoning and numerous black inclusions that make them quite distinct from adjacent overgrowths or cores when observed in polarizing light microscopy and in backscattered electron micrographs. Careful handpicking and analysis of the “best” magmatic grains, devoid of visible overgrowth of core material, produced two nearly concordant points that along with two of the multi-grain analyses yielded an upper-intercept age of 1118 ± 2.8 Ma and a lowerintercept age of 251 ± 13 Ma. The older age is interpreted as the crystallization age of the syenite and the younger one is consistent with late stage uplift of the Appalachian region. The 1118 Ma age for the Diana Complex, some 35 Ma younger than previously believed, is now approximately synchronous with the main Adirondack anorthosite intrusion, implying a cogenetic relationship among the various meta-igneous rocks of the Adirondacks. The retention of a high-temperature contact metamorphic aureole around Diana convincingly places the timing of Adirondack regional metamorphism as early as 1118 Ma. This result also implies that the sources of anomalous hightemperature during granulite metamorphism are the syn-metamorphic intrusions, such as the Diana Complex.

New York↗

USGS2005

Surface complexation studied via combined grazing-incidence EXAFS and surface diffraction: Arsenate on hematite (0001) and (10-12)

X-ray diffraction [crystal-truncation-rod (CTR)] studies of the surface structure of moisture-equilibrated hematite reveal sites for complexation not present on the bulk oxygen-terminated surface, and impose constraints on the types of inner-sphere sorption topologies. We have used this improved model of the hematite surface to analyze grazing-incidence EXAFS results for arsenate sorption on the c (0001) and r (10–12) surfaces measured in two electric vector polarizations. This work shows that the reconfiguration of the surface under moist conditions is responsible for an increased adsorption density of arsenate complexes on the (0001) surface relative to predicted ideal termination, and an abundance of “edge-sharing” bidentate complexes on both studied surfaces. We consider possible limitations on combining the methods due to differing surface sensitivities, and discuss further analysis possibilities using both methods.

Analytical and Bioanalytical Chemistry↗

USGS2022

Eruptive history of Mason Spur, a Miocene—Pleistocene polygenetic volcanic complex in southern Victoria Land, West Antarctic Rift System, Antarctica

Mason Spur is a deeply eroded Middle Miocene to Pleistocene (c. 13 to 0.37 Ma) volcanic complex in southern Victoria Land, within the West Antarctic Rift System (WARS). The oldest rocks include a large volume of trachyte ignimbrites that provided abundant volcanic detritus recovered in McMurdo Sound drill cores. The ignimbrites together with early-formed intrusions were strongly deformed during a substantial caldera collapse at c. 13 Ma. Intense erosion modified the volcanic landscape, creating a paleo-relief of several hundred metres. Deep ravines were cut and filled by deposits of multiple lahars probably linked to gravitational collapses of trachyte dome(s). Small-volume trachytic magmas were also erupted, forming lavas and at least one tuff cone. The youngest trachytic activity comprises a lava dome and related block-and-ash-flow deposits, erupted at 6 Ma. Basanite erupted throughout the history of the complex and eruptions younger than 12 Ma are almost exclusively basanite, forming scoria cones, water-cooled lavas, and tuff cones. Three peripheral outcrops are composed of basanitic ‘a‘ā lava-fed deltas, probably erupted from vents on neighbouring volcanoes at Mount Discovery and Mount Morning. Abundant ignimbrite deposits at Mason Spur differentiate this volcanic complex from others in the WARS. Eruptions were triggered by rift extension initially, yielding the voluminous trachytes sourced from a magma chamber on the margin of the WARS. Later mafic eruptions were associated with deep crustal faults related to residual intraplate deformation. These results add important details to the eruptive history of the intracontinental WARS.

Bulletin of Volcanology↗

USGS2006

Protolith and metamorphic ages of the Haiyangsuo Complex, eastern China: A non-UHP exotic tectonic slab in the Sulu ultrahigh-pressure terrane

The Haiyangsuo Complex in the NE Sulu ultrahigh-pressure (UHP) terrane has discontinuous, coastal exposures of Late Archean gneiss with amphibolitized granulite, amphibolite, Paleoproterozoic metagabbroic intrusives, and Cretaceous granitic dikes over an area of about 15 km2. The U-Pb SHRIMP dating of zircons indicates that theprotolith age of a garnet-biotite gneiss is >2500 Ma, whereas the granulite-facie metamorphism occurred at around 1800 Ma. A gabbroic intrusion was dated at ???1730 Ma, and the formation of amphibolite-facies assemblages in both metagabbro and granulite occurred at ???340-460 Ma. Petrologic and geochronological data indicate that these various rocks show no evidence of Triassic eclogite-facies metamorphism and Neoproterozoic protolith ages that are characteristics of Sulu-Dabie HP-UHP rocks, except Neoproterozoic inherited ages from post-collisional Jurassic granitic dikes. Haiyangsuo retrograde granulites with amphibolite-facies assemblages within the gneiss preserve relict garnet formed during granulite-facies metamorphism at ???1.85 Ga. The Paleoproterozoic metamorphic events are almost coeval with gabbroic intrusions. The granulite-bearing gneiss unit and gabbro-dominated unit of the Haiyangsuo Complex were intruded by thin granitic dikes at about 160 Ma, which is coeval with post-collisional granitic intrusions in the Sulu terrane. We suggest that the Haiyangsuo Complex may represent a fragment of the Jiao-Liao-Ji Paleoproterozoic terrane developed at the eastern margin of the Sino-Korean basement, which was juxtaposed with the Sulu terrane prior to Jurassic granitic activity and regional deformation. ?? Springer-Verlag 2006.

Conference Paper↗

USGS2008

Use of complex hydraulic variables to predict the distribution and density of unionids in a side channel of the Upper Mississippi River

Previous attempts to predict the importance of abiotic and biotic factors to unionids in large rivers have been largely unsuccessful. Many simple physical habitat descriptors (e.g., current velocity, substrate particle size, and water depth) have limited ability to predict unionid density. However, more recent studies have found that complex hydraulic variables (e.g., shear velocity, boundary shear stress, and Reynolds number) may be more useful predictors of unionid density. We performed a retrospective analysis with unionid density, current velocity, and substrate particle size data from 1987 to 1988 in a 6-km reach of the Upper Mississippi River near Prairie du Chien, Wisconsin. We used these data to model simple and complex hydraulic variables under low and high flow conditions. We then used classification and regression tree analysis to examine the relationships between hydraulic variables and unionid density. We found that boundary Reynolds number, Froude number, boundary shear stress, and grain size were the best predictors of density. Models with complex hydraulic variables were a substantial improvement over previously published discriminant models and correctly classified 65-88% of the observations for the total mussel fauna and six species. These data suggest that unionid beds may be constrained by threshold limits at both ends of the flow regime. Under low flow, mussels may require a minimum hydraulic variable (Rez.ast;, Fr) to transport nutrients, oxygen, and waste products. Under high flow, areas with relatively low boundary shear stress may provide a hydraulic refuge for mussels. Data on hydraulic preferences and identification of other conditions that constitute unionid habitat are needed to help restore and enhance habitats for unionids in rivers. ?? 2008 Springer Science+Business Media B.V.

Hydrobiologia↗

USGS1978

Stability of fluoride complex with silica and its distribution in natural water systems

Fluoride reacts with silicic acid to form SiF 2− 6 . A fluoride electrode was used to obtain an equilibrium constant of 10 30.18 for the reaction: Si(OH) 0 6 + 6 F − +4 H + = SiF 2− 6 + 4 H 2 O "> Si(OH)06+ 6F−+4H+=SiF2−6+ 4H2O at 25°C Although there may be some experimental evidence for existence of traces of species containing less than six F − ions per silicon ( n = 6), the species SiF 2− 6 predominates for n values from about 0.1 to 6. Silicic-acid complexing with fluoride is important only in solutions which have rather low pH and low concentrations of other cations which compete with silicon for fluoride. Computations for cold volcanic condensates from Hawaii indicate that for some samples much of the silicon is complexed by fluoride as SiF 2− 6 . However, in most cooled acidic natural water samples Al and Fe are more important than Si in complexing fluoride.

Chemical Geology↗

USGS1992

Experimental study of iron-chloride complexing in hydrothermal fluids

Mineral assemblage solubilities were measured in cold-seal pressure vessels as a function of pressure, temperature, and potassium chloride concentration in order to determine the nature and thermodynamic properties of iron-chloride complexes under hydrothermal conditions. The assemblage pyritepyrrhotite-magnetite was used to buffer ƒS 2 "> ƒS 2 and ƒO 2 "> ƒO 2 , and K + H + "> K + H + ratios were buffered at reasonable geologic values using the assemblage potassium feldspar-muscovite (or andalusite)-quartz. The pressure-temperature ranges were 0.5-2.0 kbar and 300–600°C, and initial fluid compositions ranged from 0.01–2.0 molal KCl. With all other factors constant, the concentration of iron in solution increases with increasing temperature, with decreasing pressure, and with increasing total potassium chloride concentration. Changes in iron concentrations as a function of KCl concentration, in conjunction with charge balance, mass action, and mass balance constraints on the system, place constraints on the stoichiometry of the important iron-chloride complexes under each of the experimental conditions. Using least-squared linear regression fits to determine these slopes, the calculations yield values for the average ligand numbers that are in the range 1.2-1.9, with uncertainties ranging from ±0.1-0.6 at the several PT conditions considered. The slopes of the regressed fits to the data suggest that both FeCl + and FeCl 2 0 are important in the experimental fluids, with FeCl 2 0 becoming dominant at the higher temperatures. Theoretical calculations, however, indicate that FeCl + does not contribute significantly to the solubility. Because of the large uncertainties associated with some of the calculated average ligand numbers, we base our data analysis on the theoretical calculations. A statistical analysis is applied to the solubility data in order to determine the values and uncertainties of the dissociation constant for FeCl 2 0 that best fit the data at each of the experimental pressures and temperatures. The calculated stability of FeCl 2 0 increases with increasing temperature and total chloride concentration, and with decreasing pressure. The values of the dissociation constant of FeCl 2 0 that are calculated in this study are in moderately good agreement with FeCl 2 0 dissociation constants from other studies of iron-chloride complexing in supercritical fluids. Differences are likely due to different assumptions made concerning activity coefficients of aqueous species. Log k d values for full dissociation of FeCl 2 0 at 0.5 kbar—300°C—and at 1 kbar—400, 500, and 600°C, respectively—are −3.75 ± 0.40, −6.25 ± 0.10, −9.19 ± 0.44, and −13.29 ± 0.09.

Geochimica et Cosmochimica Acta↗

USGS1978

The geochemical nature of the Archean Ancient Gneiss Complex and Granodiorite Suite, Swaziland: A preliminary study

The Ancient Gneiss Complex (AGC) of Swaziland, an Archean gray gneiss complex, lies southeast and south of the Barberton greenstone belt and includes the most structurally complex and highly metamorphosed portions of the eastern Kaapvaal craton. The AGC is not precisely dated but apparently is older than 3.4 Ga. The AGC consists of three major units: (a) a bimodal suite of closely interlayered siliceous, low-K gneisses and metabasalt; (b) homogeneous tonalite gneiss; and (c) interlayered siliceous microcline gneiss, metabasalt, and minor metasedimentary rocks - termed the metamorphite suite. A geologically younger gabbro-diorite-tonalite-trondhjemite suite, the Granodiorite Suite, is spatially associated with the AGC and intrusive into it. The bimodal suite consists largely of two types of low-K siliceous gneiss: one has SiO 2 < 75%, Al 2 O 3 > 14%, low Rb/Sr ratios, and depleted heavy rare earth elements (REE's); the other has SiO 2 > 75%, Al 2 O 3 < 13%, high Rb/Sr ratios, and relatively abundant REE's except for negative Eu anomalies. The interlayered metabasalt ranges from komatiitic to tholeiitic compositions. Lenses of quartz monzonitic gneiss of K 2 O/Na 2 O close to 1 form a minor part of the bimodal suite. Tonalitic to trondhjemitic migmatite locally is abundant and has major-element abundances similar to those of non-migmatitic varieties. The siliceous gneisses of the metamorphic suite show low Al 2 O, K 2 O/Na 2 O ratios of about 1, high Rb/Sr ratios, moderate REE abundances and negative Eu anomalies. K/Rb ratios of siliceous gneisses of the bimodal suite are very low (∼130); of the tonalitic gneiss, low (∼225); of the siliceous gneiss of the metamorphite suite, moderate (∼300); and of the Granodiorite Suite, high (∼400). Rocks of the AGC differ geochemically in several ways from the siliceous volcanic and hypabyssal rocks of the Upper Onverwacht Group and from the diapirs of tonalite and trondhjemite that intrude the Swaziland Group.

Precambrian Research↗

USGS2004

Comparison of in situ uranium KD values with a laboratory determined surface complexation model

Reactive solute transport simulations in groundwater require a large number of parameters to describe hydrologic and chemical reaction processes. Appropriate methods for determining chemical reaction parameters required for reactive solute transport simulations are still under investigation. This work compares U(VI) distribution coefficients (i.e. KD values) measured under field conditions with KD values calculated from a surface complexation model developed in the laboratory. Field studies were conducted in an alluvial aquifer at a former U mill tailings site near the town of Naturita, CO, USA, by suspending approximately 10 g samples of Naturita aquifer background sediments (NABS) in 17-5.1-cm diameter wells for periods of 3 to 15 months. Adsorbed U(VI) on these samples was determined by extraction with a pH 9.45 NaHCO3/Na2CO3 solution. In wells where the chemical conditions in groundwater were nearly constant, adsorbed U concentrations for samples taken after 3 months of exposure to groundwater were indistinguishable from samples taken after 15 months. Measured in situ K D values calculated from the measurements of adsorbed and dissolved U(VI) ranged from 0.50 to 10.6 mL/g and the KD values decreased with increasing groundwater alkalinity, consistent with increased formation of soluble U(VI)-carbonate complexes at higher alkalinities. The in situ K D values were compared with KD values predicted from a surface complexation model (SCM) developed under laboratory conditions in a separate study. A good agreement between the predicted and measured in situ KD values was observed. The demonstration that the laboratory derived SCM can predict U(VI) adsorption in the field provides a critical independent test of a submodel used in a reactive transport model. ?? 2004 Elsevier Ltd. All rights reserved.

Applied Geochemistry↗

USGS2004

Surface complexation model of uranyl sorption on Georgia kaolinite

The adsorption of uranyl on standard Georgia kaolinites (KGa-1 and KGa-1B) was studied as a function of pH (3–10), total U (1 and 10 μmol/l), and mass loading of clay (4 and 40 g/l). The uptake of uranyl in air-equilibrated systems increased with pH and reached a maximum in the near-neutral pH range. At higher pH values, the sorption decreased due to the presence of aqueous uranyl carbonate complexes. One kaolinite sample was examined after the uranyl uptake experiments by transmission electron microscopy (TEM), using energy dispersive X-ray spectroscopy (EDS) to determine the U content. It was found that uraniumwas preferentially adsorbed by Ti-rich impurity phases (predominantly anatase), which are present in the kaolinite samples. Uranyl sorption on the Georgia kaolinites was simulated with U sorption reactions on both titanol and aluminol sites, using a simple non-electrostatic surface complexation model (SCM). The relative amounts of U-binding >TiOH and >AlOH sites were estimated from the TEM/EDS results. A ternary uranyl carbonate complex on the titanol site improved the fit to the experimental data in the higher pH range. The final model contained only three optimised log K values, and was able to simulate adsorption data across a wide range of experimental conditions. The >TiOH (anatase) sites appear to play an important role in retaining U at low uranyl concentrations. As kaolinite often contains trace TiO 2 , its presence may need to be taken into account when modelling the results of sorption experiments with radionuclides or trace metals on kaolinite.

Applied Clay Science↗