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At least 415 records · Page 23Linked to original sources

USGS2025

Linking stream-reach nitrogen loads and groundwater “reachsheds” to inform wastewater-nitrogen management actions, Cape Cod, Massachusetts

Study Region Cape Cod, Massachusetts, U.S.A. Study Focus Anthropogenic nitrogen (N) is a key factor in degrading groundwater and surface-water quality, particularly in coastal New England where onsite wastewater systems are prevalent. This study evaluated whether direct N-load measurements in streams on Cape Cod, Massachusetts, coupled with flow-path information from groundwater-flow models, can effectively identify potential land areas where nitrogen mitigation could substantially reduce loads to receiving waters. Nitrogen fluxes were measured along 63 stream reaches during winter and summer and paired with simulated groundwater recharge areas to identify and rank potential areas for reduction of nonpoint-source N inputs. New Hydrologic Insights for the Region Reach-scale nitrate-N loads ranged from −39.1–1182 kg-N/yr per 100 m of stream, indicating spatially variable groundwater inputs across seasons. “Reachsheds” — areas contributing groundwater recharge to specific stream reaches — were delineated using a regional groundwater-flow model. Strong correlations were found between observed N loads and land-use characteristics, especially the number of septic systems and total N inputs from the sum of considered sources. Observed N loads were moderately correlated with recharge area size and wastewater flow estimates. Correlating reach-specific groundwater N loads with land use and parcel-scale nitrogen-yield data identified reachsheds with the highest potential for N load reduction. This approach enables targeted implementation of restoration efforts to optimize nutrient management and support regional load reduction.

Massachusetts↗

USGS2019

Decreased atmospheric nitrogen deposition in eastern North America: Predicted responses of forest ecosystems

Historical increases in emissions and atmospheric deposition of oxidized and reduced nitrogen (N) provided the impetus for extensive, global-scale research investigating the effects of excess N in terrestrial and aquatic ecosystems, with several regions within the Eastern Deciduous Forest of the United States found to be susceptible to negative effects of excess N. The Clean Air Act and associated rules have led to decreases in emissions and deposition of oxidized N, especially in eastern U.S., representing a research challenge and opportunity for ecosystem ecologists and biogeochemists. The purpose of this paper is to predict changes in the structure and function of North American forest ecosystems in a future of decreased N deposition. Hysteresis is a property of a system wherein output is not a strict function of corresponding input, incorporating lag, delay, or history dependence, particularly when the response to decreasing input is different from the response to increasing input. We suggest a conceptual hysteretic model predicting varying lag times in recovery of soil acidification, plant biodiversity, soil microbial communities, forest carbon (C) and N cycling, and surface water chemistry toward pre-N impact conditions. Nearly all of these can potentially respond strongly to reductions in N deposition. Most responses are expected to show some degree of hysteresis, with the greatest delays in response occurring in processes most tightly linked to “slow pools” of N in wood and soil organic matter. Because experimental studies of declines in N loads in forests of North America are lacking and because of the expected hysteresis, it is difficult to generalize from experimental results to patterns expected from declining N deposition. These will likely be long-term phenomena, difficult to distinguish from other, concurrent environmental changes, including elevated atmospheric CO 2 , climate change, reductions in acidity, invasions of new species, and long-term vegetation responses to past disturbance.

Environmental Pollution↗

USGS2009

Chemical weathering of a marine terrace chronosequence, Santa Cruz, California. Part II: Solute profiles, gradients and the comparisons of contemporary and long-term weathering rates

The spatial and temporal changes in hydrology and pore water elemental and 87 Sr/ 86 Sr compositions are used to determine contemporary weathering rates in a 65- to 226-kyr-old soil chronosequence formed from granitic sediments deposited on marine terraces along coastal California. Soil moisture, tension and saturation exhibit large seasonal variations in shallow soils in response to a Mediterranean climate. These climate effects are dampened in underlying argillic horizons that progressively developed in older soils, and reached steady-state conditions in unsaturated horizons extending to depths in excess of 15 m. Hydraulic fluxes (q h ), based on Cl mass balances, vary from 0.06 to 0.22 m yr -1 , resulting in fluid residence times in the terraces of 10-24 yrs. As expected for a coastal environment, the order of cation abundances in soil pore waters is comparable to sea water, i.e., Na > Mg > Ca > K > Sr, while the anion sequence Cl > NO 3 > HCO 3 > SO 4 reflects modifying effects of nutrient cycling in the grassland vegetation. Net Cl-corrected solute Na, K and Si increase with depth, denoting inputs from feldspar weathering. Solute 87 Sr/ 86 Sr ratios exhibit progressive mixing of sea water-dominated precipitation with inputs from less radiogenic plagioclase. While net Sr and Ca concentrations are anomalously high in shallow soils due to biological cycling, they decline with depth to low and/or negative net concentrations. Ca/Mg, Sr/Mg and 87 Sr/ 86 Sr solute and exchange ratios are similar in all the terraces, denoting active exchange equilibration with selectivities close to unity for both detrital smectite and secondary kaolinite. Large differences in the magnitudes of the pore waters and exchange reservoirs result in short-term buffering of the solute Ca, Sr, and Mg. Such buffering over geologic time scales can not be sustained due to declining inputs from residual plagioclase and smectite, implying periodic resetting of the exchange reservoir such as by past vegetational changes and/or climate. Pore waters approach thermodynamic saturation with respect to albite at depth in the younger terraces, indicating that weathering rates ultimately become transport-limited and dependent on hydrologic flux. Contemporary rates R solute are estimated from linear Na and Si pore weathering gradients b solute such that R solute = frac(q h , b solute ?? S v ) where S v is the volumetric surface area and ?? is the stoichiometric coefficient. Plagioclase weathering rates (0.38-2.8 ?? 10 -15 mol m -2 s -1 ) are comparable to those based on 87 Sr/ 86 Sr mass balances and solid-state Na and Ca gradients using analogous gradient approximations. In addition, contemporary solute gradients, under transport-limited conditions, approximate long-term solid-state gradients when normalized against the mass of protolith plagioclase and its corresponding aqueous solubility. The multi-faceted weathering analysis presented in this paper is perhaps the most comprehensive yet applied to a single field study. Within uncertainties of the methods used, present day weathering rates, based on solute characterizations, are comparable to average long-term past rates as evidenced by soil profiles.

Geochimica et Cosmochimica Acta↗

USGS2014

Modeling the influence of organic acids on soil weathering

Biological inputs and organic matter cycling have long been regarded as important factors in the physical and chemical development of soils. In particular, the extent to which low molecular weight organic acids, such as oxalate, influence geochemical reactions has been widely studied. Although the effects of organic acids are diverse, there is strong evidence that organic acids accelerate the dissolution of some minerals. However, the influence of organic acids at the field-scale and over the timescales of soil development has not been evaluated in detail. In this study, a reactive-transport model of soil chemical weathering and pedogenic development was used to quantify the extent to which organic acid cycling controls mineral dissolution rates and long-term patterns of chemical weathering. Specifically, oxalic acid was added to simulations of soil development to investigate a well-studied chronosequence of soils near Santa Cruz, CA. The model formulation includes organic acid input, transport, decomposition, organic-metal aqueous complexation and mineral surface complexation in various combinations. Results suggest that although organic acid reactions accelerate mineral dissolution rates near the soil surface, the net response is an overall decrease in chemical weathering. Model results demonstrate the importance of organic acid input concentrations, fluid flow, decomposition and secondary mineral precipitation rates on the evolution of mineral weathering fronts. In particular, model soil profile evolution is sensitive to kaolinite precipitation and oxalate decomposition rates. The soil profile-scale modeling presented here provides insights into the influence of organic carbon cycling on soil weathering and pedogenesis and supports the need for further field-scale measurements of the flux and speciation of reactive organic compounds.

California↗

USGS2005

Animating the biodynamics of soil thickness using process vector analysis: A dynamic denudation approach to soil formation

This paper expands the dynamic denudation framework of landscape evolution by providing new process insights and details on how soil and its signature morphological feature, the biomantle, form and function in the environment. We examine soils and their biomantles from disparate parts of the world, from the tropics through midlatitudes and hyperarid through perhumid, a range that exhibits varying environments for, and of, life. We then explicate the process pathways that cause soils to thicken and thin, and to even disappear, then reform. We do this by examining thickness relationships, where soil thickness stand biomantle thickness bt are functions of upbuilding u and deepening d minus removal r processes, hence st/bt=f(u+d-r). Upbuilding has two subsets, u1, which includes all exogenous (allochthonous-outside) mineral and/or organic inputs to the soil system, and u2, which includes all endogenous (autochthonous-in situ) processes and productions, including weathering. Exogenous u1 inputs include eolian and slopewash inputs (sedimentations) of mineral and organic materials, mass wasting accumulations and the like. Endogenous u2 processes and productions include the sum of in situ bioturbations, biosynthetic productions, organic accumulations, biovoid productions, weathering and volume increases caused by their sum. Endogenous upbuildings, which dominantly occur in the biomantle, are basically biodynamic bd processes and productions, hence u2=bd. Therefore, if exogenous upbuildings u1 are minimal or zero, then biomantle thickness bt is expressed by bt=f(u2-r) or bt=f(bd-r). Drawing on these relationships, we employ a graphic-conceptual device called process vector analysis in a digital animation (see supplementary materials or cf. https://netfiles.uiuc.edu/jdomier/www/temp/ biomantle.html) that illustrates the main pathways that form both Earth's soil and its unique epidermis, the biomantle. We then discuss the main elements of the animation using still frames that represent thickness turning points. We end by encouraging researchers, instructors and students to view Earth's landforms and soils as integrated dynamic entities that are constantly coevolving elements of a global subaerial-subaqueous continuum. ?? 2004 Elsevier B.V. All rights reserved.

Geomorphology↗

USGS2022

Microbial source tracking and evaluation of best management practices for restoring degraded beaches of Lake Michigan

Attempts to mitigate shoreline microbial contamination require a thorough understanding of pollutant sources, which often requires multiple years of data collection (e.g., point/nonpoint) and the interacting factors that influence water quality. Because restoration efforts can alter shoreline or beach morphology, revisiting source inputs is often necessary. Microbial source tracking (MST) using source-specific molecular markers, genomic community analyses, and physical modeling was used to identify contamination sources along three Lake Michigan beaches of the Laurentian Great Lakes with historically high fecal indicator bacteria (FIB, E. coli ) concentrations. Genetic markers for human (Bacteroides HF183) and mixed gull species ( Catellicoccus marimammalium ) fecal sources were tested from water and sediment. Gene sequencing (16S rRNA) was used to identify similarities in bacterial communities in nearshore water, river inputs, sand, sediment, and groundwater. Synoptic surveys of water exchange were conducted to determine nearshore-offshore interactions of FIB. In addition to these MST studies, best management practices to mitigate FIB, including gull deterrence, slope grading, wetland establishment, and shoreline plantings, were reviewed for their effectiveness at reducing FIB concentrations over time. Using multiple tools for MST helped identify primary and secondary sources of FIB (gulls, stormwater inputs) and the physical processes that exacerbate FIB concentrations (onshore currents, limited circulation). Management actions were successful in the short-term at reducing FIB, but scope of success was temporally limited, with FIB concentrations often rebounding. Results highlight the usefulness of MST to inform best management practices and the need for a sustained adaptive approach that adjusts for changes in the coastal system.

Illinois, Wisconsin↗

USGS2010

Seasonal groundwater contribution to crop-water use assessed with lysimeter observations and model simulations

Groundwater evaporation can play an important role in crop-water use where the water table is shallow. Lysimeters are often used to quantify the groundwater evaporation contribution influenced by a broad range of environmental factors. However, it is difficult for such field facilities, which are operated under limited conditions within limited time, to capture the whole spectrum of capillary upflow with regard to the inter-seasonal variability of climate, especially rainfall. Therefore, in this work, the method of combining lysimeter and numerical experiments was implemented to investigate seasonal groundwater contribution to crop-water use. Groundwater evaporation experiments were conducted through a weighing lysimeter at an agricultural experiment station located within an irrigation district in the lower Yellow River Basin for two winter wheat growth seasons. A HYDRUS-1D model was first calibrated and validated with weighing lysimeter data, and then was employed to perform scenario simulations of groundwater evaporation under different depths to water table (DTW) and water input (rainfall plus irrigation) driven by long term meteorological data. The scenario simulations revealed that the seasonally averaged groundwater evaporation amount was linearly correlated to water input for different values of DTW. The linear regression could explain more than 70% of the variability. The seasonally averaged ratio of the groundwater contribution to crop-water use varied with the seasonal water input and DTW. The ratio reached as high as 75% in the case of DTW=1.0. m and no irrigation, and as low as 3% in the case of DTW=3.0. m and three irrigation applications. The results also revealed that the ratio of seasonal groundwater evaporation to potential evapotranspiration could be fitted to an exponential function of the DTW that may be applied to estimate seasonal groundwater evaporation. In this case study of multilayered soil profile, the depth at which groundwater may evaporate at potential rate was 0.60-0.65. m, and the extinction depth of groundwater evaporation was approximately 3.8. m. ?? 2010 Elsevier B.V.

Journal of Hydrology↗

USGS2020

Changes in sediment source areas to the Amerasia Basin, Arctic Ocean, over the past 5.5 million years based on radiogenic isotopes (Sr, Nd, Pb) of detritus from ferromanganese crusts

Ferromanganese (FeMn) crusts provide a useful paleoenvironmental archive for studying the poorly understood climatic, oceanographic, and geologic evolution of the Arctic Ocean. This study is based on the identification and temporal reconstruction of sources and inferred transport pathways of terrigenous material in FeMn crusts collected from several sites across the Amerasia Basin. Samples from the Alpha Ridge (AR), Mendeleev Ridge (MR), and Chukchi Borderland (CB) have similar chemical compositions and high detrital contents. Sr, Nd, and Pb isotopic compositions of the terrigenous detritus extracted from the FeMn crust layers show spatial and temporal variability due to the variable proportions of inputs from the North American and East Siberian margins and local submarine outcrops. The temporal resolution is restricted by macroscopic crust layers, which represent times of significant changes in the depositional environment and are used to study first-order environmental changes. During the period of ca. 4.4 to 3.8 Myr ago, detritus in the MR area was derived mostly from the Laptev Sea. Then, until about 1.3 Myr ago, FeMn crusts from MR received a higher volcanic component sourced from the East Siberian Sea, with mixing of detritus from the Okhotsk-Chukotka volcanic belt (OCVB) area and possibly weathering of local MR outcrops, which is mostly High Arctic Large Igneous Province (HALIP) rocks. The period from about 1.3 Myr ago to the present reflects enhanced contributions of detritus from the Canadian Shield, approximately equal to the East Siberian contribution for the MR area. CB crusts show three main periods of distinct detrital input. During the period ca. 5.5–5.0 Myr ago, CB detritus was sourced from local submarine outcrops of the Jurassic-Cretaceous HALIP rocks and possibly from northeast Siberia, including OCVB rocks, while during the period from about 5.0 to 3.6 Myr ago, the CB FeMn crusts had a much greater input of detritus from the North American margin. After 3.6 Myr ago, the CB detritus shows a mixed composition predominantly sourced from North America with some material transported from the Bering Sea and smaller contributions from northeast Siberia. The AR crust was influenced mostly by detritus sourced from the Canadian Shield. This study shows that FeMn crusts from the Arctic ocean are a useful tool and archive for climate reconstruction and depositional history of this polar region.

Marine Geology↗

USGS2024

Utilization of stochastic ground motion simulations for scenario-based performance assessment of geo-structures

Probabilistic seismic performance assessments of engineered structures can be highly sensitive to the seismic input excitation and its variability. In the present study, the scenario-based performance assessment recommended by Federal Emergency Management Agency (FEMA) P-58 guidelines is adopted to estimate seismic fragility of concrete dams for various seismic hazard scenarios. Due to the scarcity of recorded ground motions and thereby their poor representation of uncertainties, stochastic ground motion simulation methods are utilized to obtain the required input excitations. Moreover, to understand the uncertainty in ground motion simulation models, two broadband stochastic simulation models are used to generate input excitations representing six seismic hazard scenarios defined by earthquake magnitude, source-to-site distance, and soil conditions. Optimal intensity measure parameters for each scenario are identified using a systematic procedure that considers criteria such as efficiency, practicality, proficiency, sufficiency, and hazard compatibility. Fragility curves and surfaces are derived using the cloud analysis technique, taking into account various damage measures and limit state functions. The study finds that the derived fragility curves are particularly sensitive to the selection of earthquake scenarios, the choice of records, and the methods used to calculate fragility curves, with less sensitivity observed to different engineering demand parameters. Given this sensitivity, particularly to ground motion selection, the study highlights the necessity of incorporating both model-to-model variability (epistemic uncertainty) and record-to-record variability (aleatory uncertainty), alongside the established material and modeling uncertainties, in the probabilistic seismic assessment.

Reliability Engineering and System Safety (RESS)↗

USGS2009

Using LiDAR and quickbird data to model plant production and quantify uncertainties associated with wetland detection and land cover generalizations

Spatiotemporal data from satellite remote sensing and surface meteorology networks have made it possible to continuously monitor global plant production, and to identify global trends associated with land cover/use and climate change. Gross primary production (GPP) and net primary production (NPP) are routinely derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard satellites Terra and Aqua, and estimates generally agree with independent measurements at validation sites across the globe. However, the accuracy of GPP and NPP estimates in some regions may be limited by the quality of model input variables and heterogeneity at fine spatial scales. We developed new methods for deriving model inputs (i.e., land cover, leaf area, and photosynthetically active radiation absorbed by plant canopies) from airborne laser altimetry (LiDAR) and Quickbird multispectral data at resolutions ranging from about 30??m to 1??km. In addition, LiDAR-derived biomass was used as a means for computing carbon-use efficiency. Spatial variables were used with temporal data from ground-based monitoring stations to compute a six-year GPP and NPP time series for a 3600??ha study site in the Great Lakes region of North America. Model results compared favorably with independent observations from a 400??m flux tower and a process-based ecosystem model (BIOME-BGC), but only after removing vapor pressure deficit as a constraint on photosynthesis from the MODIS global algorithm. Fine-resolution inputs captured more of the spatial variability, but estimates were similar to coarse-resolution data when integrated across the entire landscape. Failure to account for wetlands had little impact on landscape-scale estimates, because vegetation structure, composition, and conversion efficiencies were similar to upland plant communities. Plant productivity estimates were noticeably improved using LiDAR-derived variables, while uncertainties associated with land cover generalizations and wetlands in this largely forested landscape were considered less important.

Remote Sensing of Environment↗

USGS2017

A hybrid machine learning model to predict and visualize nitrate concentration throughout the Central Valley aquifer, California, USA

Intense demand for water in the Central Valley of California and related increases in groundwater nitrate concentration threaten the sustainability of the groundwater resource. To assess contamination risk in the region, we developed a hybrid, non-linear, machine learning model within a statistical learning framework to predict nitrate contamination of groundwater to depths of approximately 500 m below ground surface. A database of 145 predictor variables representing well characteristics, historical and current field and landscape-scale nitrogen mass balances, historical and current land use, oxidation/reduction conditions, groundwater flow, climate, soil characteristics, depth to groundwater, and groundwater age were assigned to over 6000 private supply and public supply wells measured previously for nitrate and located throughout the study area. The boosted regression tree (BRT) method was used to screen and rank variables to predict nitrate concentration at the depths of domestic and public well supplies. The novel approach included as predictor variables outputs from existing physically based models of the Central Valley. The top five most important predictor variables included two oxidation/reduction variables (probability of manganese concentration to exceed 50 ppb and probability of dissolved oxygen concentration to be below 0.5 ppm), field-scale adjusted unsaturated zone nitrogen input for the 1975 time period, average difference between precipitation and evapotranspiration during the years 1971–2000, and 1992 total landscape nitrogen input. Twenty-five variables were selected for the final model for log-transformed nitrate. In general, increasing probability of anoxic conditions and increasing precipitation relative to potential evapotranspiration had a corresponding decrease in nitrate concentration predictions. Conversely, increasing 1975 unsaturated zone nitrogen leaching flux and 1992 total landscape nitrogen input had an increasing relative impact on nitrate predictions. Three-dimensional visualization indicates that nitrate predictions depend on the probability of anoxic conditions and other factors, and that nitrate predictions generally decreased with increasing groundwater age.

California↗

USGS2018

Pharmaceutical manufacturing facility discharges can substantially increase the pharmaceutical load to U.S. wastewaters

Discharges from pharmaceutical manufacturing facilities (PMFs) previously have been identified as important sources of pharmaceuticals to the environment. Yet few studies are available to establish the influence of PMFs on the pharmaceutical source contribution to wastewater treatment plants (WWTPs) and waterways at the national scale. Consequently, a national network of 13 WWTPs receiving PMF discharges, six WWTPs with no PMF input, and one WWTP that transitioned through a PMF closure were selected from across the United States to assess the influence of PMF inputs on pharmaceutical loading to WWTPs. Effluent samples were analyzed for 120 pharmaceuticals and pharmaceutical degradates. Of these, 33 pharmaceuticals had concentrations substantially higher in PMF-influenced effluent (maximum 555,000 ng/L) compared to effluent from control sites (maximum 175 ng/L). Concentrations in WWTP receiving PMF input are variable, as discharges from PMFs are episodic, indicating that production activities can vary substantially over relatively short (several months) periods and have the potential to rapidly transition to other pharmaceutical products. Results show that PMFs are an important, national-scale source of pharmaceuticals to the environment.

Science of the Total Environment↗

USGS2020

Evaluating the impacts of foreshore sand and birds on microbiological contamination at a freshwater beach

Beaches along the Great Lakes shorelines are important recreational and economic resources. However, contamination at the beaches can threaten their usage during the swimming season, potentially resulting in beach closures and/or advisories. Thus, understanding the dynamics that control nearshore water quality is integral to effective beach management. There have been significant improvements in this effort, including incorporating modeling (empirical, mechanistic) in recent years. Mechanistic modeling frameworks can contribute to this understanding of dynamics by determining sources and interactions that substantially impact fecal indicator bacteria concentrations, an index routinely used in water quality monitoring programs. To simulate E. coli concentrations at Jeorse Park beaches in southwest Lake Michigan, a coupled hydrodynamic and wave–current interaction model was developed that progressively added contaminant sources from river inputs, avian presence, bacteria–sediment interactions, and bacteria–sand–sediment interactions. Results indicated that riverine inputs affected E. coli concentrations at Jeorse Park beaches only marginally, while avian, shoreline sand, and sediment sources were much more substantial drivers of E. coli contamination at the beach. By including avian and riverine inputs, as well as bacteria–sand–sediment interactions at the beach, models can reasonably capture the variability in observed E. coli concentrations in nearshore water and bed sediments at Jeorse Park beaches. Consequently, it will be crucial to consider avian contamination sources and water-sand-sediment interactions in effective management of the beach for public health and as a recreational resource and to extend these findings to similar beaches affected by shoreline embayment.

Illlinois↗

USGS2000

Lithofacies identification using multiple adaptive resonance theory neural networks and group decision expert system

Lithofacies identification supplies qualitative information about rocks. Lithofacies represent rock textures and are important components of hydrocarbon reservoir description. Traditional techniques of lithofacies identification from core data are costly and different geologists may provide different interpretations. In this paper, we present a low-cost intelligent system consisting of three adaptive resonance theory neural networks and a rule-based expert system to consistently and objectively identify lithofacies from well-log data. The input data are altered into different forms representing different perspectives of observation of lithofacies. Each form of input is processed by a different adaptive resonance theory neural network. Among these three adaptive resonance theory neural networks, one neural network processes the raw continuous data, another processes categorial data, and the third processes fuzzy-set data. Outputs from these three networks are then combined by the expert system using fuzzy inference to determine to which facies the input data should be assigned. Rules are prioritized to emphasize the importance of firing order. This new approach combines the learning ability of neural networks, the adaptability of fuzzy logic, and the expertise of geologists to infer facies of the rocks. This approach is applied to the Appleton Field, an oil field located in Escambia County, Alabama. The hybrid intelligence system predicts lithofacies identity from log data with 87.6% accuracy. This prediction is more accurate than those of single adaptive resonance theory networks, 79.3%, 68.0% and 66.0%, using raw, fuzzy-set, and categorical data, respectively, and by an error-backpropagation neural network, 57.3%. (C) 2000 Published by Elsevier Science Ltd. All rights reserved.

Computers & Geosciences↗

USGS2002

Identification of lithofacies using Kohonen self-organizing maps

Lithofacies identification is a primary task in reservoir characterization. Traditional techniques of lithofacies identification from core data are costly, and it is difficult to extrapolate to non-cored wells. We present a low-cost automated technique using Kohonen self-organizing maps (SOMs) to identify systematically and objectively lithofacies from well log data. SOMs are unsupervised artificial neural networks that map the input space into clusters in a topological form whose organization is related to trends in the input data. A case study used five wells located in Appleton Field, Escambia County, Alabama (Smackover Formation, limestone and dolomite, Oxfordian, Jurassic). A five-input, one-dimensional output approach is employed, assuming the lithofacies are in ascending/descending order with respect to paleoenvironmental energy levels. To consider the possible appearance of new logfacies not seen in training mode, which may potentially appear in test wells, the maximum number of outputs is set to 20 instead of four, the designated number of lithosfacies in the study area. This study found eleven major clusters. The clusters were compared to depositional lithofacies identified by manual core examination. The clusters were ordered by the SOM in a pattern consistent with environmental gradients inferred from core examination: bind/boundstone, grainstone, packstone, and wackestone. This new approach predicted lithofacies identity from well log data with 78.8% accuracy which is more accurate than using a backpropagation neural network (57.3%). The clusters produced by the SOM are ordered with respect to paleoenvironmental energy levels. This energy-related clustering provides geologists and petroleum engineers with valuable geologic information about the logfacies and their interrelationships. This advantage is not obtained in backpropagation neural networks and adaptive resonance theory neural networks. ?? 2002 Elsevier Science Ltd. All rights reserved.

Computers & Geosciences↗

USGS2002

HIBAL: A hydrologic-isotopic-balance model for application to paleolake systems

A simple hydrologic-isotopic-balance (HIBAL) model for application to paleolake ??18O records is presented. Inputs to the model include discharge, on-lake precipitation, evaporation, and the ??18O values of these fluid fluxes. Monthly values of climatic parameters that govern the fractionation of 18O and 16O during evaporation have been extracted from historical data sets and held constant in the model. The ability of the model to simulate changes in the hydrologic balance and the ??18O evolution of the mixed layer has been demonstrated using measured data from Pyramid Lake, Nevada. Simulations of the response in ??18O to step- and periodic-function changes in fluid inputs indicate that the hydrologic balance and ??18O values lag climate change. Input of reconstructed river discharges and their ??18O values to Pyramid and Walker lakes indicates that minima and maxima in simulated ??18O records correspond to minima and maxima in the reconstructed volume records and that the overall shape of the volume and ??18O records is similar. The model was also used in a simulation of abrupt oscillations in the ??18O values of paleo-Owens Lake, California.

Quaternary Science Reviews↗

USGS2002

Hydrographic and particle distributions over the Palos Verdes continental shelf: Spatial, seasonal and daily variability

Moorings and towyo mapping were used to study the temporal and spatial variability of physical processes and suspended particulate material over the continental shelf of the Palos Verdes Peninsula in southwestern Los Angeles, California during the late summer of 1992 and winter of 1992-93. Seasonal evolution of the hydrographic structure is related to seasonal atmospheric forcing. During summer, stratification results from heating of the upper layer. Summer insolation coupled with the stratification results in a slight salinity increase nearsurface due to evaporation. Winter cooling removes much of the upper layer stratification, but winter storms can introduce sufficient quantities of freshwater into the shelf water column again adding stratification through the buoyancy input. Vertical mixing of the low salinity surface water deeper into the water column decreases the sharp nearsurface stratification and reduces the overall salinity of the upper water column. Moored conductivity measurements indicate that the decreased salinity persisted for at least 2 months after a major storm with additional freshwater inputs through the period. Four particulate groups contributed to the suspended particulate load in the water column: phytoplankton, resuspended sediments, and particles in treated sewage effluent were observed in every towyo mapping cruise; terrigenous particles are introduced through runoff from winter rainstorms. Terrigenous suspended particulate material sinks from the water column in <9 days and phytoplankton respond to the stormwater input of buoyancy and nutrients within the same period. The suspended particles near the bottom have spatially patchy distributions, but are always present in hydrographic surveys of the shelf. Temporal variations in these particles do not show a significant tidal response, but they may be maintained in suspension by internal wave and tide processes impinging on the shelf. ?? 2002 Elsevier Science Ltd. All rights reserved.

Continental Shelf Research↗

USGS1999

Sediment chronology in San Francisco Bay, California, defined by 210 Pb, 234 Th, 137 Cs, and 239,340 Pu

Sediment chronologies based on radioisotope depth profiles were developed at two sites in the San Francisco Bay estuary to provide a framework for interpreting historical trends in organic compound and metal contaminant inputs. At Richardson Bay near the estuary mouth, sediments are highly mixed by biological and/or physical processes. Excess penetration ranged from 2 to more than 10 cm at eight coring sites, yielding surface sediment mixing coefficients ranging from 12 to 170 cm 2 /year. At the site chosen for contaminant analyses, excess activity was essentially constant over the upper 25 cm of the core with an exponential decrease below to the supported activity between 70 and 90 cm. Both and penetrated to 57-cm depth and have broad subsurface maxima between 33 and 41 cm. The best fit of the excess profile to a steady state sediment accumulation and mixing model yielded an accumulation rate of 0.825 g/cm 2 /year (0.89 cm/year at sediment surface), surface mixing coefficient of 71 cm 2 /year, and 33-cm mixed zone with a half-Gaussian depth dependence parameter of 9 cm. Simulations of and profiles using these parameters successfully predicted the maximum depth of penetration and the depth of maximum and activity. Profiles of successive 1-year hypothetical contaminant pulses were generated using this parameter set to determine the age distribution of sediments at any depth horizon. Because of mixing, sediment particles with a wide range of deposition dates occur at each depth. A sediment chronology was derived from this age distribution to assign the minimum age of deposition and a date of maximum deposition to a depth horizon. The minimum age of sediments in a given horizon is used to estimate the date of first appearance of a contaminant from its maximum depth of penetration. The date of maximum deposition is used to estimate the peak year of input for a contaminant from the depth interval with the highest concentration of that contaminant. Because of the extensive mixing, sediment-bound constituents are rapidly diluted with older material after deposition. In addition, contaminants persist in the mixed zone for many years after deposition. More than 75 years are required to bury 90% of a deposited contaminant below the mixed zone. Reconstructing contaminant inputs is limited to changes occurring on a 20-year time scale. In contrast, mixing is much lower relative to accumulation at a site in San Pablo Bay. Instead, periods of rapid deposition and/or erosion occurred as indicated by frequent sand-silt laminae in the X-radiograph. , , and excess activity all penetrated to about 120 cm. The distinct maxima in the fallout radionuclides at 105–110 cm yielded overall linear sedimentation rates of 3.9 to 4.1 cm/year, which are comparable to a rate of 4.5±1.5 cm/year derived from the excess profile.

California↗