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Mobility of organic solvents in water-saturated soil materials

This investigation presents an analysis of the mobility of 37 organic solvents in saturated soil-water systems, focusing on adsorption phenomena at the solid-liquid interface This analysis was made, in part, by applying predictive expressions that estimate the potential magnitude of adsorption by soil materials Of the 37 solvents considered, 19 were classified as either "very highly mobile" or "highly mobile" and, thus, would have little tendency to be retained by soils to a significant extent, 12 were considered to have medium mobility and 6 low mobility None of these solvents were in the immobile class The limited information available indicates that these predictive expressions yield satisfactory first approximations of the magnitude of adsorption of these solvents by soil materials ?? 1985 Springer-Verlag New York Inc.

Environmental Geology and Water Sciences

Streamflow Simulations and Percolation Estimates Using the Soil and Water Assessment Tool for Selected Basins in North-Central Nebraska, 1940-2005

The U.S. Geological Survey, in cooperation with the Upper Elkhorn, Lower Elkhorn, Upper Loup, Lower Loup, Middle Niobrara, Lower Niobrara, Lewis and Clark, and Lower Platte North Natural Resources Districts, used the Soil and Water Assessment Tool to simulate streamflow and estimate percolation in north-central Nebraska to aid development of long-term strategies for management of hydrologically connected ground and surface water. Although groundwater models adequately simulate subsurface hydrologic processes, they often are not designed to simulate the hydrologically complex processes occurring at or near the land surface. The use of watershed models such as the Soil and Water Assessment Tool, which are designed specifically to simulate surface and near-subsurface processes, can provide helpful insight into the effects of surface-water hydrology on the groundwater system. The Soil and Water Assessment Tool was calibrated for five stream basins in the Elkhorn-Loup Groundwater Model study area in north-central Nebraska to obtain spatially variable estimates of percolation. Six watershed models were calibrated to recorded streamflow in each subbasin by modifying the adjustment parameters. The calibrated parameter sets were then used to simulate a validation period; the validation period was half of the total streamflow period of record with a minimum requirement of 10 years. If the statistical and water-balance results for the validation period were similar to those for the calibration period, a model was considered satisfactory. Statistical measures of each watershed model's performance were variable. These objective measures included the Nash-Sutcliffe measure of efficiency, the ratio of the root-mean-square error to the standard deviation of the measured data, and an estimate of bias. The model met performance criteria for the bias statistic, but failed to meet statistical adequacy criteria for the other two performance measures when evaluated at a monthly time step. A primary cause of the poor model validation results was the inability of the model to reproduce the sustained base flow and streamflow response to precipitation that was observed in the Sand Hills region. The watershed models also were evaluated based on how well they conformed to the annual mass balance (precipitation equals the sum of evapotranspiration, streamflow/runoff, and deep percolation). The model was able to adequately simulate annual values of evapotranspiration, runoff, and precipitation in comparison to reported values, which indicates the model may provide reasonable estimates of annual percolation. Mean annual percolation estimated by the model as basin averages varied within the study area from a maximum of 12.9 inches in the Loup River Basin to a minimum of 1.5 inches in the Shell Creek Basin. Percolation also varied within the studied basins; basin headwaters tended to have greater percolation rates than downstream areas. This variance in percolation rates was mainly was because of the predominance of sandy, highly permeable soils in the upstream areas of the modeled basins.

Scientific Investigations Report

Human land-use and soil change

Soil change refers to the alteration of soil and soil properties over time in one location, as opposed to soil variability across space. Although soils change with pedogensis, this chapter focuses on human caused soil change. Soil change can occur with human use and management over long or short time periods and small or large scales. While change can be negative or positive; often soil change is observed when short-term or narrow goals overshadow the other soil’s ecosystem services. Many soils have been changed in their chemical, physical or biological properties through agricultural activities, including cultivation, tillage, weeding, terracing, subsoiling, deep plowing, manure and fertilizer addition, liming, draining, and irrigation. Assessing soil change depends upon the ecosystem services and soil functions being evaluated. The interaction of soil properties with the type and intensity of management and disturbance determines the changes that will be observed. Tillage of cropland disrupts aggregates and decreases soil organic carbon content which can lead to decreased infiltration, increased erosion, and reduced biological function. Improved agricultural management systems can increase soil functions including crop productivity and sustainability. Forest management is most intensive during harvesting and seedling establishment. Most active management in forests causes disturbance of the soil surface which may include loss of forest floor organic materials, increases in bulk density, and increased risk of erosion. In grazing lands, pasture management often includes periods of biological, chemical and physical disturbance in addition to the grazing management imposed on rangelands. Grazing animals have both direct and indirect impacts on soil change. Hoof action can lead to the disturbance of biological crusts and other surface features impairing the soil’s physical, biological and hydrological function. There are clear feedbacks between vegetative systems and soil properties; when vegetation is altered because of grazing or other disturbances, soil property changes often follow. Some soils are very sensitive to management and disturbance and can undergo rapid change: cropping led to massive gully formation in the southeastern USA, exposure of acid-sulfate soils led to irreversible changes in soil minerology and thawing of cold soils has created thermokarst features. These soil changes alter soil properties and functions and may impact soil ecosystem services far into the future.

World Soils Book Series

Soil property and class maps of the conterminous United States at 100-meter spatial resolution

With growing concern for the depletion of soil resources, conventional soil maps need to be updated and provided at finer and finer resolutions to be able to support spatially explicit human–landscape models. Three US soil point datasets—the National Cooperative Soil Survey Characterization Database, the National Soil Information System, and the Rapid Carbon Assessment dataset—were combined with a stack of over 200 environmental datasets and gSSURGO polygon maps to generate complete coverage gridded predictions at 100-m spatial resolution of six soil properties (percentage of organic C, total N, bulk density, pH, and percentage of sand and clay) and two US soil taxonomic classes (291 great groups [GGs] and 78 modified particle size classes [mPSCs]) for the conterminous United States. Models were built using parallelized random forest and gradient boosting algorithms as implemented in the ranger and xgboost packages for R. Soil property predictions were generated at seven standard soil depths (0, 5, 15, 30, 60, 100, and 200 cm). Prediction probability maps for US soil taxonomic classifications were also generated. Cross validation results indicated an out-of-bag classification accuracy of 60% for GGs and 66% for mPSCs; for soil properties, RMSE for leave-location-out cross-validation was 0.74 ( R 2 = 0.68), 17.8 wt% ( R 2 = 0.57), 12 wt% ( R 2 = 0.46), 3.63 wt% ( R 2 = 0.41), 0.2 g cm −3 ( R 2 = 0.42), and 0.27 wt% ( R 2 = 0.39) for pH, percent sand and clay, weight percentage of organic C, bulk density, and weight percentage of total N, respectively. Nine independent validation datasets were used to assess prediction accuracies for soil class models, and results ranged between 24 and 58% and between 24 and 93% for GG and mPSC prediction accuracies, respectively. Although mapping accuracies were variable and likely lower than gSSURGO in some areas, this modeling approach can enable easier integration of soil information with spatially explicit models compared with multicomponent map units.

Soil Science Society of America Journal

Evaluation of Nitrate Concentrations and Sources in the Elk Creek Watershed, Southwestern Ohio, 2003-2004

Nitrate concentrations exceeding the U.S. Environmental Protection Agency maximum contaminant level of 10 milligrams per liter have been reported in ground water near the City of Trenton, Ohio, in the southern part of the Elk Creek watershed. A study of nitrate concentrations and sources in surface and ground water within the Elk Creek watershed was conducted during 2003 and 2004. Nitrate concentrations in the Elk Creek watershed range from less than 0.06 to 11 milligrams per liter. The likely sources of elevated nitrate in the ground water near the City of Trenton appear to be soil organic matter and ammonia fertilizer. Land use is predominantly (93 percent) agricultural, with no identified point sources of nitrate. Likely sources of nitrate in the surface water appear to be manure and septic system effluent, soil organic matter, and ammonia fertilizer. Water-quality constituents, including nitrate, were sampled in water from 38 wells and at 6 surface-water sites. The wells were all shallow (less than 105 feet deep), with open intervals in aquifers of glacial origin, that include tills, outwash, and alluvium. Nitrate concentrations (median of 0.06 milligrams per liter) in the ground water of the upper section of the watershed were lower than those in the lower section of the watershed (median of 4.2 milligrams per liter). Nitrate was analyzed for nitrogen and oxygen isotope values. The d15N and d18O range from -22.36 to +32.29 per mil, and -6.27 to +17.72 per mil, respectively. A positive correlation of d15N and d18O enrichment indicates that denitrification is a prevalent process within the watershed.

Scientific Investigations Report

Agriculture

Agricultural production is a fundamental activity conducted on 45% of the U.S. land area, 55% of Mexico’s land area, and 7% of Canada’s land area (World Bank 2016). Because of this vast spatial extent and the strong role that land management plays in how agricultural ecosystems function, agricultural lands and activities represent a large portion of the North American carbon budget. Accordingly, improved quantification of the agricultural carbon cycle, new trends in agriculture, and added opportunities for emissions reductions provide a critical foundation for considering the relationships between agriculture and carbon cycling at local, regional, continental, and global scales. More than 145 countries have specifically included agriculture in their targets and actions for mitigating climate change (FAO 2016), and agriculture has featured particularly prominently in recent target and action commitments made by developing countries to reduce greenhouse gas (GHG) emissions (Richards et al., 2015). Conversion of vast native forest and prairie to agriculture across North America between 1860 and 1960 resulted in carbon dioxide (CO2) fluxes to the atmosphere from biota and soils that exceeded those from fossil fuel emissions over the same period (Houghton et al., 1983). Correspondingly, soil organic carbon (SOC) declined in many soils during the 50 years following conversion from native ecosystems to production agriculture (Huggins et al., 1998; Janzen et al., 1998; Slobodian et al., 2002). Crop yields and corresponding above- and belowground biomass have steadily increased since the 1930s due to genetic and management innovations, which provide more organic input from which to build SOC ( Johnson et al., 2006; Hatfield and Walthall 2015). This, coupled with improved input-use efficiencies may reduce GHG-emissions per unit yield (GHG intensity), with additional improvements possible through management optimization (Grassini and Cassman 2012; Pittelkow et al., 2015). Options include reducing tillage, integrating perennials onto the landscape, reducing or eliminating bare-fallow land (i.e., land without living plants), adding cover crops, and enrolling lands in conservation easement programs. These options, originally proposed to control erosion, have potential co-benefits in terms of increased soil health, plant productivity, and soil carbon stabilization (Lehman et al., 2015). Conversely, returning lands previously enrolled in conservation easements (e.g., the Conservation Reserve Program [CRP] and other land set-aside efforts) to row-crop production, tillage, or aggressive harvesting of crop residues all risk degrading soil quality and exacerbating SOC loss. Of note is that the net results of land use and land management practices in an agricultural setting vary according to many factors, such as crop or production system type, soil type, climate, and the collection of practices at any given site. For example, many traditional practices followed by Indigenous people on tribal lands are based on an integrated approach to natural resource management and response to environmental change that may provide agricultural options uniquely suited to varied environmental settings (see Ch. 7: Tribal Lands, p. 303). Agricultural land in the United States totaled 408.2 million hectares (ha) in 2014, of which 251 million ha were in permanent meadows and pastures, 152.2 million ha were in arable land, and 2.6 million ha were in permanent crops (FAOSTAT 2016). Compared with the distribution in 2007, these numbers reflect a 4.7 million ha decline in total agricultural lands, driven by declines in arable land and permanent crops but partially offset by a modest increase in permanent meadows and pastures. Although arable lands have been declining, the combined acreage of the four major crops (corn, wheat, soybeans, and cotton) has risen slightly, with increases in land planted in corn and soybeans and decreases in cotton and wheat (see Figure 5.1, p. 232). Despite the overall slight decline in agricultural land area, the value of U.S. agricultural production rose over the past decade as a result of increased production efficiency and higher prices (USDA 2017a; see also www.ers.usda.gov). Canada has about 65 million ha of agricultural land, of which about 46 million ha are arable, accounting for only about 7% of the country’s total land area (FAOSTAT 2017). Prominent crops on Canada’s arable lands include cereals (e.g., wheat, barley, and maize), oilseeds (e.g., canola and soybeans), and pulses (e.g., peas and lentils). Natural and seeded pastures available for grazing in Canada make up about 20 million ha (Legesse et al., 2016). Agricultural land in Mexico makes up 107 million ha, of which 23 million ha are arable land, 2.7 million ha are permanent crops, and 81 million ha are permanent meadows and pastures (FAOSTAT 2017). Mexico’s major crops are fruits, corn, grains, vegetables, and sugarcane.

Report

Comparison and analysis of empirical equations for soil heat flux for different cropping systems and irrigation methods

We evaluated the performance of four models for estimating soil heat flux density (G) in maize (Zea mays L.) and soybean (Glycine max L.) fields under different irrigation methods (center-pivot irrigated fields at Mead, Nebraska, and subsurface drip irrigated field at Clay Center, Nebraska) and rainfed conditions at Mead. The model estimates were compared against measurements made during growing seasons of 2003, 2004, and 2005 at Mead and during 2005, 2006, and 2007 at Clay Center. We observed a strong relationship between the G and net radiation (Rn) ratio (G/Rn) and the normalized difference vegetation index (NDVI). When a significant portion of the ground was bare soil, G/Rn ranged from 0.15 to 0.30 and decreased with increasing NDVI. In contrast to the NDVI progression, the G/Rn ratio decreased with crop growth and development. The G/Rn ratio for subsurface drip irrigated crops was smaller than for the center-pivot irrigated crops. The seasonal average G was 13.1%, 15.2%, 10.9%, and 12.8% of Rn for irrigated maize, rainfed maize, irrigated soybean, and rainfed soybean, respectively. Statistical analyses of the performance of the four models showed a wide range of variation in G estimation. The root mean square error (RMSE) of predictions ranged from 15 to 81.3 W m-2. Based on the wide range of RMSE, it is recommended that local calibration of the models should be carried out for remote estimation of soil heat flux.

Transactions of the ASABE

Evaluating microbial purification during soil treatment of wastewater with multicomponent tracer and surrogate tests

Soil treatment of wastewater has the potential to achieve high purification efficiency, yet the understanding and predictability of purification with respect to removal of viruses and other pathogens is limited. Research has been completed to quantify the removal of virus and bacteria through the use of microbial surrogates and conservative tracers during controlled experiments with three-dimensional pilot-scale soil treatment systems in the laboratory and during the testing of full-scale systems under field conditions. The surrogates and tracers employed included two viruses (MS-2 and PRID-1 bacteriophages), one bacterium (ice-nucleating active Pseudomonas ), and one conservative tracer (bromide ion). Efforts have also been made to determine the relationship between viruses and fecal coliform bacteria in soil samples below the wastewater infiltrative surface, and the correlation between Escherichia coli concentrations measured in percolating soil solution as compared with those estimated from analyses of soil solids. The results suggest episodic breakthrough of virus and bacteria during soil treatment of wastewater and a 2 to 3 log (99-99.9%) removal of virus and near complete removal of fecal coliform bacteria during unsaturated flow through 60 to 90 cm of sandy medium. Results also suggest that the fate of fecal coliform bacteria may be indicative of that of viruses in soil media near the infiltrative surface receiving wastewater effluent. Concentrations of fecal coliform in percolating soil solution may be conservatively estimated from analysis of extracted soil solids.

Journal of Environmental Quality

A comparison of rock and soil samples for geochemical mapping of two porphyry-metal systems in Colorado

Paired rock and soil samples were collected at widely spaced locations in large segments of the porphyry-metal systems of the Montezuma district in central Colorado and of a northwestward extension of the Summitville district into Crater Creek in southern Colorado. The paired samples do not covary closely enough for one sample medium to proxy for the other. However, the areal distributions of elements in both rocks and soils in these two districts conform to alteration zoning as defined by mineralogy. Differing geochemical patterns of rocks and soils reflect species-dependent responses to weathering. Soils appear to be statistically enriched in ore elements and depleted in rock elements as compared to the matching rocks. These differences are largely artificial s owing to different methods of sample preparation and chemical analysis for rocks and for soils. The distributions of metals in soils delineate the occurrence of ore-metal minerals mostly from vein deposits whereas the distributions of metals in rocks conform to zones of pervasive hydrothermal alteration and to the distribution of varied mineral deposits among these zones. Rock and soil samples are equally useful s of comparable map resolution and complement one another as a basis for geochemically mapping these porphyry-metal systems.

Open-File Report

A seasonal agricultural drought forecast system for food-insecure regions of East Africa

The increasing food and water demands of East Africa's growing population are stressing the region's inconsistent water resources and rain-fed agriculture. More accurate seasonal agricultural drought forecasts for this region can inform better water and agricultural management decisions, support optimal allocation of the region's water resources, and mitigate socio-economic losses incurred by droughts and floods. Here we describe the development and implementation of a seasonal agricultural drought forecast system for East Africa (EA) that provides decision support for the Famine Early Warning Systems Network's science team. We evaluate this forecast system for a region of equatorial EA (2° S to 8° N, and 36° to 46° E) for the March-April-May growing season. This domain encompasses one of the most food insecure, climatically variable and socio-economically vulnerable regions in EA, and potentially the world: this region has experienced famine as recently as 2011. To assess the agricultural outlook for the upcoming season our forecast system simulates soil moisture (SM) scenarios using the Variable Infiltration Capacity (VIC) hydrologic model forced with climate scenarios for the upcoming season. First, to show that the VIC model is appropriate for this application we forced the model with high quality atmospheric observations and found that the resulting SM values were consistent with the Food and Agriculture Organization's (FAO's) Water Requirement Satisfaction Index (WRSI), an index used by FEWS NET to estimate crop yields. Next we tested our forecasting system with hindcast runs (1993–2012). We found that initializing SM forecasts with start-of-season (5 March) SM conditions resulted in useful SM forecast skill (> 0.5 correlation) at 1-month, and in some cases at 3 month lead times. Similarly, when the forecast was initialized with mid-season (i.e. 5 April) SM conditions the skill until the end-of-season improved. This shows that early-season rainfall is critical for end-of-season outcomes. Finally we show that, in terms of forecasting spatial patterns of SM anomalies, the skill of this agricultural drought forecast system is generally greater (> 0.8 correlation) during drought years. This means that this system might be particularity useful for identifying the events that present the greatest risk to the region.

Hydrology and Earth System Sciences

Soil gas studies along the Trans-Challis fault system near Idaho City, Boise County, Idaho

Soil gases were sampled along several traverses that cross the Trans-Challis fault system in central Idaho. Anomalous carbon dioxide, hydrogen, oxygen, hydrocarbon, and sulfur gas concentrations coincide with faults and known mineralized areas. Anomalies in areas not known to be mineralized may reflect undiscovered mineral deposits or concealed faults. Soil gases may be a useful exploration guide for mineral deposits in this terrane.

Idaho

Capturing interactions between nitrogen and hydrological cycles under historical climate and land use: Susquehanna watershed analysis with the GFDL land model LM3-TAN

We developed a process model LM3-TAN to assess the combined effects of direct human influences and climate change on terrestrial and aquatic nitrogen (TAN) cycling. The model was developed by expanding NOAA's Geophysical Fluid Dynamics Laboratory land model LM3V-N of coupled terrestrial carbon and nitrogen (C-N) cycling and including new N cycling processes and inputs such as a soil denitrification, point N sources to streams (i.e., sewage), and stream transport and microbial processes. Because the model integrates ecological, hydrological, and biogeochemical processes, it captures key controls of the transport and fate of N in the vegetation–soil–river system in a comprehensive and consistent framework which is responsive to climatic variations and land-use changes. We applied the model at 1/8° resolution for a study of the Susquehanna River Basin. We simulated with LM3-TAN stream dissolved organic-N, ammonium-N, and nitrate-N loads throughout the river network, and we evaluated the modeled loads for 1986–2005 using data from 16 monitoring stations as well as a reported budget for the entire basin. By accounting for interannual hydrologic variability, the model was able to capture interannual variations of stream N loadings. While the model was calibrated with the stream N loads only at the last downstream Susquehanna River Basin Commission station Marietta (40°02' N, 76°32' W), it captured the N loads well at multiple locations within the basin with different climate regimes, land-use types, and associated N sources and transformations in the sub-basins. Furthermore, the calculated and previously reported N budgets agreed well at the level of the whole Susquehanna watershed. Here we illustrate how point and non-point N sources contributing to the various ecosystems are stored, lost, and exported via the river. Local analysis of six sub-basins showed combined effects of land use and climate on soil denitrification rates, with the highest rates in the Lower Susquehanna Sub-Basin (extensive agriculture; Atlantic coastal climate) and the lowest rates in the West Branch Susquehanna Sub-Basin (mostly forest; Great Lakes and Midwest climate). In the re-growing secondary forests, most of the N from non-point sources was stored in the vegetation and soil, but in the agricultural lands most N inputs were removed by soil denitrification, indicating that anthropogenic N applications could drive substantial increase of N 2 O emission, an intermediate of the denitrification process.

Pennsylvania

Fate of trace organic compounds during vadose zone soil treatment in an onsite wastewater system

During onsite wastewater treatment, trace organic compounds are often present in the effluents applied to subsurface soils for advanced treatment during vadose zone percolation and groundwater recharge. The fate of the endocrine-disrupting surfactant metabolites 4-nonylphenol (NP), 4-nonylphenolmonoethoxylate (NP1EO), and 4-nonylphenolmonoethoxycarboxylate (NP1EC), metal-chelating agents ethylenediaminetetraacetic acid (EDTA) and nitrilotriacetic acid (NTA), antimicrobial agent triclosan, stimulant caffeine, and antibiotic sulfamethoxazole during transport through an unsaturated sandy loam soil was studied at a field-scale test site. To assess the effects of effluent quality and hydraulic loading rate (HLR) on compound fate in the soil profile, two effluents (septic tank or textile biofilter) were applied at two design HLRs (2 or 8 cm/d). Chemical concentrations were determined in the two effluents and soil pore water at 60, 120, and 240 cm below the soil infiltrative surface. Concentrations of trace organic compounds in septic tank effluent were reduced by more than 90% during transport through 240 cm (often within 60 cm) of soil, likely due to sorption and biotransformation. However, the concentration of NP increased with depth in the shallow soil profile. Additional treatment of anaerobic septic tank effluent with an aerobic textile biofilter reduced effluent concentrations of many compounds, but generally did not affect any changes in pore water concentrations. The soil profile receiving septic tank effluent (vs. textile biofilter effluent) generally had greater percent removal efficiencies. EDTA, NP, NP1EC, and sulfamethoxazole were measured in soil pore water, indicating the ability of some trace organic compounds to reach shallow groundwater. Risk is highly dependent on the degree of further treatment in the saturated zone and the types and proximity of uses for the receiving groundwater environment.

Environmental Toxicology and Chemistry

POLARIS: A 30-meter probabilistic soil series map of the contiguous United States

A new complete map of soil series probabilities has been produced for the contiguous United States at a 30 m spatial resolution. This innovative database, named POLARIS, is constructed using available high-resolution geospatial environmental data and a state-of-the-art machine learning algorithm (DSMART-HPC) to remap the Soil Survey Geographic (SSURGO) database. This 9 billion grid cell database is possible using available high performance computing resources. POLARIS provides a spatially continuous, internally consistent, quantitative prediction of soil series. It offers potential solutions to the primary weaknesses in SSURGO: 1) unmapped areas are gap-filled using survey data from the surrounding regions, 2) the artificial discontinuities at political boundaries are removed, and 3) the use of high resolution environmental covariate data leads to a spatial disaggregation of the coarse polygons. The geospatial environmental covariates that have the largest role in assembling POLARIS over the contiguous United States (CONUS) are fine-scale (30 m) elevation data and coarse-scale (~ 2 km) estimates of the geographic distribution of uranium, thorium, and potassium. A preliminary validation of POLARIS using the NRCS National Soil Information System (NASIS) database shows variable performance over CONUS. In general, the best performance is obtained at grid cells where DSMART-HPC is most able to reduce the chance of misclassification. The important role of environmental covariates in limiting prediction uncertainty suggests including additional covariates is pivotal to improving POLARIS' accuracy. This database has the potential to improve the modeling of biogeochemical, water, and energy cycles in environmental models; enhance availability of data for precision agriculture; and assist hydrologic monitoring and forecasting to ensure food and water security.

Geoderma

Predicting redox conditions in groundwater at a regional scale

Defining the oxic-suboxic interface is often critical for determining pathways for nitrate transport in groundwater and to streams at the local scale. Defining this interface on a regional scale is complicated by the spatial variability of reaction rates. The probability of oxic groundwater in the Chesapeake Bay watershed was predicted by relating dissolved O 2 concentrations in groundwater samples to indicators of residence time and/or electron donor availability using logistic regression. Variables that describe surficial geology, position in the flow system, and soil drainage were important predictors of oxic water. The probability of encountering oxic groundwater at a 30 m depth and the depth to the bottom of the oxic layer were predicted for the Chesapeake Bay watershed. The influence of depth to the bottom of the oxic layer on stream nitrate concentrations and time lags (i.e., time period between land application of nitrogen and its effect on streams) are illustrated using model simulations for hypothetical basins. Regional maps of the probability of oxic groundwater should prove useful as indicators of groundwater susceptibility and stream susceptibility to contaminant sources derived from groundwater.

Maryland, New York, Pennsylvania, Virginia

Microbial antimony biogeochemistry: Enzymes, regulation, and related metabolic pathways

Antimony (Sb) is a toxic metalloid that occurs widely at trace concentrations in soil, aquatic systems, and the atmosphere. Nowadays, with the development of its new industrial applications and the corresponding expansion of antimony mining activities, the phenomenon of antimony pollution has become an increasingly serious concern. In recent years, research interest in Sb has been growing and reflects a fundamental scientific concern regarding Sb in the environment. In this review, we summarize the recent research on bacterial antimony transformations, especially those regarding antimony uptake, efflux, antimonite oxidation, and antimonate reduction. We conclude that our current understanding of antimony biochemistry and biogeochemistry is roughly equivalent to where that of arsenic was some 20 years ago. This portends the possibility of future discoveries with regard to the ability of microorganisms to conserve energy for their growth from antimony redox reactions and the isolation of new species of “antimonotrophs.”

Applied and Environmental Microbiology

Earthquake and ambient vibration monitoring of the steel-frame UCLA factor building

Dynamic property measurements of the moment-resisting steel-frame University of California, Los Angeles, Factor building are being made to assess how forces are distributed over the building. Fourier amplitude spectra have been calculated from several intervals of ambient vibrations, a 24-hour period of strong winds, and from the 28 March 2003 Encino, California (ML = 2.9), the 3 September 2002 Yorba Linda, California (ML = 4.7), and the 3 November 2002 Central Alaska (Mw = 7.9) earthquakes. Measurements made from the ambient vibration records show that the first-mode frequency of horizontal vibration is between 0.55 and 0.6 Hz. The second horizontal mode has a frequency between 1.6 and 1.9 Hz. In contrast, the first-mode frequencies measured from earthquake data are about 0.05 to 0.1 Hz lower than those corresponding to ambient vibration recordings indicating softening of the soil-structure system as amplitudes become larger. The frequencies revert to pre-earthquake levels within five minutes of the Yorba Linda earthquake. Shaking due to strong winds that occurred during the Encino earthquake dominates the frequency decrease, which correlates in time with the duration of the strong winds. The first shear wave recorded from the Encino and Yorba Linda earthquakes takes about 0.4 sec to travel up the 17-story building. ?? 2005, Earthquake Engineering Research Institute.

Earthquake Spectra

Chapter J: Issues and challenges in the application of geostatistics and spatial-data analysis to the characterization of sand-and-gravel resources

Sand-and-gravel (aggregate) resources are a critical component of the Nation's infrastructure, yet aggregate-mining technologies lag far behind those of metalliferous mining and other sectors. Deposit-evaluation and site-characterization methodologies are antiquated, and few serious studies of the potential applications of spatial-data analysis and geostatistics have been published. However, because of commodity usage and the necessary proximity of a mine to end use, aggregate-resource exploration and evaluation differ fundamentally from comparable activities for metalliferous ores. Acceptable practices, therefore, can reflect this cruder scale. The increasing use of computer technologies is colliding with the need for sand-and-gravel mines to modernize and improve their overall efficiency of exploration, mine planning, scheduling, automation, and other operations. The emergence of megaquarries in the 21st century will also be a contributing factor. Preliminary research into the practical applications of exploratory-data analysis (EDA) have been promising. For example, EDA was used to develop a linear-regression equation to forecast freeze-thaw durability from absorption values for Lower Paleozoic carbonate rocks mined for crushed aggregate from quarries in Oklahoma. Applications of EDA within a spatial context, a method of spatial-data analysis, have also been promising, as with the investigation of undeveloped sand-and-gravel resources in the sedimentary deposits of Pleistocene Lake Bonneville, Utah. Formal geostatistical investigations of sand-and-gravel deposits are quite rare, and the primary focus of those studies that have been completed is on the spatial characterization of deposit thickness and its subsequent effect on ore reserves. A thorough investigation of a gravel deposit in an active aggregate-mining area in central Essex, U.K., emphasized the problems inherent in the geostatistical characterization of particle-size-analysis data. Beyond such factors as common drilling methods jeopardizing the accuracy of the size-distribution curve, the application of formal geostatistical principles has other limitations. Many of the variables used in evaluating gravel deposits, including such sedimentologic parameters as sorting and such United Soil Classification System parameters as gradation coefficient, are nonadditive. Also, uniform sampling methods, such as drilling, are relatively uncommon, and sampling is generally accomplished by a combination of boreholes, water-well logs, test pits, trenches, stratigraphic columns from exposures, and, possibly, some geophysical cross sections. When evaluated in consideration of the fact that uniform mining blocks are also uncommon in practice, subsequent complexities in establishment of the volume/variance relation are inevitable. Several approaches exist to confront the limitations of geostatistical methods in evaluating sand-and-gravel deposits. Initially, we must acknowledge the practical requirements of the aggregate industry, as well as the limitations of the data collected by that industry, as a function of what the industry requires at the practical level, and consider that broader acceptance of formal geostatistics may require modifications of typical exploration and sampling protocols. Future investigations should utilize data from the full spectrum of sand-and-gravel deposits (flood plain, glacial, catastrophic flood, and marine), integrate such other disci plines as sedimentology and geophysics into the research, develop commodity-specific approaches to nonadditive variables, and include the results of comparative drilling.

Bulletin