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At least 685 records · Page 38Linked to original sources
USGS1982

Results of a modeling workshop concerning economic and environmental trends and concomitant resource management issues in the Mobile Bay area

During the past decade, the southern regions of the U.S. have experienced rapid change which is expected to continue into the foreseeable future. Growth in population, industry, and resource development has been attributed to a variety of advantages such as an abundant and inexpensive labor force, a mild climate, and the availability of energy, water, land, and other natural resources. While this growth has many benefits for the region, it also creates the potential for increased air, water, and solid waste pollution, and modification of natural habitats. A workshop was convened to consider the Mobile Bay area as a site-specific case of growth and its environmental consequences in the southern region. The objectives of the modeling workshop were to: (1) identify major factors of economic development as they relate to growth in the area over the immediate and longer term; (2) identify major environmental and resource management issues associated with this expected growth; and (3) identify and characterize the complex interrelationships among economic and environmental factors. This report summarizes the activities and results of a modeling workshop concerning economic growth and concomitant resource management issues in the Mobile Bay area. The workshop was organized around construction of a simulation model representing the relationships between a series of actions and indicators identified by participants. The workshop model had five major components. An Industry Submodel generated scenarios of growth in several industrial and transportation sectors. A Human Population/Economy Submodel calculated human population and economic variables in response to employment opportunities. A Land Use/Air Quality Submodel tabulated changes in land use, shoreline use, and air quality. A Water Submodel calculated indicators of water quality and quantity for fresh surface water, ground water, and Mobile Bay based on discharge information provided by the Industry and Human Population/Economy Submodels. Finally, a Fish Submodel calculated indicators of habitat quality for finfish and shellfish, utilizing information on water quality and wetlands acreage. The workshop was successful in identifying many of the critical interrelations between components of the Mobile area system. Not all of those interactions, such as the feedback of air quality as a limitation on development, could be incorporated into the workshop model because of the model's broad spatial scale and because of uncertainties or data gaps. Thus, the value of the modeling workshop was in the areas outlines below, rather than in the predictive power of the initial model developed at the workshop. First, participants developed a holistic perspective on the interactions which will determine future economic and environmental trends within the Mobile Bay area. Potential environmental consequences and limitations to grown identified at the workshop included: shoreline and water access; water quality of Mobile Bay; finfish and shellfish habitat quality with respect to dissolved oxygen and coliforms; air quality; and acreage of critical wetland habitat. Second, the model's requirements for specific, quantitative information stimulated supporting analyses, such as economic input-output calculations, which provide additional insight into the Mobile Bay area system. Third, the perspective of the Mobile area as an interacting system was developed in an open, cooperative forum which my provide a foundation for conflict resolution based on common understanding. Finally, the identification of model limitations and uncertainties should be useful in guiding the efficient allocation of future research effort.

Alabama↗
USGS2023

Developing fluvial fish species distribution models across the conterminous United States—A framework for management and conservation

This report explains the steps and specific methods used to predict fluvial fish occurrences in their native ranges for the conterminous United States. In this study, boosted regression tree models predict distributions of 271 ecologically important fluvial fish species using relations between fish presence/absence and 22 natural and anthropogenic landscape variables. Models developed for the freshwater portions of the ranges for species represented 28 families. Cyprinidae was the family with the most species (87 of 271) modeled for this study, followed by Percidae (34) and Ictaluridae (17). Model predictive performance was evaluated using four metrics: area under the receiver operating characteristic curve, sensitivity, specificity, and True Skill Statistic, which are all from tenfold cross-validation results. The relative importance of the predictor variables in the boosted regression tree models was calculated and ranked for each species. The three strongest natural predictors of fish distributions were network catchment area, the mean annual air temperature of the local catchment, and the maximum elevation of the local catchment, while the three strongest anthropogenic predictors were downstream main stem dam density, distance to downstream main stem dam, and the percentage of pasture/hay land use area within network catchment boundaries. Study results showed 61 fish species were sensitive to climate variables, and 40 fish species were sensitive to anthropogenic stressors. The models developed in this study can be used to derive critical information regarding habitat protection priorities, anthropogenic threats, and potential effects of climate change on habitat suitability, aiding in efforts to conserve fluvial fishes now and into the future.

Conterminous United States↗
USGS2022

A critical review of bioaccumulation and biotransformation of organic chemicals in birds

A literature review of bioaccumulation and biotransformation of organic chemicals in birds was undertaken, aiming to support scoping and prioritization of future research. The objectives were to characterize available bioaccumulation/biotransformation data, identify knowledge gaps, determine how extant data can be used, and explore the strategy and steps forward. An intermediate approach balanced between expediency and rigor was taken given the vastness of the literature. Following a critical review of > 500 peer-reviewed studies, > 25,000 data entries and 2 million information bytes were compiled on > 700 organic compounds for ~ 320 wild species and 60 domestic breeds of birds. These data were organized into themed databases on bioaccumulation and biotransformation , field survey , microsomal enzyme activity , metabolic pathway , and bird taxonomy and diet . Significant data gaps were identified in all databases at multiple levels. Biotransformation characterization was largely fragmented over metabolite/pathway identification and characterization of enzyme activity or biotransformation kinetics. Limited biotransformation kinetic data constrained development of an avian biotransformation model. A substantial shortage of in vivo biotransformation kinetics has been observed as most reported rate constants were derived in vitro. No metric comprehensively captured all key contaminant classes or chemical groups to support broad-scope modeling of bioaccumulation or biotransformation. However, metrics such as biota-feed accumulation factor, maximum transfer factor, and total elimination rate constant were more readily usable for modeling or benchmarking than other reviewed parameters. Analysis demonstrated the lack of bioaccumulation/biotransformation characterization of shorebirds, seabirds, and raptors. In the study of bioaccumulation and biotransformation of organic chemicals in birds, this review revealed the need for greater chemical and avian species diversity, chemical measurements in environmental media, basic biometrics and exposure conditions, multiple tissues/matrices sampling, and further exploration on biotransformation. Limitations of classical bioaccumulation metrics and current research strategies used in bird studies were also discussed. Forward-looking research strategies were proposed: adopting a chemical roadmap for future investigations, integrating existing biomonitoring data, gap-filling with non-testing approaches, improving data reporting practices, expanding field sampling scopes, bridging existing models and theories, exploring biotransformation via avian genomics, and establishing an online data repository.

Reviews of Environmental Contamination and Toxicol↗
USGS2019

Evaluation of groundwater-flow models for estimating drawdown from proposed groundwater development in Tule Desert, Nevada

At the request of the Bureau of Land Management (BLM), the U.S. Geological Survey (USGS) is releasing with this open-file report (OFR) a previously unpublished review and comparison of two numerical models for Tule Desert, Nevada. The original review was performed in spring 2013, and only minor editorial revisions were made in the current (2019) OFR for clarity and to reformat the original interagency correspondence to the USGS OFR template. No revisions have been made to the technical content of the original review for this OFR release. Report content presented in the purpose and scope statement, and all subsequent sections of the OFR, are original content submitted to BLM in May 2013. Model review and comparisons described in the following paragraphs are based on, in part, results of a long-term (more than 2 years) aquifer test mandated by Nevada State Engineer Order 1169. Additional information on Order 1169 and associated aquifer test results can be found at the State of Nevada Division of Water Resources website (State of Nevada, 2019).

Nevada↗
USGS2016

A modeling approach to compare ΣPCB concentrations between congener-specific analyses

Changes in analytical methods over time pose problems for assessing long-term trends in environmental contamination by polychlorinated biphenyls (PCBs). Congener-specific analyses vary widely in the number and identity of the 209 distinct PCB chemical configurations (congeners) that are quantified, leading to inconsistencies among summed PCB concentrations (ΣPCB) reported by different studies. Here we present a modeling approach using linear regression to compare ΣPCB concentrations derived from different congener-specific analyses measuring different co-eluting groups. The approach can be used to develop a specific conversion model between any two sets of congener-specific analytical data from similar samples (similar matrix and geographic origin). We demonstrate the method by developing a conversion model for an example data set that includes data from two different analytical methods, a low resolution method quantifying 119 congeners and a high resolution method quantifying all 209 congeners. We used the model to show that the 119-congener set captured most (93%) of the total PCB concentration (i.e., Σ 209 PCB) in sediment and biological samples. ΣPCB concentrations estimated using the model closely matched measured values (mean relative percent difference = 9.6). General applications of the modeling approach include (a) generating comparable ΣPCB concentrations for samples that were analyzed for different congener sets; and (b) estimating the proportional contribution of different congener sets to ΣPCB. This approach may be especially valuable for enabling comparison of long-term remediation monitoring results even as analytical methods change over time.

Integrated Environmental Assessment and Management↗
USGS2003

Preliminary metallogenic belt and mineral deposit maps for northeast Asia

The metallogenic belts and locations of major mineral deposits of Northeast Asia are portrayed on Sheets 1-4. Sheet 1 portrays the location of significant lode deposits and placer districts at a scale of 1:7,500,000. Sheets 2-4 portray the metallogenic belts of the region in a series of 12 time-slices from the Archean through the Quaternary at a scale of 1:15,000,000. For all four map sheets, a generalized geodynamics base map, derived from a more detailed map by Parfenov and others (2003), is used as an underlay for the metallogenic belt maps. This geodynamics map underlay permits depicts the major host geologic units and structures that host metallogenic belts. Four tables are included in this report. A hierarchial ranking of mineral deposit models is listed in Table 1. And summary features of lode deposits, placer districts, and metallogenic belts are described in Tables 2, 3, and 4, respectively. The metallogenic belts for Northeast Asia are synthesized, compiled, described, and interpreted with the use of modern concepts of plate tectonics, analysis of terranes and overlap assemblages, and synthesis of mineral deposit models. The data supporting the compilation are: (1) comprehensive descriptions of mineral deposits; (2) compilation and synthesis of a regional geodynamics map the region at 5 million scale with detailed explanations and cited references; and (3) compilation and synthesis of metallogenic belt maps at 15 million scale with detailed explanations and cited references. These studies are part of a major international collaborative study of the Mineral Resources, Metallogenesis, and Tectonics of Northeast Asia that is being conducted from 1997 through 2002 by geologists from earth science agencies and universities in Russia, Mongolia, Northeastern China, South Korea, Japan, and the USA. Companion studies and previous publications are: (1) a detailed geodynamics map of Northeast Asia (Parfenov and 2003); (2) a compilation of major mineral deposit models (Rodionov and Nokleberg, 2000; Rodionov and others, 2000; Obolenskiy and others, 2003); and (3) a database on significant metalliferous and selected nonmetalliferous lode deposits, and selected placer districts (Ariunbileg and others, 2003).

Open-File Report↗
USGS2014

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↗
USGS1981

The U.S. Geological Survey Coal Hydrology Program and the potential of hydrologic models for impact assessments

A requirement of Public Law 95-87, the Surface Mining Control and Reclamation Act of 1977, is the understanding of the hydrology in actual and proposed surface-mined areas. Surface-water data for small specific-sites and for larger areas such as adjacent and general areas are needed also to satisfy the hydrologic requirements of the Act. The Act specifies that surface-water modeling techniques may be used to generate the data and information. The purpose of this report is to describe how this can be achieved for smaller watersheds. This report also characterizes 12 ' state-of-the-art ' strip-mining assessment models that are to be tested with data from two data-intensive studies involving small watersheds in Tennessee and Indiana. Watershed models are best applied to small watersheds with specific-site data. Extending the use of modeling techniques to larger watersheds remains relatively untested, and to date the upper limits for application have not been established. The U.S. Geological Survey is currently collecting regional hydrologic data in the major coal provinces of the United States and this data will be used to help satisfy the ' general-area ' data requirements of the Act. This program is reviewed and described in this report. (USGS)

Open-File Report↗
USGS2017

Simulation of groundwater flow in the glacial aquifer system of northeastern Wisconsin with variable model complexity

The U.S. Geological Survey, National Water-Quality Assessment seeks to map estimated intrinsic susceptibility of the glacial aquifer system of the conterminous United States. Improved understanding of the hydrogeologic characteristics that explain spatial patterns of intrinsic susceptibility, commonly inferred from estimates of groundwater age distributions, is sought so that methods used for the estimation process are properly equipped. An important step beyond identifying relevant hydrogeologic datasets, such as glacial geology maps, is to evaluate how incorporation of these resources into process-based models using differing levels of detail could affect resulting simulations of groundwater age distributions and, thus, estimates of intrinsic susceptibility. This report describes the construction and calibration of three groundwater-flow models of northeastern Wisconsin that were developed with differing levels of complexity to provide a framework for subsequent evaluations of the effects of process-based model complexity on estimations of groundwater age distributions for withdrawal wells and streams. Preliminary assessments, which focused on the effects of model complexity on simulated water levels and base flows in the glacial aquifer system, illustrate that simulation of vertical gradients using multiple model layers improves simulated heads more in low-permeability units than in high-permeability units. Moreover, simulation of heterogeneous hydraulic conductivity fields in coarse-grained and some fine-grained glacial materials produced a larger improvement in simulated water levels in the glacial aquifer system compared with simulation of uniform hydraulic conductivity within zones. The relation between base flows and model complexity was less clear; however, the relation generally seemed to follow a similar pattern as water levels. Although increased model complexity resulted in improved calibrations, future application of the models using simulated particle tracking is anticipated to evaluate if these model design considerations are similarly important for understanding the primary modeling objective - to simulate reasonable groundwater age distributions.

Wisconsin↗
USGS2007

OPR-PPR, a computer program for assessing data importance to model predictions using linear statistics

The OPR-PPR program calculates the Observation-Prediction (OPR) and Parameter-Prediction (PPR) statistics that can be used to evaluate the relative importance of various kinds of data to simulated predictions. The data considered fall into three categories: (1) existing observations, (2) potential observations, and (3) potential information about parameters. The first two are addressed by the OPR statistic; the third is addressed by the PPR statistic. The statistics are based on linear theory and measure the leverage of the data, which depends on the location, the type, and possibly the time of the data being considered. For example, in a ground-water system the type of data might be a head measurement at a particular location and time. As a measure of leverage, the statistics do not take into account the value of the measurement. As linear measures, the OPR and PPR statistics require minimal computational effort once sensitivities have been calculated. Sensitivities need to be calculated for only one set of parameter values; commonly these are the values estimated through model calibration. OPR-PPR can calculate the OPR and PPR statistics for any mathematical model that produces the necessary OPR-PPR input files. In this report, OPR-PPR capabilities are presented in the context of using the ground-water model MODFLOW-2000 and the universal inverse program UCODE_2005. The method used to calculate the OPR and PPR statistics is based on the linear equation for prediction standard deviation. Using sensitivities and other information, OPR-PPR calculates (a) the percent increase in the prediction standard deviation that results when one or more existing observations are omitted from the calibration data set; (b) the percent decrease in the prediction standard deviation that results when one or more potential observations are added to the calibration data set; or (c) the percent decrease in the prediction standard deviation that results when potential information on one or more parameters is added.

Techniques and Methods↗
USGS2023

Approaches for assessing flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM)

The Stochastic Empirical Loading and Dilution Model (SELDM) was designed to help quantify the risk of adverse effects of runoff on receiving waters, the potential need for mitigation measures, and the potential effectiveness of such management measures for reducing these risks. SELDM is calibrated using representative hydrological and water-quality input statistics. This report by the U.S. Geological Survey, in cooperation with the Federal Highway Administration and the Connecticut, Massachusetts, and Rhode Island Departments of Transportation, documents approaches for assessing flows, concentrations, and loads of highway- and urban-runoff and receiving-stream stormwater in southern New England with SELDM. In this report, the term “urban runoff” is used to identify stormwater flows from developed areas with impervious fractions ranging from 10 to 100 percent without regard to the U.S. Census Bureau designation for any given location. There are more than 48,000 delineated road-stream crossings in southern New England, but because there are relatively few precipitation, streamflow, and water-quality monitoring sites in this area, methods were needed to simulate conditions at unmonitored sites. This report documents simulation methods, methods for interpreting stochastic model results, sensitivity analyses to identify the most critical variables of concern, and examples demonstrating how simulation results can be used to inform scientific decision-making processes. Results of 7,511 SELDM simulations were used to do the sensitivity analyses and provide information decisionmakers can use to address runoff-quality issues in southern New England and other areas of the Nation. The sensitivity analyses indicate the relatively strong effect of input variables on variations in output results. These analyses indicate that highway and urban runoff quality and upstream water-quality statistics that vary considerably from site to site have the greatest effect on simulated results. Further data are needed to improve available water-quality statistics, and because the number of monitored sites will never approach the number of sites of interest for water-quality management, research is needed to identify methods to select statistics for unmonitored sites and quantify the uncertainties in the selection process. Hydrologically, prestorm streamflows with and without zero flows are the most sensitive and therefore the most important hydrologic variables to quantify. Results of analyses also are sensitive to statistics used for simulating structural best management practices. Although the focus of the report is on data, statistics, simulation methods, and methods to interpret stochastic simulations, the examples in this report provide results that can be used to inform scientific decision-making processes. The results of 441 simulations that provide regional and site-specific highway and urban runoff yields across southern New England can be used for total maximum daily load analyses. The example stormwater load analysis done for 16 tributaries of the Narragansett Bay demonstrates that highway nitrogen loads are a small fraction of stormwater loads (about 3.6 percent), and a much smaller fraction of all nitrogen loads to the bay, primarily because highways have a small footprint on the land. Examples evaluating the potential effectiveness of end-of-pipe treatment indicate that offsite treatment is warranted in developed areas, and land conservation may be an effective mitigation strategy. The results of these analyses are consistent with conclusions from other simulation and monitoring studies.

Connecticut, Massachusetts, New Hampshire, Rhode I↗
USGS2011

Joint Ecosystem Modeling (JEM) ecological model documentation volume 2: roseate spoonbill ( Platalea ajaja ) landscape habitat suitability index v1.0.0

Ecological conditions in the Greater Everglades have changed due to human activities, including the construction of canals to divert water away from the core of the landscape. Current and planned restoration projects are designed to produce a natural sheetflow of water across the landscape. This restoration of water flow should provide an increase in freshwater needed to restore natural salinities to the fringing estuarine ecosystem. In this report, we describe a Landscape Habitat Suitability Index model designed to evaluate alternative restoration plans for the benefit of a key species, the roseate spoonbill (Platalea ajaja). Model output has shown to be a good indicator of areas capable of supporting spoonbills. Use of this model will allow examination of the potential response of this key species to water management proposed through the Greater Everglades restoration process.

Florida↗
USGS2023

2021–2022 Statewide Abundance Estimates for the Florida Manatee

Knowing the population size of Florida manatees ( Trichechus manatus latirostris ) is critical for conservation and management of this threatened species. Martin et al. (2015) and Hostetler et al. (2018) applied statistical models that incorporated multiple data sources to estimate the statewide abundance of manatees from aerial surveys f lown in 2011–2012 and 2015–2016. We conducted additional aerial surveys in 2021–2022 and applied similar models to provide an updated abundance estimate. This report serves as an update to Hostetler et al. (2018), with most of the text and methodology adapted from the previous report, and provides updated population estimates based on the newly available data. We estimate that the number of manatees in Florida in 2021–2022 was 9,790 (95% Bayesian credible interval 8,350–11,730), of which 4,630 (3,960–5,420) were on the west coast of Florida and 5,160 (3,940–6,980) were on the east coast. These estimates and the associated uncertainty, in addition to being of immediate value to wildlife managers, are essential new data for incorporation into integrated population models and population viability analyses. We also provide context for interpreting the new estimates and perspectives for future modeling improvements.

Florida↗
USGS2008

Data to support statistical modeling of instream nutrient load based on watershed attributes, southeastern United States, 2002

This report presents and describes the digital datasets that characterize nutrient source inputs, environmental characteristics, and instream nutrient loads for the purpose of calibrating and applying a nutrient water-quality model for the southeastern United States for 2002. The model area includes all of the river basins draining to the south Atlantic and the eastern Gulf of Mexico, as well as the Tennessee River basin (referred to collectively as the SAGT area). The water-quality model SPARROW (SPAtially-Referenced Regression On Watershed attributes), developed by the U.S. Geological Survey, uses a regression equation to describe the relation between watershed attributes (predictors) and measured instream loads (response). Watershed attributes that are considered to describe nutrient input conditions and are tested in the SPARROW model for the SAGT area as source variables include atmospheric deposition, fertilizer application to farmland, manure from livestock production, permitted wastewater discharge, and land cover. Watershed and channel attributes that are considered to affect rates of nutrient transport from land to water and are tested in the SAGT SPARROW model as nutrient-transport variables include characteristics of soil, landform, climate, reach time of travel, and reservoir hydraulic loading. Datasets with estimates of each of these attributes for each individual reach or catchment in the reach-catchment network are presented in this report, along with descriptions of methods used to produce them. Measurements of nutrient water quality at stream monitoring sites from a combination of monitoring programs were used to develop observations of the response variable - mean annual nitrogen or phosphorus load - in the SPARROW regression equation. Instream load of nitrogen and phosphorus was estimated using bias-corrected log-linear regression models using the program Fluxmaster, which provides temporally detrended estimates of long-term mean load well-suited for spatial comparisons. The detrended, or normalized, estimates of load are useful for regional-scale assessments but should be used with caution for local-scale interpretations, for which use of loads estimated for actual time periods and employing more detailed regression analysis is suggested. The mean value of the nitrogen yield estimates, normalized to 2002, for 637 stations in the SAGT area is 4.7 kilograms per hectare; the mean value of nitrogen flow-weighted mean concentration is 1.2 milligrams per liter. The mean value of the phosphorus yield estimates, normalized to 2002, for the 747 stations in the SAGT area is 0.66 kilogram per hectare; the mean value of phosphorus flow-weighted mean concentration is 0.17 milligram per liter. Nutrient conditions measured in streams affected by substantial influx or outflux of water and nutrient mass across surface-water basin divides do not reflect nutrient source and transport conditions in the topographic watershed; therefore, inclusion of such streams in the SPARROW modeling approach is considered inappropriate. River basins identified with this concern include south Florida (where surface-water flow paths have been extensively altered) and the Oklawaha, Crystal, Lower Sante Fe, Lower Suwanee, St. Marks, and Chipola River basins in central and northern Florida (where flow exchange with the underlying regional aquifer may represent substantial nitrogen influx to and outflux from the surface-water basins).

Open-File Report↗
USGS2008

Volcan Baru: Eruptive History and Volcano-Hazards Assessment

Volcan Baru is a potentially active volcano in western Panama, about 35 km east of the Costa Rican border. The volcano has had four eruptive episodes during the past 1,600 years, including its most recent eruption about 400?500 years ago. Several other eruptions occurred in the prior 10,000 years. Several seismic swarms in the 20th century and a recent swarm in 2006 serve as reminders of a restless tectonic terrane. Given this history, Volcan Baru likely will erupt again in the near or distant future, following some premonitory period of seismic activity and subtle ground deformation that may last for days or months. Future eruptions will likely be similar to past eruptions?explosive and dangerous to those living on the volcano?s flanks. Outlying towns and cities could endure several years of disruption in the wake of renewed volcanic activity. Described in this open-file report are reconnaissance mapping and stratigraphic studies, radiocarbon dating, lahar-inundation modeling, and hazard-analysis maps. Existing data have been compiled and included to make this report as comprehensive as possible. The report is prepared in coooperation with National Secretariat for Science, Technology and Innovation (SENACYT) of the Republic of Panama and the U.S. Agency for International Development (USAID).

Open-File Report↗
USGS2023

Geology, hydrology, and groundwater contamination in the vicinity of Central Chemical facility, Hagerstown, Maryland

The soil and groundwater at the Central Chemical facility, Hagerstown, Maryland, are contaminated due to the blending and production of pesticides and fertilizers during much of the 20th century. Remedial investigations focus on two operable units (OU) consisting of the surface soils and waste disposal lagoon (OU-1) and the groundwater (OU-2). The contaminants of concern (COC) for groundwater include 41 compounds categorized within the subgroups of volatile organic compounds (VOCs), semi-volatile organic compounds (SVOCs), pesticides, and metals. The purpose of this report is to provide a conceptual site model of the hydrogeology and groundwater contaminant transport at and near the Central Chemical facility. The conceptual model was developed through review, synthesis, and interpretation of the results of hydrogeologic, soil, and other environmental investigations conducted at and in the vicinity of the facility in recent decades and is intended to support plans for environmental remediation of the groundwater in OU-2. The extent and nature of the groundwater contaminant plume associated with the bedrock was characterized for OU-2 of the site. Lithologic and structural comparisons between shallow soil, weathered rock, and epikarst and deeper competent but bedded, dipping, fractured, and karstic limestones illustrate two connected flow systems—a surficial flow system consisting of the unconsolidated overburden and epikarst and a structurally dominant bedrock flow system below the epikarst. Uncertainties exist regarding the nature and transport of contaminants within the epikarst system particularly within voids and perched epikarst water tables. Karst dissolution features are observed within the site including sinkholes and dissolution voids within wells at the site. Of interest, one well in the northern part of the study area (MW-J-71) appears to have a dissolution void connected to an offsite well (OW-2-115) farther to the north. This connection is supported by groundwater level data and elevated concentrations of total suspended solids (TSS) and chlorobenzene in both wells. The high level of TSS supports the possibility of offsite transport of particle-bound contaminants within the conduit system. Episodically elevated concentrations of COC from different groups also were observed within select wells in the epikarst near the waste disposal lagoon (particularly MW-A-51). The variability observed between different COC within the same well may be the result of additional contaminated source materials unrelated to the disposal lagoon. Storage and episodic transport of contaminated material within the epikarst system has the potential to hinder remediation efforts if not considered in the remedial action.

Maryland↗
USGS2010

Use of Continuous Monitors and Autosamplers to Predict Unmeasured Water-Quality Constituents in Tributaries of the Tualatin River, Oregon

Management of water quality in streams of the United States is becoming increasingly complex as regulators seek to control aquatic pollution and ecological problems through Total Maximum Daily Load programs that target reductions in the concentrations of certain constituents. Sediment, nutrients, and bacteria, for example, are constituents that regulators target for reduction nationally and in the Tualatin River basin, Oregon. These constituents require laboratory analysis of discrete samples for definitive determinations of concentrations in streams. Recent technological advances in the nearly continuous, in situ monitoring of related water-quality parameters has fostered the use of these parameters as surrogates for the labor intensive, laboratory-analyzed constituents. Although these correlative techniques have been successful in large rivers, it was unclear whether they could be applied successfully in tributaries of the Tualatin River, primarily because these streams tend to be small, have rapid hydrologic response to rainfall and high streamflow variability, and may contain unique sources of sediment, nutrients, and bacteria. This report evaluates the feasibility of developing correlative regression models for predicting dependent variables (concentrations of total suspended solids, total phosphorus, and Escherichia coli bacteria) in two Tualatin River basin streams: one draining highly urbanized land (Fanno Creek near Durham, Oregon) and one draining rural agricultural land (Dairy Creek at Highway 8 near Hillsboro, Oregon), during 2002-04. An important difference between these two streams is their response to storm runoff; Fanno Creek has a relatively rapid response due to extensive upstream impervious areas and Dairy Creek has a relatively slow response because of the large amount of undeveloped upstream land. Four other stream sites also were evaluated, but in less detail. Potential explanatory variables included continuously monitored streamflow (discharge), stream stage, specific conductance, turbidity, and time (to account for seasonal processes). Preliminary multiple-regression models were identified using stepwise regression and Mallow's Cp, which maximizes regression correlation coefficients and accounts for the loss of additional degrees of freedom when extra explanatory variables are used. Several data scenarios were created and evaluated for each site to assess the representativeness of existing monitoring data and autosampler-derived data, and to assess the utility of the available data to develop robust predictive models. The goodness-of-fit of candidate predictive models was assessed with diagnostic statistics from validation exercises that compared predictions against a subset of the available data. The regression modeling met with mixed success. Functional model forms that have a high likelihood of success were identified for most (but not all) dependent variables at each site, but there were limitations in the available datasets, notably the lack of samples from high-flows. These limitations increase the uncertainty in the predictions of the models and suggest that the models are not yet ready for use in assessing these streams, particularly under high-flow conditions, without additional data collection and recalibration of model coefficients. Nonetheless, the results reveal opportunities to use existing resources more efficiently. Baseline conditions are well represented in the available data, and, for the most part, the models reproduced these conditions well. Future sampling might therefore focus on high flow conditions, without much loss of ability to characterize the baseline. Seasonal cycles, as represented by trigonometric functions of time, were not significant in the evaluated models, perhaps because the baseline conditions are well characterized in the datasets or because the other explanatory variables indirectly incorporate seasonal aspects. Multicollinearity among independent variabl

Scientific Investigations Report↗
USGS2012

Version 3.0 of EMINERS - Economic Mineral Resource Simulator

Quantitative mineral resource assessment, as developed by the U.S. Geological Survey (USGS), consists of three parts: (1) development of grade and tonnage mineral deposit models; (2) delineation of tracts permissive for each deposit type; and (3) probabilistic estimation of the numbers of undiscovered deposits for each deposit type. The estimate of the number of undiscovered deposits at different levels of probability is the input to the EMINERS (Economic Mineral Resource Simulator) program. EMINERS uses a Monte Carlo statistical process to combine probabilistic estimates of undiscovered mineral deposits with models of mineral deposit grade and tonnage to estimate mineral resources. Version 3.0 of the EMINERS program is available as this USGS Open-File Report 2004-1344. Changes from version 2.0 include updating 87 grade and tonnage models, designing new templates to produce graphs showing cumulative distribution and summary tables, and disabling economic filters. The economic filters were disabled because embedded data for costs of labor and materials, mining techniques, and beneficiation methods are out of date. However, the cost algorithms used in the disabled economic filters are still in the program and available for reference for mining methods and milling techniques. The release notes included with this report give more details on changes in EMINERS over the years. EMINERS is written in C++ and depends upon the Microsoft Visual C++ 6.0 programming environment. The code depends heavily on the use of Microsoft Foundation Classes (MFC) for implementation of the Windows interface. The program works only on Microsoft Windows XP or newer personal computers. It does not work on Macintosh computers. For help in using the program in this report, see the "Quick-Start Guide for Version 3.0 of EMINERS-Economic Mineral Resource Simulator" (W.J. Bawiec and G.T. Spanski, 2012, USGS Open-File Report 2009-1057, linked at right). It demonstrates how to execute EMINERS software using default settings and existing deposit models.

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