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Porosity and pore size distribution in a sedimentary rock: Implications for the distribution of chlorinated solvents

Characterizing properties of the rock matrix that control retention and release of chlorinated solvents is essential in evaluating the extent of contamination and the application of remediation technologies in fractured rock. Core samples from seven closely spaced boreholes in a mudstone subject to trichloroethene (TCE) contamination were analyzed using Mercury Intrusion Porosimetry to investigate porosity and pore size distribution as a function of mudstone characteristics, and depth and lateral extent in the aquifer; organic carbon content was also evaluated to identify the potential for adsorption. Porosity and retardation factor varied over two orders of magnitude, with the largest porosities and largest retardation factors associated with carbon-rich mudstone layers. Larger porosities were also measured in the shallow rock that has been subject to enhanced groundwater flow. Porosity also varied over more than an order of magnitude in spatially continuous mudstone layers. The analyses of the rock cores indicated that the largest pore diameters may be accessible to entry of the nonaqueous form of TCE. Although the porosity associated with the largest pore diameters is small (~ 0.1%), that volume of TCE can significantly affect the total TCE that is retained in the rock matrix. The dimensions of the largest pore diameters may also be accessible to microbes responsible for reductive dechlorination; however, the small percentage of the pore space that can accommodate microbes may limit the extent of reductive dechlorination in the rock matrix.

Journal of Contaminant Hydrology

System characterization report on the German Aerospace Center (DLR) Earth Sensing Imaging Spectrometer (DESIS)

Executive Summary This report addresses system characterization of the German Aerospace Center (DLR) Earth Sensing Imaging Spectrometer (DESIS) and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present the methodology and procedures for characterization and the technical and operational information about the specific sensing system being evaluated. These reports also provide a description of data measurements, data retention practices, and data analysis results and provide system characterization conclusions. In partnership with Teledyne Brown Engineering, DLR built the DESIS hyperspectral instrument, which Teledyne Brown Engineering then integrated onto its International Space Station-based imaging platform, the Multi-User System for Earth Sensing. DLR developed the processing software and, together with Innovative Imaging and Research, completes the validation and calibration of the data products. DESIS was launched in 2018, and the data are used for scientific research in atmospheric physics and Earth sciences. The DESIS sensor contributes to the scientific and commercial utilization of the International Space Station and helps to further hyperspectral remote sensing technologies for future satellites. More information on DLR satellites and sensors is included within the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and at https://www.dlr.de/DE/Home/home_node.html . The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that DESIS has an interior geometric performance of less than a 3.30-meter (less than 0.11 pixel) root mean square error in band-to-band registration, an exterior geometric performance in the range of a 2.40- (0.08 pixel) to 17.40-meter (0.58 pixel) offset in comparison to the Landsat 8 Operational Land Imager, a radiometric performance in the range of −0.013 to 1.011 (offset and slope), and a spatial performance for band 130 of 1.5 pixels at full width at half maximum, with a modulation transfer function at a Nyquist frequency of 0.167.

Open-File Report

Accounting for location uncertainty in azimuthaltelemetry data improves ecological inference

Background Characterizing animal space use is critical for understanding ecological relationships. Animal telemetry technology has revolutionized the fields of ecology and conservation biology by providing high quality spatial data on animal movement. Radio-telemetry with very high frequency (VHF) radio signals continues to be a useful technology because of its low cost, miniaturization, and low battery requirements. Despite a number of statistical developments synthetically integrating animal location estimation and uncertainty with spatial process models using satellite telemetry data, we are unaware of similar developments for azimuthal telemetry data. As such, there are few statistical options to handle these unique data and no synthetic framework for modeling animal location uncertainty and accounting for it in ecological models. We developed a hierarchical modeling framework to provide robust animal location estimates from one or more intersecting or non-intersecting azimuths. We used our azimuthal telemetry model (ATM) to account for azimuthal uncertainty with covariates and propagate location uncertainty into spatial ecological models. We evaluate the ATM with commonly used estimators (Lenth (1981) maximum likelihood and M-Estimators) using simulation. We also provide illustrative empirical examples, demonstrating the impact of ignoring location uncertainty within home range and resource selection analyses. We further use simulation to better understand the relationship among location uncertainty, spatial covariate autocorrelation, and resource selection inference. Results We found the ATM to have good performance in estimating locations and the only model that has appropriate measures of coverage. Ignoring animal location uncertainty when estimating resource selection or home ranges can have pernicious effects on ecological inference. Home range estimates can be overly confident and conservative when ignoring location uncertainty and resource selection coefficients can lead to incorrect inference and over confidence in the magnitude of selection. Furthermore, our simulation study clarified that incorporating location uncertainty helps reduce bias in resource selection coefficients across all levels of covariate spatial autocorrelation. Conclusion The ATM can accommodate one or more azimuths when estimating animal locations, regardless of how they intersect; this ensures that all data collected are used for ecological inference. Our findings and model development have important implications for interpreting historical analyses using this type of data and the future design of radio-telemetry studies.

Movement Ecology

The cartographic and scientific application of ERTS-1 imagery in polar regions

The first Earth Resources Technology Satellite (ERTS-1), launched by the National Aeronautics and Space Administration in. July 1972, is providing valuable data for investigations of the most inaccessible and hostile regions of the Earth the Arctic and Antarctic. ERTS images and map products derived from them offer a whole new dimension in source material for multidiscipline investigations in the earth sciences. For the first time scientists can view synoptic, repetitive scenes of the polar regions in four spectral bands. Ongoing experiments funded by NASA and conducted in the U.S. Geological Survey have demonstrated the feasibility of revising coastlines on maps of Antarctica, detected gross changes in the northern limits of the three largest ice shelves in the world, and led to the discovery of uncharted mountain ranges.

Journal of Research of the U.S. Geological Survey

Hydrogeologic aspects of structural deformation in the northern Gulf of Mexico Basin

The first Earth Resources Technology Satellite (ERTS-1), launched by the National Aeronautics and Space Administration in.July 1972, is providing valuable data for investigations of the most inaccessible and hostile regions of the Earth the Arctic and Antarctic. ERTS images and map products derived from them offer a whole new dimension in source material for multidiscipline investigations in the earth sciences. For the first time scientists can view synoptic, repetitive scenes of the polar regions in four spectral bands. Ongoing experiments funded by NASA and conducted in the U.S. Geological Survey have demonstrated the feasibility of revising coastlines on maps of Antarctica, detected gross changes in the northern limits of the three largest ice shelves in the world, and led to the discovery of uncharted mountain ranges.

Louisiana, Texas

Weathering a Perfect Storm from Space

Extreme space-weather events — intense solar and geomagnetic storms — have occurred in the past: most recently in 1859, 1921 and 1989. So scientists expect that, sooner or later, another extremely intense spaceweather event will strike Earth again. Such storms have the potential to cause widespread interference with and damage to technological systems. A National Academy of Sciences study projects that an extreme space-weather event could end up costing the American economy more than $1 trillion. The question now is whether or not we will take the actions needed to avoid such expensive consequences. Let’s assume that we do. Below is an imagined scenario of how, sometime in the future, an extreme space-weather event might play out.

Earth Magazine

EROS: A space program for Earth resources

The EROS Program, administered by the U. S. Geological Survey, works with representatives of departmental bureaus and offices to coordinate research and application of remote-sensing technology to the day to-day operations of the department. Most of the research and applications have been made possible by the experimental data acquisition systems of the National Aeronautics and Space Administration (NASA). In particular, the EROS Program uses data from the Earth Resources Technology Satellite (ERTS), from the Earth Resources Experiment Package (EREP) of Skylab, and from NASA's Aircraft Program.

General Information Product

Acoustic space occupancy: Combining ecoacoustics and lidar to model biodiversity variation and detection bias across heterogeneous landscapes

There is global interest in quantifying changing biodiversity in human-modified landscapes. Ecoacoustics may offer a promising pathway for supporting multi-taxa monitoring, but its scalability has been hampered by the sonic complexity of biodiverse ecosystems and the imperfect detectability of animal-generated sounds. The acoustic signature of a habitat, or soundscape, contains information about multiple taxa and may circumvent species identification, but robust statistical technology for characterizing community-level attributes is lacking. Here, we present the Acoustic Space Occupancy Model, a flexible hierarchical framework designed to account for detection artifacts from acoustic surveys in order to model biologically relevant variation in acoustic space use among community assemblages. We illustrate its utility in a biologically and structurally diverse Amazon frontier forest landscape, a valuable test case for modeling biodiversity variation and acoustic attenuation from vegetation density. We use complementary airborne lidar data to capture aspects of 3D forest structure hypothesized to influence community composition and acoustic signal detection. Our novel analytic framework permitted us to model both the assembly and detectability of soundscapes using lidar-derived estimates of forest structure. Our empirical predictions were consistent with physical models of frequency-dependent attenuation, and we estimated that the probability of observing animal activity in the frequency channel most vulnerable to acoustic attenuation varied by over 60%, depending on vegetation density. There were also large differences in the biotic use of acoustic space predicted for intact and degraded forest habitats, with notable differences in the soundscape channels predominantly occupied by insects . This study advances the utility of ecoacoustics by providing a robust modeling framework for addressing detection bias from remote audio surveys while preserving the rich dimensionality of soundscape data, which may be critical for inferring biological patterns pertinent to multiple taxonomic groups in the tropics. Our methodology paves the way for greater integration of remotely sensed observations with high-throughput biodiversity data to help bring routine, multi-taxa monitoring to scale in dynamic and diverse landscapes.

Mato Grosso

Volcano geodesy: Challenges and opportunities for the 21st century

Intrusions of magma beneath volcanoes deform the surrounding rock and, if the intrusion is large enough, the overlying ground surface. Numerical models generally agree that, for most eruptions, subsurface volume changes are sufficient to produce measurable deformation at the surface. Studying this deformation can help to determine the location, volume, and shape of a subsurface magma body and thus to anticipate the onset and course of an eruption. This approach has been successfully applied at many restless volcanoes, especially basaltic shields and silicic calderas, using various geodetic techniques and sensors. However, its success at many intermediate-composition strato-volcanoes has been limited by generally long repose intervals, steep terrain, and structural influences that complicate the history and shape of surface deformation. These factors have made it difficult to adequately characterize deformation in space and time at many of the world's dangerous volcanoes. Recent technological advances promise to make this task easier by enabling the acquisition of geodetic data of high spatial and temporal resolution from Earth-orbiting satellites. Synthetic aperture radar interferometry (InSAR) can image ground deformation over large areas at metre-scale resolution over time-scales of a month to a few years. Global Positioning System (GPS) stations can provide continuous information on three-dimensional ground displacements at a network of key sites -information that is especially important during volcanic crises. By using InSAR to determine the shape of the displacement field and GPS to monitor temporal changes at key sites, scientists have a much better chance to capture geodetic signals that have so far been elusive at many volcanoes. This approach has the potential to provide longer-term warnings of impending volcanic activity than is possible with other monitoring techniques.

Philosophical Transactions of the Royal Society A:

Landsat Data Continuity Mission (LDCM) space to ground mission data architecture

The Landsat Data Continuity Mission (LDCM) is a scientific endeavor to extend the longest continuous multi-spectral imaging record of Earth's land surface. The observatory consists of a spacecraft bus integrated with two imaging instruments; the Operational Land Imager (OLI), built by Ball Aerospace & Technologies Corporation in Boulder, Colorado, and the Thermal Infrared Sensor (TIRS), an in-house instrument built at the Goddard Space Flight Center (GSFC). Both instruments are integrated aboard a fine-pointing, fully redundant, spacecraft bus built by Orbital Sciences Corporation, Gilbert, Arizona. The mission is scheduled for launch in January 2013. This paper will describe the innovative end-to-end approach for efficiently managing high volumes of simultaneous realtime and playback of image and ancillary data from the instruments to the reception at the United States Geological Survey's (USGS) Landsat Ground Network (LGN) and International Cooperator (IC) ground stations. The core enabling capability lies within the spacecraft Command and Data Handling (C&DH) system and Radio Frequency (RF) communications system implementation. Each of these systems uniquely contribute to the efficient processing of high speed image data (up to 265Mbps) from each instrument, and provide virtually error free data delivery to the ground. Onboard methods include a combination of lossless data compression, Consultative Committee for Space Data Systems (CCSDS) data formatting, a file-based/managed Solid State Recorder (SSR), and Low Density Parity Check (LDPC) forward error correction. The 440 Mbps wideband X-Band downlink uses Class 1 CCSDS File Delivery Protocol (CFDP), and an earth coverage antenna to deliver an average of 400 scenes per day to a combination of LGN and IC ground stations. This paper will also describe the integrated capabilities and processes at the LGN ground stations for data reception using adaptive filtering, and the mission operations approach fro- the LDCM Mission Operations Center (MOC) to perform the CFDP accounting, file retransmissions, and management of the autonomous features of the SSR.

Conference Paper

Honolulu Magnetic Observatory

Tucked in a grove of thorny mesquite trees, on an ancient coral reef on the south side of the Hawaiian island of Oahu, west of Pearl Harbor, a small unmanned observatory quietly records the Earth’s time-varying magnetic field. The Honolulu Magnetic Observatory is 1 of 14 that the U.S. Geological Survey Geomag­netism Program operates at various locations across the United States and its territories. Data from these observatories, Honolulu, and those operated by institutions in foreign countries, record a variety of magnetic signals related to a wide diversity of physical phenomena in the Earth’s interior and its surrounding outer-space environment. USGS magnetic observatory operations are an integral part of a U.S. National Space Weather Strategy for monitoring and assessing natural hazards that potentially threaten important technological systems.

Hawaii

Museum metabarcoding: a novel method revealing gut helminth communities of small mammals across space and time

Natural history collections spanning multiple decades provide fundamental historical baselines to measure and understand changing biodiversity. New technologies such as next generation DNA sequencing (NGS) have considerably increased the potential of museum specimens to address significant questions regarding the impact of environmental changes on host and parasite/pathogen dynamics. We developed a new technique to identify intestinal helminth parasites and applied it to shrews (Eulipotyphla: Soricidae) because they are ubiquitous, occupy diverse habitats, and host a diverse and abundant parasite fauna. Notably, we included museum specimens preserved in various ways to explore the efficacy of using metabarcoding analyses that may enable identification of helminth symbiont communities from historical archives. We successfully sequenced the parasite communities (using 12S mtDNA, 16S mtDNA, 28S rDNA) of 23 whole gastrointestinal (GI) tracts. All GI tracts were obtained from the Museum of Southwestern Biology (MSB), USA, and from recent field collections, varying both in time since fixation (ranging from 4 months to 16 years) and preservation method (70% or 95% ethanol stored at room temperature, or flash frozen in liquid nitrogen and stored at -80°C). Our proof of concept demonstrates the feasibility of applying NGS techniques to authoritatively identify the parasite/pathogen communities within whole GI tracts from museum specimens of varying age and fixation, and the value of future preservation of host-associated whole GI tracts in public research archives. This powerful approach facilitates future comparative examinations of the distributions and interactions among multiple associated groups of organisms through time and space.

International Journal for Parasitology

Magnetic monitoring in Saguaro National Park

On a sandy, arid plain, near the Rincon Moun­tain Visitor Center of Saguaro National Park, tucked in among brittlebush, creosote, and other hardy desert plants, is an unusual type of observatory—a small unmanned station that is used for monitor­ing the Earth’s variable magnetic field. Named for the nearby city of Tucson, Arizona, the observatory is 1 of 14 that the Geomagnetism Program of the U.S. Geological Survey operates at various locations across the United States and Ter­ritories. Data from USGS magnetic observatories, including the Tucson observatory, as well as observatories operated by institutions in other countries, record a variety of signals related to a wide diversity of physical phenomena in the Earth’s interior and its surrounding outer-space environment. The data are used for geomagnetic mapping and surveying, for fundamental scientific research, and for assessment of magnetic storms, which can be hazardous for the activities and infra­structure of our modern, technologically based society. The U.S. Geological Survey observatory service is an integral part of a U.S. national project for monitoring and assessing space weather hazards.

Arizona

The electric storm of November 1882

In November 1882, an intense magnetic storm related to a large sunspot group caused widespread interference to telegraph and telephone systems and provided spectacular and unusual auroral displays. The (ring current) storm time disturbance index for this storm reached maximum − Dst ≈ 386 nT, comparable to Halloween storm of 29–31 October 2003, but from 17 to 20 November the aa midlatitude geomagnetic disturbance index averaged 214.25 nT, the highest 4 day level of disturbance since the beginning of aa index in 1868. This storm contributed to scientists' understanding of the reality of solar‐terrestrial interaction. Past occurrences of magnetic storms, like that of November 1882, can inform modern evaluations of the deleterious effects that a magnetic superstorm might have on technological systems of importance to society.

Space Weather

Basis function models for animal movement

Advances in satellite-based data collection techniques have served as a catalyst for new statistical methodology to analyze these data. In wildlife ecological studies, satellite-based data and methodology have provided a wealth of information about animal space use and the investigation of individual-based animal–environment relationships. With the technology for data collection improving dramatically over time, we are left with massive archives of historical animal telemetry data of varying quality. While many contemporary statistical approaches for inferring movement behavior are specified in discrete time, we develop a flexible continuous-time stochastic integral equation framework that is amenable to reduced-rank second-order covariance parameterizations. We demonstrate how the associated first-order basis functions can be constructed to mimic behavioral characteristics in realistic trajectory processes using telemetry data from mule deer and mountain lion individuals in western North America. Our approach is parallelizable and provides inference for heterogenous trajectories using nonstationary spatial modeling techniques that are feasible for large telemetry datasets. Supplementary materials for this article are available online.

Journal of the American Statistical Association

Satellite monitoring of cyanobacterial harmful algal bloom frequency in recreational waters and drinking water sources

Cyanobacterial harmful algal blooms (cyanoHAB) cause extensive problems in lakes worldwide, including human and ecological health risks, anoxia and fish kills, and taste and odor problems. CyanoHABs are a particular concern in both recreational waters and drinking water sources because of their dense biomass and the risk of exposure to toxins. Successful cyanoHAB assessment using satellites may provide an indicator for human and ecological health protection. In this study, methods were developed to assess the utility of satellite technology for detecting cyanoHAB frequency of occurrence at locations of potential management interest. The European Space Agency's MEdium Resolution Imaging Spectrometer (MERIS) was evaluated to prepare for the equivalent series of Sentinel-3 Ocean and Land Colour Imagers (OLCI) launched in 2016 as part of the Copernicus program. Based on the 2012 National Lakes Assessment site evaluation guidelines and National Hydrography Dataset, the continental United States contains 275,897 lakes and reservoirs >1 ha in area. Results from this study show that 5.6% of waterbodies were resolvable by satellites with 300 m single-pixel resolution and 0.7% of waterbodies were resolvable when a three by three pixel (3 × 3-pixel) array was applied based on minimum Euclidian distance from shore. Satellite data were spatially joined to U.S. public water surface intake (PWSI) locations, where single-pixel resolution resolved 57% of the PWSI locations and a 3 × 3-pixel array resolved 33% of the PWSI locations. Recreational and drinking water sources in Florida and Ohio were ranked from 2008 through 2011 by cyanoHAB frequency above the World Health Organization’s (WHO) high threshold for risk of 100,000 cells mL −1 . The ranking identified waterbodies with values above the WHO high threshold, where Lake Apopka, FL (99.1%) and Grand Lake St. Marys, OH (83%) had the highest observed bloom frequencies per region. The method presented here may indicate locations with high exposure to cyanoHABs and therefore can be used to assist in prioritizing management resources and actions for recreational and drinking water sources.

Florida, Ohio

Effects of sample gear on estuarine nekton assemblage assessments and food web model simulations

Long-term fisheries-independent sampling data inform population status and trends of species-specific biomass and are often used to drive biomass-based food web models such as the Comprehensive Aquatic Systems Model (CASM). Indicators such as total biomass and mean trophic level derived from these data and from CASM outputs inform management and facilitate assessments of on-going and predicted coastal change and restoration activities on fisheries, but rely on consistent sampling to enable comparisons across space and time. Changes in coastal estuarine gradients, combined with the availability of new sampling technologies, highlight a need to assess the potential consequences of changing sampling technologies on fisheries data and the cascading impact on model outputs. In Louisiana, USA, CASM models are used to inform coastal restoration projects, relying on 40 years of fisheries-independent data derived from 50′ seine sampling. However, alternative use of electrofishers as a sampling method has been proposed to replace the seine sampling. In this study, we examine data from concurrent seine and electrofisher sampling in Barataria Basin, Louisiana, and compare biomass, assemblage data and CASM outputs related to species biomass, food web structure and energy cycling. In a paired comparison of data in 2018–2019, the electrofisher captured higher total catch and diversity compared to the seine. The electrofisher samples were dominated by shrimp (grass, white, brown) and larger bodied fish, while seine samples were dominated by smaller-bodied fish (i.e., anchovy, menhaden). Ecosystem indicators derived from running the CASM using biomass data from seine and electrofisher sampling separately in two different simulation exercises provide contrasting results. In Simulation Exercise 1, the use of different datasets (long-term CASM calibration, 2018–2019 seine, 2018–2019 electrofisher) to initialize the CASM biomasses did not result in large or long-running changes in the simulated biomasses over time. In contrast, in Simulation Exercise 2, CASM model outputs using adjusted gear ratios indicated changes in biomass structure when using electrofisher data, with a doubling of total food web biomass due to the increased shrimp count, and a 13% increase in total energy flow through the food web. Conversions based on area and gear efficiency for overall catch may be useful in maintaining the continuity of historical data. However, differences in species-specific catch due to gear selectivity could have large consequences for constructing and calibrating fish and ecosystem models and remain difficult to reconcile. These differences in assemblages, and estimated biomasses for key food web species, suggest careful consideration in changing gears.

Louisiana

The USGS geomagnetism program and its role in space weather monitoring

Magnetic storms result from the dynamic interaction of the solar wind with the coupled magnetospheric-ionospheric system. Large storms represent a potential hazard for the activities and infrastructure of a modern, technologically based society [Baker et al., 2008]; they can cause the loss of radio communications, reduce the accuracy of global positioning systems, damage satellite electronics and affect satellite operations, increase pipeline corrosion, and induce voltage surges in electric power grids, causing blackouts. So while space weather starts with the Sun and is driven by the solar wind, it is on, or just above, the surface of the Earth that the practical effects of space weather are realized. Therefore, ground-based sensor networks, including magnetic observatories [Love, 2008], play an important role in space weather monitoring.

Space Weather