Recent satellite mapping and coring of the peatland complex of the Congo Basin’s Couvette Centrale region underscores the global significance of this area. Freshwater tropical peatlands in the Congo Basin make up one of Earth’s largest terrestrial carbon sinks which forms an important nexus between global climate, biogeochemical cycling, and biodiversity. These peatlands are also a unique record of past climates, containing microfossil and geochemical proxies documenting past climatic and hydrological conditions in the region, yet there are no published studies of these peatland deposits south of the Congo River in the Democratic Republic of Congo (DRC). Recent coring and radiocarbon dating of peatland core sequences collected from the Couvette Centrale and Mai Ndombe regions of DRC provides new data on the timing of peatland establishment in the Congo Basin. Furthermore, preliminary results of palynological and isotope geochemical analysis shed light on the spatial and temporal variability in regional rainfall regimes for these regions.

Potential evapotranspiration (ETp), defined as the amount of water that would be lost by evaporation and transpiration from an area in the absence of water limitation, is an import hydrometeorological variable. Accurate estimation ETp is critical for a wide range of applications including predictions of, irrigation water requirement, groundwater recharge, stream discharge, drought and wildfires. Long-term change in ETp is considered an indicator of the impact of climate change on ecosystem functioning. A wide range of physically-based and empirical models have been developed to estimate ETp. These methods can be explained in terms of their complexity data requirements. The most complex and demanding models (e.g., Penmann-Montheith) require measurements of radiation, temperature, windspeed, and vapor pressure and have been shown to provide very close approximation of physically measured ET from unstressed systems. On the other extreme, the simplest models require only temperature data (e.g., Thornthwaite, 1948) and are the most commonly implemented. However, without site-specific calibration, methods that depend solely on temperature achieve only modest accuracy. Here we present a machine-learning (ML) approaches that utilize hourly and sub-hourly temperature records to produce predictions that are comparable with the more complex methods that require full meteorological datasets. Specifically, we show that ML algorithms can learn the patterns of temperature fluctuations that are related to attenuation of potential solar radiation. We anticipate the approach developed here will be valuable for estimation of historical ETp as well as for short-term forecasting using temperature forecasts.

A few friends from the big US space place, and two places where people get lots of learning, have started putting together a tiny flying box. This box will look at the tiny bits we can not see in the upper sky. We hope to learn why we see places where the tiny bits of the sky come together in large numbers and other places where the tiny bits try to get as far away from each other as possible. But before we can learn how and why parts of the sky come close together and sometimes far away from each other, we need to finish building our tiny flying box. Then our tiny box will go on a bit up goer to visit where people live in the sky. It will sit there until they have time to push it out and send it on its way around the world. We hope that our tiny flying box will stay working in the sky for at least 6 months. While this is not a long time, our short-lived tiny flying box will help us better understand the upper parts of our sky.

The collection of high-resolution data is helping researchers better understand form, process, and change in river systems and, especially, stream restoration projects. In the last 10 years it has become apparent that there is no “one-size-fits-all” approach to collecting high-resolution data for fluvial studies. The approach we demonstrate here is a self-contained pole aerial photography (PAP) system capable of collecting data for directly georeferenced structure from motion photogrammetry. PAP can produce higher-spatial resolution data than remotely piloted aerial system collected data and is one option where RPAS are restricted, like in parks and protected places. Another advantage of PAP is that it makes 3D data collection possible in parts of rivers, like under riparian canopies, that can elude capture with RPAS methods. Direct georeferencing removes the necessity for ground control points, which can greatly decrease the amount of time needed for a survey. The system that we developed combines a low-cost, dual-frequency GPS receiver capable of Real-time and Post-Processed Kinematic surveying with an off-the-shelf digital SLR camera, an inertial measurement unit, and 3D printed mounts and housings. The open-source control/survey software runs on an inexpensive Raspberry Pi computer with a 7-inch (18 cm) touch screen display. We highlight the accuracy of the system along with the high spatial resolution 3D data, ortho imagery, as well as other data that can be derived from these datasets such as sediment size measurements.

Reservoirs are a globally important source of methane (CH4) to the atmosphere, but measuring CH4 emission rates from reservoirs is difficult due to the spatial and temporal variability in emissions via the emission pathways of ebullition (bubbling) and diffusion. The dominant source of CH4 in reservoirs is production by methanogens in the reservoir sediment, a process that has been widely shown to have a positive correlation with temperature. However, oxidation of CH4 to carbon dioxide by methanotrophs, an important sink for CH4 within lakes, also scales with temperature. Understanding the relationship between reservoir CH4 emission (i.e. production – consumption) and temperature is made more complex by this dual feedback. This study presents results from multiple in-situ monitoring efforts at a small eutrophic reservoir in the Midwest US that look at how CH4 emissions vary with temperature across space and time. Using data sets from eddy covariance monitoring as well as inverted funnels, we found strong log relationships between daily average CH4 fluxes and daily average sediment temperature, with R2 values of 0.58, 0.45, and 0.7 for the eddy covariance data, the inverted funnel deployed at the 1.3-m site (“shallow”), and the inverted funnel deployed at the 8-m site (“deep”), respectively. The Q10 values for the shallow and deep site were 32 and 20, respectively, indicating a stronger dependence on temperature at the shallow site. However, both the shallow and deep sites had similar emission rates, scaling with relative maximum sediment temperature at each respective site. Sediment temperature was also found to be the second most important variable input to the artificial neural network used for gap-filling the eddy covariance CH4 fluxes (after wind speed). Improving our understanding of the temperature – methane emission feedback in freshwaters will enhance our ability to predict future global methane emissions.

Seamounts can be habitats and hazards to submarine navigation, and their distribution reveals the volcanic history of the oceans. As only a few percent of ocean floor has been sounded, seamount distribution must be mapped by satellite altimetry. Wessel (doi:10.1029/2000JB000083) looked at data from an earlier generation of altimeter technology and suggested that all seamounts 2 km and taller had been found, but there might be as many as 50,000 seamounts between 1–2 km tall that were not yet found. The AltiKa altimeter delivers more precise sea level measurements at a higher along-track sampling rate than previous altimeters. These data resolve small seamounts not previously resolvable (Smith, doi:10.1080/01490419.2015.1014950), particularly if repeat-track profiles are “stacked” and band-pass filtered (Marks and Smith, doi:10.1007/s11001-016-9293-0). These two studies looked at only a few isolated locations where multibeam acoustic depth sounding surveys were available for “ground truth” for tuning a band-pass filter to detect the small seamount geoid signal. In the new work we present here we have stacked 32 repeat cycles of SARAL AltiKa data world-wide, and band-pass filtered the stacks, to yield 75,208 potential seamount locations distributed between +/- 81.5 latitude throughout the global ocean. These locations are detected as local maxima in the filtered geoid at least 2 cm above background and with a full-width at half-maximum (FWHM) at least 4 km wide. Of these, 4824 detections were over multibeam surveys. We assign a proxy seamount height to each by subtracting the regional SRTM30 depths from the multibeam depths. These proxy heights follow a Poisson statistical distribution similar to that which fits acoustic bathymetry profiles over seamounts (Jordan et al., doi:10.1029/JB088iB12p10508). We are currently investigating how to derive proxy heights from anomaly amplitude and FWHM, optimizing the trade-off between false negative and false positive detections, and whether it is possible to identify potential seamounts that may pose hazards to submarine navigation.

The unprecedented spatiotemporal resolution of the sixty-four dual electron and ion spectrometers comprising the Fast Plasma Investigation (FPI) onboard the four Magnetospheric Multiscale (MMS) spacecraft enables us to compute terms of the Vlasov equation and thus compare MMS measurements directly to kinetic theory. Here we discuss our techniques for determining spatial and velocity-space gradients of the ion and electron distribution function from the skymaps provided by FPI. We present initial results validating and comparing the contributions from ∂f/∂t, v·∇f, and a·∇vf for a variety of kinetic plasma contexts including both reconnection and non-reconnection events, such as electron diffusion regions (EDRs), magnetic holes, and thin electron-scale current sheets. The ability to resolve gradients of the distribution function motivates comparison of MMS observations to predictions from gyro-kinetic theory and particle-in-cell (PIC) simulations as an approach for determining which physical mechanism is responsible for generating ion and electron crescent distributions observed in association with EDRs and thin boundary layers.

Chemical, biological, radiological, or nuclear (CBRN) releases pose significant environmental and human exposure risks, especially in urban areas with high population densities. The complex nature of a cityscape brings substantial challenges when determining pollutant dispersal within the urban canopy because wind profiles become altered and turbulence is generated in street canyons and in wake of buildings. This can affect downwind and ground level concentrations after a hazardous release. To better understand complex flow conditions, the Department of Homeland Security (DHS) and Defense Threat Reduction Agency (DTRA) initiated a series of controlled field studies called Jack Rabbit II (JRII) in 2015 and 2016. Sequences of 10-20-ton releases of chlorine gas were dispersed within an array of CONEX shipping containers to mimic buildings or other roughness elements. Boundary layer wind flow characteristics were also collected using sonic anemometers, but the data have largely not been analyzed. The goal of this study is to present a preliminary analysis of the JRII wind flow dataset to inform urban adjustments in Gaussian dispersion models. Modifications to the local wind profile and turbulence terms could lead to improved boundary layer parameterizations in dispersion models, which are important for efficient and precise emergency preparation and response.

Coalbed gas is generated during coalification process and remain in the coal as an adsorbed form. This paper discusses the mechanism of generation of coalbed gas and identification of its origin. Two samples has been retrieved from exploratory borehole of Jharia Coalfield. Location of the study area was shown in figure 1. Gas content of these coal samples has been found and some gas is collected in glass bottle from desorption canister. After collection of this adsorbed gas, it was analyzed through gas chromatography and isotopic ratio mass spectrometer. Analyzed coalbed gas contains primarily CH4, ranges from 72.25% to 83.21% and CO2, ranges from 2.63% to 3.05%. Stable isotope geochemistry shows that isotopic fraction is between CH4, C2H6 and CO2. Stable isotopic fractionation and coalbed gas composition is shown in table 1. Isotope of δ13CO2 varies from -21.3% to -17.9%. CDMI and hydrocarbon index (CHC) was also calculated. CDMI index ranges from 3.51 to 3.54 which that coalbed gas might be of thermogenic origin. CHC index ranges from 68.77 to 95.07 % which shows generated CO2 is of organic in nature. Calculated dryness index ranges from 0.986 to 0.990 which shows that coalbed gas is dry to very dry in nature. Coal samples was characterized on the basis of petrochemical and petrographic for the coalbed methane recovery from Jharia Coalfield. Analyzed coalbed gas contains mainly thermogenic methane with substantial amount of biogenic methane. δ13CO2 for biogenic was assumed to be -20% to -15% for the samples. Biogenic proportion for the samples was observed 24.65% and 13.77% respectively while for thermogenic proportion, it was found around 75.35% and 86.23%.

In 2013, the Office of Science and Technology Policy (OSTP) issued a memorandum directing Federal agencies with over $100 million in annual research and development expenditures to develop a plan to support increased access to federally funded research results. In response, the US Geological Survey developed a Public Access Plan and published four new data management policies. The policies focus on review and approval of scientific data supporting scholarly conclusions, requirements for metadata, preservation, and data management planning. The new policies, in conjunction with the Public Access Plan, represent a shift in culture in how the USGS manages and provides access to its science data. The USGS recognizes that successful implementation of these new policies requires multiple pillars of support, from USGS leadership and staff buy-in, to effective tools. Active community engagement in the Bureau is stimulated through the Community for Data Integration (CDI), an open forum for community discussion and engagement, and an important component creating buy-in and contributing to the success of the new policies. Also critical are a suite of tools available to scientists to ensure their ability to implement the policies. Finally, support from leadership that manifests in the Fundamental Science Practices Advisory Council (FSPAC), a committee of representatives from across the Bureau who preside over policies and guidance is a critical component. While far from complete, the USGS has shifted its approach to science data management by engaging the community, offering tools to support policy, and providing leadership support for the quality and scientific integrity of USGS science data.

Previous single-MHD simulations demonstrate that ballooning instability can develop in thin-current sheet configurations of near-Earth magnetotail, which would in turn induce plasmoid formation and three-dimensional magnetic reconnection in absence of inward solar wind flow from magnetopause [1,2]. Our recent two-fluid MHD simulations find that such a mechanism for plasmoid formation in magnetotail remains viable in regimes and scales where Hall and finite-Larmor-radius (FLR) effects become no longer negligible. Both linear and nonlinear calculations are carried out to evaluate the two-fluid effects on the ballooning instability and its consequence, based on a generalized Harris sheet configuration of the magnetotail. Whereas FLR effects reduce and stabilize linear growth of ballooning instability at ion gyroradius scale, Hall effects can significantly increase the number of plasmoids formed along the Earth and tail-ward direction after the nonlinear growth of ballooning instability. The emergence and presence of multiple plasmoids induced by nonlinear ballooning instability suggests a potential origin of the series of neighbouring magnetic islands in magnetotail observed during a substorm expansion phase [3]. References [1] P. Zhu and J. Raeder, Phys. Rev. Lett. 110, 235005 (2013). [2] P. Zhu and J. Raeder, J. Geophys. Res. Space Physics 119, 131-141 (2014). [3] L.-J. Chen et al, Phys. Plasmas 16, 056501 (2009).

This presentation will explore land cover change impacts on hydrology, starting by posing the question: What makes a watershed sensitive to forest disturbance? Despite a long appreciation of the significance of forested watersheds to water supplies—supplying water to more than 180 million people in the U.S.—watershed sensitivity to forest disturbances remains difficult to predict. Individual studies have often contradicted long-standing understanding that forest disturbance leads to increases in total water yield. This research seeks to address the above question by linking a national-scale watershed database with high-resolution forest disturbance imagery. Results indicate that disturbance can caused significant changes (both increases and decreases) in water yield and streamflow timing. Watersheds exhibiting post-disturbance increases or decreases in water yield were found to be distinct from each other (p<0.05) and regional patterns of sensitivity are explored in the context of observable climatic and physiographic variables. The last part of the presentation will explore the development of a multi-algorithm sediment modeling system motivated towards understanding the impacts of changing climate and land cover on sediment yield. Sediment loading driven by current and future hydrological extremes challenges drinking water utilities’ ability to treat water to meet regulatory and public health protection goals. This framework is tested over medium sized (~1000 sq. km) watersheds, with the aim of a larger-scale analysis over the western U.S.

The synergistic use of large datasets from cabled array sensors and remote sensing satellites is vastly under used for studying marine mammals. An important element of assessing long standing shifts in biodiversity within marine environments is to understand the relationship between physical and biological oceanographic variables and the occurrence of these keystone predators. The study area for this project is the California Current Ecosystem, a dynamic and productive coastal and offshore marine ecosystem within the Pacific Northwest region of the United States. This complex environment is influenced by the southward flowing California Current, seasonal changes in wind intensity, and a narrow continental shelf paired with a steep continental slope. A series of long-term, continuous data are collected by the Ocean Observatories Initiative (OOI) and includes physical and biological sensors from fixed and mobile sensors, as well as passive acoustic data from broadband hydrophones. We analyzed recordings collected during 2017 from three recorders located on the shelf (~80 m), slope (~580 m), and from a 200 m platform located above the base of the slope. Detections of sperm whales, delphinid species, humpback whales and fin whales suggest the region is a productive habitat. We combined acoustic derived marine mammal observations with information from the OOI sensors and remotely sensed chlorophyll data to describe ecosystem characteristics and explore indirect measures of prey availability. Our findings provide insight into regional biodiversity and associated physical and biological characteristics in a dynamic region of the northwest Pacific Ocean.

Thunderstorms are often described as consisting of three charge layers: upper positive, central negative, and lower positive. This simple charge structure is inferred from balloon-borne electric field measurements, however, they typically only provide information from a single moving point. Realistic charge structures in thunderclouds are expected to be more complicated than this tripole description for a variety of reasons, including non-trivial updraft geometry, turbulence, and charge deposition by lightning. In order to more fully measure such charge structures, we herein describe the development of an experiment composed of multiple low-cost electric field dropsondes. Each dropsonde consists of two pairs of electrodes where each pair has the electrodes on opposing sides of the device and connected to a differential charge amplifier. The enclosures for the dropsondes are designed so that they spin as they fall which induces charge motion and allows us to measure electric field strength. This electric field data will be transmitted to a ground station in real time along with GPS coordinates. By keeping instrument and recovery costs low, we aim to launch a single balloon payload carrying several of these instruments to drop at intervals to provide a multi-point map of electric field and infer associated charge structures inside a thunderstorm.

Over the past three years Stone Aerospace has developed a novel ice penetrating technology known as a Direct Laser Penetration (DLP). DLP uses laser light carried by an optical fiber to a vertically descending ice penetrator and emitted from the nose to melt the ice in front of it at extremely high power levels and melt rates. A penetrator can be made with an onboard fiber spool connected to a surface-based laser, allowing the hole to re-freeze behind, drastically increasing efficiency and providing isolation from the surface. A parallel spool can pay out a communications fiber to carry information from imagers, fiber-based sensors (e.g. temperature, pressure, seismic), and other optical sensors (e.g. fluorescence or Raman). Laser power levels of up to 100 kW (continuous) at 1070 nm wavelength are now available and can be coupled to these probes. Successful laboratory test results at Antarctic ice temperatures show that this approach could lead to the fastest ice penetration rate available to terrestrial targets, with access to any Antarctic sub-glacial lake in under 16 hours. In this way, DLP offers an alternative to traditional, logistically intense ice drilling: a small footprint system that is fast and can deploy sensor strings through the deepest ice in a short period of time. DLP also shows promise in addressing the ‘starting problem’ for extraterrestrial targets such as Europa or Mars where low pressures prevent the formation of water at the surface and thus heat transfer for traditional melt probe architectures. In order to test the effectiveness of this concept, a Europa environment ‘cryovac’ test facility has been built at Stone Aerospace in Austin, Texas. We will discuss quantitative results from initial lab and chamber tests of the DLP concept, including in an ice column at 100 K temperature subjected to vacuum.

Clay deposits in playa lake/salar environments are now recognized as a significant deposit type for economic concentrations of lithium. Clayton Valley, Nevada, the location of North America’s only lithium brine producer, also has paleo-lacustrine lithium clay deposits of significance, including the Zeus property lithium clay deposit in the eastern part of the valley. This study presents new mineralogical studies on the Zeus property lithium clays to help understand their genesis and the potential economic extraction. The Zeus property (owned by Noram Ventures Ltd.) currently has an inferred resource of 17 million tonnes @ 1060 ppm Li (96,500 tonnes Li2CO3 equivalent). Initial XRD and glycolation techniques for two Zeus property bulk samples, one from the surface (relatively oxidized) and the other from ~35 m depth (relatively reduced) indicate that the clay fraction (~50%) includes smectite, illite/muscovite, chlorite, and a significant amount of amorphous matter believed to be poorly crystalline smectite + illite. The non - clay fraction has calcite, quartz and sanidine. Hectorite, sulfates, borates and halides have not been detected (yet). TIMA (Tescan Integrated Mineral Analyzer, using SEM backscatter and X-ray imaging), and petrography will help determine the mode and mineral chemical compositions in more detail, as well as addressing the relative abundance of authigenic vs. transported clay material. Initial indications are that the smectite and illite are authigenic, and formed in and below a playa lake with evolving lithium (and other cation) concentrations. The lithium budget is likely controlled by smectite and illite. Lithium adsorption onto illite and smectite surfaces and crystal edges is dependent on lithium concentration in brine solutions. Smectite adsorbs significantly higher lithium concentrations and has a higher cation exchange capacity than illite. The apparent absence of hectorite may indicate that smectite and illite formed at low temperatures, away from the influence of hydrothermal fluids and hot springs, which are present on the western side of Clayton Valley. Hectorite is relatively refractory and hinders lithium extraction in weak acid solutions. Leaching tests are underway to determine the most effective methods to extract lithium from the clays, and membrane filtration/ion filtration techniques will be tested for lithium solute concentration and purification.

Monitoring in season crop conditions is critical when assessing the food security situation and prompting action to mitigate adverse outcomes in largely rain-fed agricultural systems. The Group of Earth Observation for Global Agricultural Monitoring (GEOGLAM) has been supporting global assessments for partners in the Agricultural market information system (AMIS) and in countries that are at risk of food insecurity with the Crop Monitor for AMIS and Crop Monitor for Early Warning respectively. Africa, and specifically Kenya is dependent on rain-fed agricultural production and with climate variability and change, timely, relevant and accurate information on crop conditions is necessary to ensure appropriate and sometimes lifesaving responses. By implementation of national crop monitors countries can synthesize and customize information to suit their reporting metrics and provide detailed sub-regional assessments in a standardized format that can inform global and regional assessments. Successful implementation and publication of The Kenya Crop Monitor Bulletin by the Kenyan Ministry of Agriculture and Irrigation is already influencing agricultural decision making. The bulletin is being used to inform internal decision making in the ministry; and through dissemination on the ministry’s website, as an important source of information for food security agencies. The report which combines earth observation data and field reports from county officers, is improving the way food security decisions are being made. Specifically, monitoring the spread of diseases and pests such as the Fall Army Worm, assessing the implications of extreme events such as floods and droughts on production, providing expected trends based on the prevailing conditions and the expected yield outlook at the end of the season. Through the bulletin, the government has also been able to assess the impact of subsidies on production and as an early warning report to prompt for mitigation and other responses.

The Kenyan ASALs (Arid and Semi-Arid Lands) through livestock production, contribute to over 12% of the 40% Agricultural GDP with further contribution through the tourism sector. They cover over 70% of the country and are home to both wildlife and pastoral communities. With dependence on rain-fed pastures, better management of the ASALs require near real time information on available resources. While information on vegetation conditions is important, other critical resources such as location of water, extent of unpalatable invasive species and other ancillary information is required for a comprehensive understanding of the condition of the ASALs. The Rangelands Decision Support tool was developed to address lack timely information for decision making in the ASALs which influences management of available pastures in dry and wet seasons, development of proper grazing plans, livestock movement, conflicts and implementation of conservation measures meant to rehabilitate degraded lands, management of scarce water resources and mitigation of the spread of invasive species. The tool automates data processing from acquisition to development of final products that consist of dekadal NDVI and monthly products (NDVI Z score, absolute anomalies and VCI (Vegetation Condition Index)). Users are able to select suitable products for specific assessment and produce maps at their monitoring units in PDF format. This research present a fully operational processing chain for the data incorporated in the tool and case studies demonstrating application of the different indicators for monitoring at different monitoring units.