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USGS2016

Determining CO 2 storage potential during miscible CO 2 enhanced oil recovery: Noble gas and stable isotope tracers

Rising atmospheric carbon dioxide (CO 2 ) concentrations are fueling anthropogenic climate change. Geologic sequestration of anthropogenic CO 2 in depleted oil reservoirs is one option for reducing CO 2 emissions to the atmosphere while enhancing oil recovery. In order to evaluate the feasibility of using enhanced oil recovery (EOR) sites in the United States for permanent CO 2 storage, an active multi-stage miscible CO 2 flooding project in the Permian Basin (North Ward Estes Field, near Wickett, Texas) was investigated. In addition, two major natural CO 2 reservoirs in the southeastern Paradox Basin (McElmo Dome and Doe Canyon) were also investigated as they provide CO 2 for EOR operations in the Permian Basin. Produced gas and water were collected from three different CO 2 flooding phases (with different start dates) within the North Ward Estes Field to evaluate possible CO 2 storage mechanisms and amounts of total CO 2 retention. McElmo Dome and Doe Canyon were sampled for produced gas to determine the noble gas and stable isotope signature of the original injected EOR gas and to confirm the source of this naturally-occurring CO 2 . As expected, the natural CO 2 produced from McElmo Dome and Doe Canyon is a mix of mantle and crustal sources. When comparing CO 2 injection and production rates for the CO 2 floods in the North Ward Estes Field, it appears that CO 2 retention in the reservoir decreased over the course of the three injections, retaining 39%, 49% and 61% of the injected CO 2 for the 2008, 2010, and 2013 projects, respectively, characteristic of maturing CO 2 miscible flood projects. Noble gas isotopic composition of the injected and produced gas for the flood projects suggest no active fractionation, while δ 13 C CO 2 values suggest no active CO 2 dissolution into formation water, or mineralization. CO 2 volumes capable of dissolving in residual formation fluids were also estimated along with the potential to store pure-phase supercritical CO 2 . Using a combination of dissolution trapping and residual trapping, both volumes of CO 2 currently retained in the 2008 and 2013 projects could be justified, suggesting no major leakage is occurring. These subsurface reservoirs, jointly considered, have the capacity to store up to 9 years of CO 2 emissions from an average US powerplant.

International Journal of Greenhouse Gas Control↗

USGS2022

Bathymetry retrieval from CubeSat image sequences with short time lags

The rapid expansion of CubeSat constellations could revolutionize the way inland and nearshore coastal waters are monitored from space. This potential stems from the ability of CubeSats to provide daily imagery with global coverage at meter-scale spatial resolution. In this study, we explore the unique opportunity to improve the retrieval of bathymetry offered by CubeSats, specifically those of the PlanetScope constellation. The orbital design of the PlanetScope constellation enables the acquisition of image sequences with short time lags (from seconds to hours). This characteristic allows multiple images to be captured during a short period of steady bathymetric conditions, especially in dynamic environments like rivers. We hypothesize that taking the ensemble mean of a CubeSat image sequence can enhance bathymetry retrieval compared to standard single-image analysis. Along with the existing optimal band ratio analysis (OBRA) algorithm, we also use a new neural network-based depth retrieval (NNDR) technique to infer bathymetry from both individual and time-averaged images. The two methodologies are evaluated using field data from five different river reaches with depths up to 15 m and both top-of-atmosphere (TOA) radiance and bottom-of-atmosphere (BOA) surface reflectance PlanetScope data products. Despite low spectral resolution and concerns about the radiometric quality of CubeSat imagery, accuracy assessment based on in-situ comparisons indicates the potential (0.52 < R 2 < 0.7 for the NNDR method) of PlanetScope imagery to retrieve depths up to ∼ 10 m in clear water conditions. The proposed image averaging consistently improves bathymetry retrieval over single image analysis. The NNDR technique was found to outperform OBRA, illustrating the importance of leveraging all spectral bands through machine learning approaches. TOA data provided more robust bathymetry results than BOA data for the OBRA technique, but the NNDR technique was minimally impacted by the type of data product.

International Journal of Applied Earth Observation↗

USGS2008

Sensitivity of summer climate to anthropogenic land-cover change over the Greater Phoenix, AZ, region

This work evaluates the first-order effect of land-use/land-cover change (LULCC) on the summer climate of one of the nation's most rapidly expanding metropolitan complexes, the Greater Phoenix, AZ, region. High-resolution-2-km grid spacing-Regional Atmospheric Modeling System (RAMS) simulations of three "wet" and three "dry" summers were carried out for two different land-cover reconstructions for the region: a circa 1992 representation based on satellite observations, and a hypothetical land-cover scenario where the anthropogenic landscape of irrigated agriculture and urban pixels was replaced with current semi-natural vegetation. Model output is evaluated with respect to observed air temperature, dew point, and precipitation. Our results suggest that development of extensive irrigated agriculture adjacent to the urban area has dampened any regional-mean warming due to urbanization. Consistent with previous observationally based work, LULCC produces a systematic increase in precipitation to the north and east of the city, though only under dry conditions. This is due to a change in background atmospheric stability resulting from the advection of both warmth from the urban core and moisture from the irrigated area. ?? 2008 Elsevier Ltd. All rights reserved.

Journal of Arid Environments↗

USGS2017

Spatial variation in edaphic characteristics is a stronger control than nitrogen inputs in regulating soil microbial effects on a desert grass

Increased atmospheric nitrogen (N) deposition can have wide-ranging effects on plant community structure and ecosystem function, some of which may be indirectly mediated by soil microbial responses to an altered biogeochemical environment. In this study, soils from a field N fertilization experiment that spanned a soil texture gradient were used as inocula in the greenhouse to assess the indirect effects of soil microbial communities on growth of a desert grass. Plant performance and interaction with soil microbiota were evaluated via plant above- and belowground biomass, leaf N concentration, and root fungal colonization. Nitrogen fertilization in the field increased the benefits of soil microbial inoculation to plant leaf N concentration, but did not alter the effect of soil microbes on plant growth. Plant-microbe interaction outcomes differed most strongly among sites with different soil textures, where the soil microbial community from the sandiest site was most beneficial to host plant growth. The findings of this study suggest that in a desert grassland, increases in atmospheric N deposition may exert a more subtle influence on plant-microbe interactions by altering plant nutrient status, whereas edaphic factors can alter the whole-plant growth response to soil microbial associates.

Journal of Arid Environments↗

USGS2006

Investigating the role of gas bubble formation and entrapment in contaminated aquifers: Reactive transport modelling

In many natural and contaminated aquifers, geochemical processes result in the production or consumption of dissolved gases. In cases where methanogenesis or denitrification occurs, the production of gases may result in the formation and growth of gas bubbles below the water table. Near the water table, entrapment of atmospheric gases during water table rise may provide a significant source of O 2 to waters otherwise depleted in O 2 . Furthermore, the presence of bubbles will affect the hydraulic conductivity of an aquifer, resulting in changes to the groundwater flow regime. The interactions between physical transport, biogeochemical processes, and gas bubble formation, entrapment and release is complex and requires suitable analysis tools. The objective of the present work is the development of a numerical model capable of quantitatively assessing these processes. The multicomponent reactive transport code MIN3P has been enhanced to simulate bubble growth and contraction due to in-situ gas production or consumption, bubble entrapment due to water table rise and subsequent re-equilibration of the bubble with ambient groundwater, and permeability changes due to trapped gas phase saturation. The resulting formulation allows for the investigation of complex geochemical systems where microbially mediated redox reactions both produce and consume gases as well as affect solution chemistry, alkalinity, and pH. The enhanced model has been used to simulate processes in a petroleum hydrocarbon contaminated aquifer where methanogenesis is an important redox process. The simulations are constrained by data from a crude oil spill site near Bemidji, MN. Our results suggest that permeability reduction in the methanogenic zone due to in-situ formation of gas bubbles, and dissolution of entrapped atmospheric bubbles near the water table, both work to attenuate the dissolved gas plume emanating from the source zone. Furthermore, the simulations demonstrate that under the given conditions more than 50% of all produced CH 4 partitions to the gas phase or is aerobically oxidised near the water table, suggesting that these processes should be accounted for when assessing the rate and extent of methanogenic degradation of hydrocarbons.

Journal of Contaminant Hydrology↗

USGS2023

Future climate-induced changes in mixing and deep oxygen content of a caldera lake with hydrothermal heat and salt inputs

Vertical profiles of temperature, salinity and dissolved oxygen in Crater Lake, a caldera lake in the Oregon Cascade Range that receives hydrothermal inputs of heat and salt, were simulated with a 1-dimensional model. Twelve Global Circulation Models and two Representative Concentration Pathways (RCPs) were used to develop boundary conditions from 1950 to 2099. The model simulated the ventilation of deep water initiated by reverse stratification and subsequent thermobaric instability. All models predicted a reduction in the frequency of deep ventilation events, from an ensemble median frequency of 5.4 winters decade−1 during 1950–2005 to 4.3 (RCP4.5) or 2.5 (RCP8.5) winters decade−1 during 2045–2099. Favorable conditions for thermobaric instability-induced mixing currently occur infrequently and will become rare in the future. The salinity gradient resulting from hydrothermal inputs presents an additional barrier to thermobaric instability that will continue through 2099. A redistribution of salt to the deep lake may prevent ventilation all the way to the bottom in the future. Hypolimnetic dissolved oxygen percent saturation remained above 75% within the 21st century, consistent with oligotrophy and very small oxygen demands. The rate of change in all variables accelerated approaching 2099, coincident with elimination of winter reverse stratification. Historically, about half of the hydrothermal heat added to Crater Lake has been vented to the atmosphere. In the RCP8.5 scenario, the hydrothermal heat will cease to be vented to the atmosphere by the end of the 21st century, and then the temperature of the deep waters will increase rapidly.

Oregon↗

USGS2016

Uncertainty analysis of the Operational Simplified Surface Energy Balance (SSEBop) model at multiple flux tower sites

Evapotranspiration (ET) is an important component of the water cycle – ET from the land surface returns approximately 60% of the global precipitation back to the atmosphere. ET also plays an important role in energy transport among the biosphere, atmosphere, and hydrosphere. Current regional to global and daily to annual ET estimation relies mainly on surface energy balance (SEB) ET models or statistical and empirical methods driven by remote sensing data and various climatological databases. These models have uncertainties due to inevitable input errors, poorly defined parameters, and inadequate model structures. The eddy covariance measurements on water, energy, and carbon fluxes at the AmeriFlux tower sites provide an opportunity to assess the ET modeling uncertainties. In this study, we focused on uncertainty analysis of the Operational Simplified Surface Energy Balance (SSEBop) model for ET estimation at multiple AmeriFlux tower sites with diverse land cover characteristics and climatic conditions. The 8-day composite 1-km MODerate resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) was used as input land surface temperature for the SSEBop algorithms. The other input data were taken from the AmeriFlux database. Results of statistical analysis indicated that the SSEBop model performed well in estimating ET with an R2 of 0.86 between estimated ET and eddy covariance measurements at 42 AmeriFlux tower sites during 2001–2007. It was encouraging to see that the best performance was observed for croplands, where R2 was 0.92 with a root mean square error of 13 mm/month. The uncertainties or random errors from input variables and parameters of the SSEBop model led to monthly ET estimates with relative errors less than 20% across multiple flux tower sites distributed across different biomes. This uncertainty of the SSEBop model lies within the error range of other SEB models, suggesting systematic error or bias of the SSEBop model is within the normal range. This finding implies that the simplified parameterization of the SSEBop model did not significantly affect the accuracy of the ET estimate while increasing the ease of model setup for operational applications. The sensitivity analysis indicated that the SSEBop model is most sensitive to input variables, land surface temperature (LST) and reference ET ( ET o ); and parameters, differential temperature ( dT ), and maximum ET scalar ( K max ), particularly during the non-growing season and in dry areas. In summary, the uncertainty assessment verifies that the SSEBop model is a reliable and robust method for large-area ET estimation. The SSEBop model estimates can be further improved by reducing errors in two input variables ( ET o and LST) and two key parameters ( K max and dT ).

Journal of Hydrology↗

USGS2018

Prediction uncertainty and data worth assessment for groundwater transport times in an agricultural catchment

Uncertainties about the age of base-flow discharge can have serious implications for the management of degraded environmental systems where subsurface pathways, and the ongoing release of pollutants that accumulated in the subsurface during past decades, dominate the water quality signal. Numerical groundwater models may be used to estimate groundwater return times and base-flow ages and thus predict the time required for stakeholders to see the results of improved agricultural management practices. However, the uncertainty inherent in the relationship between (i) the observations of atmospherically-derived tracers that are required to calibrate such models and (ii) the predictions of system age that the observations inform have not been investigated. For example, few if any studies have assessed the uncertainty of numerically-simulated system ages or evaluated the uncertainty reductions that may result from the expense of collecting additional subsurface tracer data. In this study we combine numerical flow and transport modeling of atmospherically-derived tracers with prediction uncertainty methods to accomplish four objectives. First, we show the relative importance of head, discharge, and tracer information for characterizing response times in a uniquely data rich catchment that includes 266 age-tracer measurements (SF 6 , CFCs, and 3 H) in addition to long term monitoring of water levels and stream discharge. Second, we calculate uncertainty intervals for model-simulated base-flow ages using both linear and non-linear methods, and find that the prediction sensitivity vector used by linear first-order second-moment methods results in much larger uncertainties than non-linear Monte Carlo methods operating on the same parameter uncertainty. Third, by combining prediction uncertainty analysis with multiple models of the system, we show that data-worth calculations and monitoring network design are sensitive to variations in the amount of water leaving the system via stream discharge and irrigation withdrawals. Finally, we demonstrate a novel model-averaged computation of potential data worth that can account for these uncertainties in model structure.

Maryland↗

USGS2013

Injection, transport, and deposition of tephra during event 5 at Redoubt Volcano, 23 March, 2009

Among the events of the 2009 eruption at Redoubt Volcano, Alaska, event 5 was the best documented by radar, satellite imagery, and deposit mapping. We use the new Eulerian tephra transport model Ash3d to simulate transport and deposition of event 5 tephra at distances up to 350 km. The eruption, which started at about 1230 UTC on 23 March, 2009, sent a plume from the vent elevation (estimated at 2.3 ± 0.1 km above sea level or a.s.l.) to about 16 ± 2 km above sea level in 5 min. The plume was a few kilometers higher than would be expected for the estimated average mass eruption rate and atmospheric conditions, possibly due to release of most of the eruptive mass in the first half of the 20-minute event. The eruption injected tephra into a wind field of high shear, with weak easterly winds below ~ 3 km elevation, strong southerly winds at 6–10 km and weak westerlies above ~ 16 km. Model simulations in this wind field predicted development of a northward-migrating inverted “v”-shaped cloud with a southwest-trending arm at a few kilometers elevation, which was not visible in IR satellite images due to cloud cover, and a southeast-trending arm at > 10 km elevation that was clearly visible. Simulations also predicted a deposit distribution that strongly depended on plume height: a plume height below 15 km predicted ash deposits that were located west of those mapped, whereas good agreement was reached with a modeled plume height of 15–18 km. Field sampling of the deposit found it to contain abundant tephra aggregates, which accelerated the removal of tephra from the atmosphere. We were able to reasonably approximate the effect of aggregation on the deposit mass distribution by two methods: (1) adjusting the grain-size distribution, taking the erupted mass < = 0.063 mm in diameter and distributing it evenly into bins of coarser size; and (2) moving 80–90% of the mass < = 0.063 mm into a single particle bin ranging in size from 0.25 to 1 mm. These methods produced an area inside the 100 g m − 2 isomass lines that was within a few tens of percent of mapped area; however they under-predicted deposit mass at very proximal (< 50 km) and very distal (> 250 km) locations. Modeled grain-size distributions at sample locations are also generally coarser than observed. The mismatch may result from a combination of limitations in field sampling, approximations inherent in the model, errors in the numerical wind field, and aggregation of particles larger than 0.063 mm.

Alaska↗

USGS2016

Results of the eruptive column model inter-comparison study

This study compares and evaluates one-dimensional (1D) and three-dimensional (3D) numerical models of volcanic eruption columns in a set of different inter-comparison exercises. The exercises were designed as a blind test in which a set of common input parameters was given for two reference eruptions, representing a strong and a weak eruption column under different meteorological conditions. Comparing the results of the different models allows us to evaluate their capabilities and target areas for future improvement. Despite their different formulations, the 1D and 3D models provide reasonably consistent predictions of some of the key global descriptors of the volcanic plumes. Variability in plume height, estimated from the standard deviation of model predictions, is within ~ 20% for the weak plume and ~ 10% for the strong plume. Predictions of neutral buoyancy level are also in reasonably good agreement among the different models, with a standard deviation ranging from 9 to 19% (the latter for the weak plume in a windy atmosphere). Overall, these discrepancies are in the range of observational uncertainty of column height. However, there are important differences amongst models in terms of local properties along the plume axis, particularly for the strong plume. Our analysis suggests that the simplified treatment of entrainment in 1D models is adequate to resolve the general behaviour of the weak plume. However, it is inadequate to capture complex features of the strong plume, such as large vortices, partial column collapse, or gravitational fountaining that strongly enhance entrainment in the lower atmosphere. We conclude that there is a need to more accurately quantify entrainment rates, improve the representation of plume radius, and incorporate the effects of column instability in future versions of 1D volcanic plume models.

Journal of Volcanology and Geothermal Research↗

USGS2017

Monitoring gas and heat emissions at Norris Geyser Basin, Yellowstone National Park, USA based on a combined eddy covariance and Multi-GAS approach

We quantified gas and heat emissions in an acid-sulfate, vapor-dominated area (0.04-km 2 ) of Norris Geyser Basin, located just north of the 0.63 Ma Yellowstone Caldera and near an area of anomalous uplift. From 14 May to 3 October 2016, an eddy covariance system measured half-hourly CO 2 , H 2 O and sensible ( H ) and latent ( LE ) heat fluxes and a Multi-GAS instrument measured (1 Hz frequency) atmospheric H 2 O, CO 2 and H 2 S volumetric mixing ratios. We also measured soil CO 2 fluxes using the accumulation chamber method and temperature profiles on a grid and collected fumarole gas samples for geochemical analysis. Eddy covariance CO 2 fluxes ranged from − 56 to 885 g m − 2 d − 1 . Using wavelet analysis, average daily eddy covariance CO 2 fluxes were locally correlated with average daily environmental parameters on several-day to monthly time scales. Estimates of CO 2 emission rate from the study area ranged from 8.6 t d − 1 based on eddy covariance measurements to 9.8 t d − 1 based on accumulation chamber measurements. Eddy covariance water vapor fluxes ranged from 1178 to 24,600 g m − 2 d − 1 . Nighttime H and LE were considered representative of hydrothermal heat fluxes and ranged from 4 to 183 and 38 to 504 W m − 2 , respectively. The total hydrothermal heat emission rate ( H + LE + radiant) estimated for the study area was 11.6 MW and LE contributed 69% of the output. The mean ± standard deviation of H 2 O, CO 2 and H 2 S mixing ratios measured by the Multi-GAS system were 9.3 ± 3.1 parts per thousand, 467 ± 61 ppmv, and 0.5 ± 0.6 ppmv, respectively, and variations in the gas compositions were strongly correlated with diurnal variations in environmental parameters (wind speed and direction, atmospheric temperature). After removing ambient H 2 O and CO 2 , the observed variations in the Multi-GAS data could be explained by the mixing of relatively H 2 O-CO 2 -H 2 S-rich fumarole gases with CO 2 -rich and H 2 O-H 2 S-poor soil gases. The fumarole H 2 O/CO 2 and CO 2 /H 2 S end member ratios (101.7 and 27.1, respectively, on average) were invariant during the measurement period and fell within the range of values measured in direct fumarole gas samples. The soil gas H 2 O/CO 2 end member ratios (~ 15–30) were variable and low relative to the fumarole end member, likely resulting from water vapor loss during cooling and condensation in the shallow subsurface, whereas the CO 2 /H 2 S end member ratio was high (~ 160), presumably related to transport of CO 2 -dominated soil gas emissions mixed with trace fumarolic emissions to the Multi-GAS station. Nighttime eddy covariance ratios of H 2 O to CO 2 flux were typically between the soil gas and fumarole end member H 2 O/CO 2 ratios defined by Multi-GAS measurements. Overall, the combined eddy covariance and Multi-GAS approach provides a powerful tool for quasi-continuous measurements of gas and heat emissions for improved volcano-hydrothermal monitoring.

Wyoming↗

USGS2021

Long-term year-round observations of magmatic CO2 emissions on Mammoth Mountain, California, USA

Diffuse emission of magmatic CO 2 is one of the main indicators of volcanic unrest at Mammoth Mountain, but the presence of deep seasonal snowpack at the site has hindered year-round CO 2 flux observations. A permanent eddy covariance station was established at the largest area of diffuse CO 2 degassing on Mammoth Mountain (Horseshoe Lake tree kill) that measured CO 2 fluxes ( F c ) and meteorological parameters on a half-hourly basis. From July 22, 2014 to May 24, 2020, F c ranged from −35 to 10,546 g m −2 d −1 . F c decreased on average by 53% over the study period, tracking the long-term decline in CO 2 emissions following the last major increase that occurred at the Horseshoe Lake tree kill area from 2009 to 2011. Statistical and spectral analyses were applied to the F c and ancillary meteorological parameter time series to understand (1) relationships between these parameters, (2) their dominant periodicities, and (3) changes in F c that may be unexplained by meteorological forcing. Variations in detrended F c ( F cdt ) were most strongly correlated with wind direction and atmospheric temperature, followed by atmospheric pressure on diurnal to annual time scales, but wind direction likely exerted the most direct control on F cdt . Comparison of the smoothed (180-d span) F cdt time series to the time series of average-daily snow water equivalent measured ~1 km away suggested that snowpack may have suppressed CO 2 emissions. No evidence of a change in CO 2 emissions related to the last major seismic swarm beneath Mammoth Mountain on February 2–18, 2014 was observed.

California↗

USGS2018

Prospects for reconstructing paleoenvironmental conditions from organic compounds in polar snow and ice

Polar ice cores provide information about past climate and environmental changes over periods ranging from a few years up to 800,000 years. The majority of chemical studies have focused on determining inorganic components, such as major ions and trace elements as well as on their isotopic fingerprint. In this paper, we review the different classes of organic compounds that might yield environmental information, discussing existing research and what is needed to improve knowledge. We also discuss the problems of sampling, analysis and interpretation of organic molecules in ice. This review highlights the great potential for organic compounds to be used as proxies for anthropogenic activities, past fire events from different types of biomass, terrestrial biogenic emissions and marine biological activity, along with the possibility of inferring past temperature fluctuations and even large-scale climate variability. In parallel, comprehensive research needs to be done to assess the atmospheric stability of these compounds, their ability to be transported long distances in the atmosphere, and their stability in the archive in order to better interpret their fluxes in ice cores. In addition, specific decontamination procedures, analytical methods with low detection limits (ng/L or lower), fast analysis time and low sample requests need to be developed in order to ensure a good time resolution in the archive.

Quaternary Science Reviews↗

USGS2004

Assessment of estuarine water-quality indicators using MODIS medium-resolution bands: initial results from Tampa Bay, FL

Using Tampa Bay, FL as an example, we explored the potential for using MODIS medium-resolution bands (250- and 500-m data at 469-, 555-, and 645-nm) for estuarine monitoring. Field surveys during 21–22 October 2003 showed that Tampa Bay has Case-II waters, in that for the salinity range of 24–32 psu, (a) chlorophyll concentration (11 to 23 mg m −3 ), (b) colored dissolved organic matter (CDOM) absorption coefficient at 400 nm (0.9 to 2.5 m −1 ), and (c) total suspended sediment concentration (TSS: 2 to 11 mg L −1 ) often do not co-vary. CDOM is the only constituent that showed a linear, inverse relationship with surface salinity, although the slope of the relationship changed with location within the bay. The MODIS medium-resolution bands, although designed for land use, are 4–5 times more sensitive than Landsat-7/ETM+ data and are comparable to or higher than those of CZCS. Several approaches were used to derive synoptic maps of water constituents from concurrent MODIS medium-resolution data. We found that application of various atmospheric-correction algorithms yielded no significant differences, due primarily to uncertainties in the sensor radiometric calibration and other sensor artifacts. However, where each scene could be groundtruthed, simple regressions between in situ observations of constituents and at-sensor radiances provided reasonable synoptic maps. We address the need for improvements of sensor calibration/characterization, atmospheric correction, and bio-optical algorithms to make operational and quantitative use of these medium-resolution bands.

Florida↗

USGS2010

Web-enabled Landsat Data (WELD): Landsat ETM+ composited mosaics of the conterminous United States

Since January 2008, the U.S. Department of Interior / U.S. Geological Survey have been providing free terrain-corrected (Level 1T) Landsat Enhanced Thematic Mapper Plus (ETM+) data via the Internet, currently for acquisitions with less than 40% cloud cover. With this rich dataset, temporally composited, mosaics of the conterminous United States (CONUS) were generated on a monthly, seasonal, and annual basis using 6521 ETM+ acquisitions from December 2007 to November 2008. The composited mosaics are designed to provide consistent Landsat data that can be used to derive land cover and geo-physical and bio-physical products for detailed regional assessments of land-cover dynamics and to study Earth system functioning. The data layers in the composited mosaics are defined at 30 m and include top of atmosphere (TOA) reflectance, TOA brightness temperature, TOA normalized difference vegetation index (NDVI), the date each composited pixel was acquired on, per-band radiometric saturation status, cloud mask values, and the number of acquisitions considered in the compositing period. Reduced spatial resolution browse imagery, and top of atmosphere 30 m reflectance time series extracted from the monthly composites, capture the expected land surface phenological change, and illustrate the potential of the composited mosaic data for terrestrial monitoring at high spatial resolution. The composited mosaics are available in 501 tiles of 5000 × 5000 30 m pixels in the Albers equal area projection and are downloadable at http://landsat.usgs.gov/WELD.php . The research described in this paper demonstrates the potential of Landsat data processing to provide a consistent, long-term, large-area, data record.

Remote Sensing of Environment↗

USGS2010

Monitoring on-orbit calibration stability of the Terra MODIS and Landsat 7 ETM+ sensors using pseudo-invariant test sites

The ability to detect and quantify changes in the Earth's environment depends on sensors that can provide calibrated, consistent measurements of the Earth's surface features through time. A critical step in this process is to put image data from different sensors onto a common radiometric scale. This work focuses on monitoring the long-term on-orbit calibration stability of the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) sensors using the Committee on Earth Observation Satellites (CEOS) reference standard pseudo-invariant test sites (Libya 4, Mauritania 1/2, Algeria 3, Libya 1, and Algeria 5). These sites have been frequently used as radiometric targets because of their relatively stable surface conditions temporally. This study was performed using all cloud-free calibrated images from the Terra MODIS and the L7 ETM+ sensors, acquired from launch to December 2008. Homogeneous regions of interest (ROI) were selected in the calibrated images and the mean target statistics were derived from sensor measurements in terms of top-of-atmosphere (TOA) reflectance. For each band pair, a set of fitted coefficients (slope and offset) is provided to monitor the long-term stability over very stable pseudo-invariant test sites. The average percent differences in intercept from the long-term trends obtained from the ETM + TOA reflectance estimates relative to the MODIS for all the CEOS reference standard test sites range from 2.5% to 15%. This gives an estimate of the collective differences due to the Relative Spectral Response (RSR) characteristics of each sensor, bi-directional reflectance distribution function (BRDF), spectral signature of the ground target, and atmospheric composition. The lifetime TOA reflectance trends from both sensors over 10 years are extremely stable, changing by no more than 0.4% per year in its TOA reflectance over the CEOS reference standard test sites.

Remote Sensing of Environment↗

USGS2010

Spectral assessment of new ASTER SWIR surface reflectance data products for spectroscopic mapping of rocks and minerals

ASTER reflectance spectra from Cuprite, Nevada, and Mountain Pass, California, were compared to spectra of field samples and to ASTER-resampled AVIRIS reflectance data to determine spectral accuracy and spectroscopic mapping potential of two new ASTER SWIR reflectance datasets: RefL1b and AST_07XT. RefL1b is a new reflectance dataset produced for this study using ASTER Level 1B data, crosstalk correction, radiance correction factors, and concurrently acquired level 2 MODIS water vapor data. The AST_07XT data product, available from EDC and ERSDAC, incorporates crosstalk correction and non-concurrently acquired MODIS water vapor data for atmospheric correction. Spectral accuracy was determined using difference values which were compiled from ASTER band 5/6 and 9/8 ratios of AST_07XT or RefL1b data subtracted from similar ratios calculated for field sample and AVIRIS reflectance data. In addition, Spectral Analyst, a statistical program that utilizes a Spectral Feature Fitting algorithm, was used to quantitatively assess spectral accuracy of AST_07XT and RefL1b data.Spectral Analyst matched more minerals correctly and had higher scores for the RefL1b data than for AST_07XT data. The radiance correction factors used in the RefL1b data corrected a low band 5 reflectance anomaly observed in the AST_07XT and AST_07 data but also produced anomalously high band 5 reflectance in RefL1b spectra with strong band 5 absorption for minerals, such as alunite. Thus, the band 5 anomaly seen in the RefL1b data cannot be corrected using additional gain adjustments. In addition, the use of concurrent MODIS water vapor data in the atmospheric correction of the RefL1b data produced datasets that had lower band 9 reflectance anomalies than the AST_07XT data. Although assessment of spectral data suggests that RefL1b data are more consistent and spectrally more correct than AST_07XT data, the Spectral Analyst results indicate that spectral discrimination between some minerals, such as alunite and kaolinite, are still not possible unless additional spectral calibration using site specific spectral data are performed. ?? 2010.

Remote Sensing of Environment↗

USGS2016

Assessing the role of climate and resource management on groundwater dependent ecosystem changes in arid environments with the Landsat archive

Groundwater dependent ecosystems (GDEs) rely on near-surface groundwater. These systems are receiving more attention with rising air temperature, prolonged drought, and where groundwater pumping captures natural groundwater discharge for anthropogenic use. Phreatophyte shrublands, meadows, and riparian areas are GDEs that provide critical habitat for many sensitive species, especially in arid and semi-arid environments. While GDEs are vital for ecosystem services and function, their long-term (i.e. ~ 30 years) spatial and temporal variability is poorly understood with respect to local and regional scale climate, groundwater, and rangeland management. In this work, we compute time series of NDVI derived from sensors of the Landsat TM, ETM +, and OLI lineage for assessing GDEs in a variety of land and water management contexts. Changes in vegetation vigor based on climate, groundwater availability, and land management in arid landscapes are detectable with Landsat. However, the effective quantification of these ecosystem changes can be undermined if changes in spectral bandwidths between different Landsat sensors introduce biases in derived vegetation indices, and if climate, and land and water management histories are not well understood. The objective of this work is to 1) use the Landsat 8 under-fly dataset to quantify differences in spectral reflectance and NDVI between Landsat 7 ETM + and Landsat 8 OLI for a range of vegetation communities in arid and semiarid regions of the southwestern United States, and 2) demonstrate the value of 30-year historical vegetation index and climate datasets for assessing GDEs. Specific study areas were chosen to represent a range of GDEs and environmental conditions important for three scenarios: baseline monitoring of vegetation and climate, riparian restoration, and groundwater level changes. Google's Earth Engine cloud computing and environmental monitoring platform is used to rapidly access and analyze the Landsat archive along with downscaled North American Land Data Assimilation System gridded meteorological data, which are used for both atmospheric correction and correlation analysis. Results from the cross-sensor comparison indicate a benefit from the application of a consistent atmospheric correction method, and that NDVI derived from Landsat 7 and 8 are very similar within the study area. Results from continuous Landsat time series analysis clearly illustrate that there are strong correlations between changes in vegetation vigor, precipitation, evaporative demand, depth to groundwater, and riparian restoration. Trends in summer NDVI associated with riparian restoration and groundwater level changes were found to be statistically significant, and interannual summer NDVI was found to be moderately correlated to interannual water-year precipitation for baseline study sites. Results clearly highlight the complementary relationship between water-year PPT, NDVI, and evaporative demand, and are consistent with regional vegetation index and complementary relationship studies. This work is supporting land and water managers for evaluation of GDEs with respect to climate, groundwater, and resource management.

Remote Sensing of Environment↗