Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “TOPOGRAPHY”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,549 records · Page 86
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

GPS-Based Gamma Survey for Characterizing and Decommissioning NORM Sites - 20389

Gamma survey techniques are an especially powerful decommissioning tool at naturally occurring radioactive material (NORM) sites due to both the low cost to obtain data over a large spatial scale and the abundance of gamma emitters in the uranium and thorium decay series. Gamma surveys are executed by coupling a detector - most often a sodium iodide crystal - to a global positioning system (GPS), then reporting a location and gross gamma reading coincidentally to a data logger. Systems may be carried by workers or mounted to a car, all-terrain vehicle, or unmanned aerial system (UAS). The resulting data set provides a high-resolution but low precision map of the gamma radiation field over the area surveyed. Frequently this map is also correlated to soil concentrations of NORM radionuclides (most often, Ra-226) and/or exposure rate. Gamma survey parameters such as movement speed, transect spacing, and data logging frequency define the spatial resolution of the resulting surface, and can be optimized depending on the desired survey sensitivity. This paper examines gamma survey as a tool for decommissioning NORM sites and provides an overview of current gamma survey technology designed to improve the efficiency and effectiveness of the decommissioning process. Topics to be discussed in the paper include: - An overview of gamma survey systems, and the utility of different delivery vehicles depending on desired cost, desired spatial resolution, and site topography. - The influence of physical detector characteristics on detection sensitivity and survey planning. - The tradeoff between high-resolution and large spatial extent, but inherently uncertain data, and low-resolution, low spatial extent, but highly certain data, as well as the specific utility of each of these types of data during NORM facility decommissioning. - Confounding variables that may limit the utility of gamma survey at some sites (e.g., radon gas and spatial heterogeneity / hot spots), and methods to plan for and control these conditions. Results show that the confounding variables, such as radon and data output can greatly influence the overall data quality associated with the decommissioning process. In addition, the use of real-time and aerial survey platforms provides a method for ensuring proper spatial extent of the data. When applied thoughtfully, gamma survey is a powerful tool for detecting NORM radionuclides in the environment and a cost-effective technique for identifying areas requiring remediation. However, entities performing or using gamma survey as a decommissioning tool must be aware of both its advantages and its limitations before basing remediation or regulatory action on gamma survey results. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Bayesian Approach to Estimation of Water Table Elevations Using Historical Rasters as Prior Information 2019 - 20430

In cases of complex but only partially known geology and a lack of spatial control in observation well locations, water table elevation estimation is very challenging. In some cases, auxiliary information, such as observations of the movement of tracers, operation of injection and extraction wells, and calibration of groundwater models against the historical elevation data, can be combined with expert judgement to estimate flow directions in areas of sparse data and to aid in the production of more reliable contour maps (and associated rasters) than could be produced by relying on sparse well elevation data alone. Given a historical sequence of these raster maps, the question arises how to automate, to the extent possible, the process of producing new raster maps to reflect data from previous times, the current data and the operation of expert judgement. One solution is to adopt a Bayesian point of view and to regard the historical well elevation data, auxiliary information and historical raster maps as prior information. The well elevations for water table wells, as well as those for injection/extraction wells and the data associated with other relevant variables, can be viewed as predictors for the raster surface. From this prior information, we can, conditional on the values of these predictors for a new time period, compute an expected value map and a standard deviation map for the new raster. These then can be taken to specify a prior predictive distribution for the pixels in the new raster map. Then we condition the pixels, corresponding to water level observation wells within the raster, on the observed values in those wells (which in general will differ from the regression estimate) for the new time period. Given the smoothness of the water table surface, we then smooth the surface of deviations from the mean surface, based on the variograms of the historical rasters, and add this smoothed surface to the regression mean surface. The error structure of the produced raster map is defined by the regression error structure and the error due to smoothing based on the estimated variograms. This methodology has been developed and is being further refined for groundwater monitoring and remediation at LANL. It is a very flexible method that can also be applied with a variety of other predictors applied to model the water level wells in the area of interest over the historical record. The smoothness of the spatial process and its possible evolution over time can then be estimated from the residuals from this regression. This can be augmented by expert hydrogeological opinion based on site topography and hydrogeology. (authors)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Evaluation of CMIP5 continental precipitation simulations relative to satellite-based gauge-adjusted observations

Numerous studies have emphasized that climate simulations are subject to various biases and uncertainties. The objective of this study is to cross-validate 34 Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations of precipitation against the Global Precipitation Climatology Project (GPCP) data, quantifying model pattern discrepancies and biases for both entire data distributions and their upper tails. The results of the Volumetric Hit Index (VHI) analysis of the total monthly precipitation amounts show that most CMIP5 simulations are in good agreement with GPCP patterns in many areas, but that their replication of observed precipitation over arid regions and certain sub-continental regions (e.g., northern Eurasia, eastern Russia, central Australia) is problematical. Overall, the VHI of the multi-model ensemble mean and median also are superior to that of the individual CMIP5 models. However, at high quantiles of reference data (e.g., the 75th and 90th percentiles), all climate models display low skill in simulating precipitation, except over North America, the Amazon, and central Africa. Analyses of total bias (B) in CMIP5 simulations reveal that most models overestimate precipitation over regions of complex topography (e.g. western North and South America and southern Africa and Asia), while underestimating it over arid regions. Also, while most climate model simulations show low biases over Europe, inter-model variations in bias over Australia and Amazonia are considerable. The Quantile Bias (QB) analyses indicate that CMIP5 simulations are even more biased at high quantiles of precipitation. Lastly, we found that a simple mean-field bias removal improves the overall B and VHI values, but does not make a significant improvement in these model performance metrics at high quantiles of precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Links Between Flood Frequency and Annual Water Balance Behaviors: A Basis for Similarity and Regionalization

This paper presents the results of a data based comparative study of several hundred catchments across continental United States belonging to the MOPEX dataset, which systematically explored the connection between the flood frequency curve and measures of mean annual water balance. Two different measures of mean annual water balance are used: (i) a climatic aridity index, AI, which is a measure of the competition between water and energy availability at the annual scale; and, (ii) baseflow index, BFI, the ratio of slow runoff to total runoff also at the annual time scale, reflecting the role of geology, soils, topography and vegetation. The data analyses showed that the aridity index, AI, has a first order control on both the mean and Cv of annual maximum floods. While mean annual flood decreases with increasing aridity, Cv increases with increasing aridity. BFI appeared to be a second order control on the magnitude and shape of the flood frequency curve. Higher BFI, meaning more subsurface flow and less surface flow leads to a decrease of mean annual flood whereas lower BFI leads to accumulation of soil moisture and increased flood magnitudes that arise from many events acting together. The results presented in this paper provide innovative means to delineate homogeneous regions within which the flood frequency curves can be assumed to be functionally similar. At another level, understanding the connection between annual water balance and flood frequency will be another building block towards developing comprehensive understanding of catchment runoff behavior in a holistic way.

annual water balance↗
DOE OSTI2015

Forecasting the response of Earth's surface to future climatic and land use changes: A review of methods and research needs

In the future, Earth will be warmer, precipitation events will be more extreme, global mean sea level will rise, and many arid and semiarid regions will be drier. Human modifications of landscapes will also occur at an accelerated rate as developed areas increase in size and population density. We now have gridded global forecasts, being continually improved, of the climatic and land use changes (C&LUC) that are likely to occur in the coming decades. However, besides a few exceptions, consensus forecasts do not exist for how these C&LUC will likely impact Earth-surface processes and hazards. In some cases, we have the tools to forecast the geomorphic responses to likely future C&LUC. Fully exploiting these models and utilizing these tools will require close collaboration among Earth-surface scientists and Earth-system modelers. This paper assesses the state-of-the-art tools and data that are being used or could be used to forecast changes in the state of Earth's surface as a result of likely future C&LUC. We also propose strategies for filling key knowledge gaps, emphasizing where additional basic research and/or collaboration across disciplines are necessary. The main body of the paper addresses cross-cutting issues, including the importance of nonlinear/threshold-dominated interactions among topography, vegetation, and sediment transport, as well as the importance of alternate stable states and extreme, rare events for understanding and forecasting Earth-surface response to C&LUC. Five supplements delve into different scales or process zones (global-scale assessments and fluvial, aeolian, glacial/periglacial, and coastal process zones) in detail.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Stochastic Parameterization for Light Absorption by Internally Mixed BC/dust in Snow Grains for Application to Climate Models

A stochastic approach to model the positions of BC/dust internally mixed with two snow-grain types has been developed, including hexagonal plate/column (convex) and Koch snowflake (concave). Subsequently, light absorption and scattering analysis can be followed by means of an improved geometric-optics approach coupled with Monte Carlo photon tracing to determine their single-scattering properties. For a given shape (plate, Koch snowflake, spheroid, or sphere), internal mixing absorbs more light than external mixing. The snow-grain shape effect on absorption is relatively small, but its effect on the asymmetry factor is substantial. Due to a greater probability of intercepting photons, multiple inclusions of BC/dust exhibit a larger absorption than an equal-volume single inclusion. The spectral absorption (0.2 – 5 um) for snow grains internally mixed with BC/dust is confined to wavelengths shorter than about 1.4 um, beyond which ice absorption predominates. Based on the single-scattering properties determined from stochastic and light absorption parameterizations and using the adding/doubling method for spectral radiative transfer, we find that internal mixing reduces snow albedo more than external mixing and that the snow-grain shape plays a critical role in snow albedo calculations through the asymmetry factor. Also, snow albedo reduces more in the case of multiple inclusion of BC/dust compared to that of an equal-volume single sphere. For application to land/snow models, we propose a two-layer spectral snow parameterization containing contaminated fresh snow on top of old snow for investigating and understanding the climatic impact of multiple BC/dust internal mixing associated with snow grain metamorphism, particularly over mountains/snow topography.

climate models↗
DOE OSTI2015

Complex terrain alters temperature and moisture limitations of forest soil respiration across a semiarid to subalpine gradient

Forest soil respiration is a major carbon (C) flux that is characterized by significant variability in space and time. In this paper, we quantified growing season soil respiration during both a drought year and a nondrought year across a complex landscape to identify how landscape and climate interact to control soil respiration. We asked the following questions: (1) How does soil respiration vary across the catchments due to terrain-induced variability in moisture availability and temperature? (2) Does the relative importance of moisture versus temperature limitation of respiration vary across space and time? And (3) what terrain elements are important for dictating the pattern of soil respiration and its controls? Moisture superseded temperature in explaining watershed respiration patterns, with wetter yet cooler areas higher up and on north facing slopes yielding greater soil respiration than lower and south facing areas. Wetter subalpine forests had reduced moisture limitation in favor of greater seasonal temperature limitation, and the reverse was true for low-elevation semiarid forests. Coincident climate poorly predicted soil respiration in the montane transition zone; however, antecedent precipitation from the prior 10 days provided additional explanatory power. A seasonal trend in respiration remained after accounting for microclimate effects, suggesting that local climate alone may not adequately predict seasonal variability in soil respiration in montane forests. Finally, soil respiration climate controls were more strongly related to topography during the drought year highlighting the importance of landscape complexity in ecosystem response to drought.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Upper mantle structure of central and West Antarctica from array analysis of Rayleigh wave phase velocities

Abstract The seismic velocity structure of Antarctica is important, both as a constraint on the tectonic history of the continent and for understanding solid Earth interactions with the ice sheet. We use Rayleigh wave array analysis methods applied to teleseismic data from recent temporary broadband seismograph deployments to image the upper mantle structure of central and West Antarctica. Phase velocity maps are determined using a two–plane wave tomography method and are inverted for shear velocity using a Monte Carlo approach to estimate three‐dimensional velocity structure. Results illuminate the structural dichotomy between the East Antarctic Craton and West Antarctica, with West Antarctica showing thinner crust and slower upper mantle velocity. West Antarctica is characterized by a 70–100 km thick lithosphere, underlain by a low‐velocity zone to depths of at least 200 km. The slowest anomalies are beneath Ross Island and the Marie Byrd Land dome and are interpreted as upper mantle thermal anomalies possibly due to mantle plumes. The central Transantarctic Mountains are marked by an uppermost mantle slow‐velocity anomaly, suggesting that the topography is thermally supported. The presence of thin, higher‐velocity lithosphere to depths of about 70 km beneath the West Antarctic Rift System limits estimates of the regionally averaged heat flow to less than 90 mW/m 2 . The Ellsworth‐Whitmore block is underlain by mantle with velocities that are intermediate between those of the West Antarctic Rift System and the East Antarctic Craton. We interpret this province as Precambrian continental lithosphere that has been altered by Phanerozoic tectonic and magmatic activity.

Heeszel, David S.↗
DOE OSTI2016

Future changes in regional precipitation simulated by a half-degree coupled climate model: Sensitivity to horizontal resolution

The global fully coupled half-degree Community Climate System Model Version 4 (CCSM4) was integrated for a suite of climate change ensemble simulations including five historical runs, five Representative Concentration Pathway 8.5 [RCP8.5) runs, and a long Pre-Industrial control run. This study focuses on precipitation at regional scales and its sensitivity to horizontal resolution. The half-degree historical CCSM4 simulations are compared to observations, where relevant, and to the standard 1° CCSM4. Both the halfdegree and 1° resolutions are coupled to a nominal 1° ocean. North American and South Asian/Indian monsoon regimes are highlighted because these regimes demonstrate improvements due to higher resolution, primarily because of better-resolved topography. Agriculturally sensitive areas are analyzed and include Southwest, Central, and Southeast U.S., Southern Europe, and Australia. Both mean and extreme precipitation is discussed for convective and large-scale precipitation processes. Convective precipitation tends to decrease with increasing resolution and large-scale precipitation tends to increase. Improvements for the half-degree agricultural regions can be found for mean and extreme precipitation in the Southeast U.S., Southern Europe, and Australian regions. Climate change responses differ between the model resolutions for the U.S. Southwest/Central regions and are seasonally dependent in the Southeast and Australian regions. Both resolutions project a clear drying signal across Southern Europe due to increased greenhouse warming. As a result, differences between resolutions tied to the representation of convective and large-scale precipitation play an important role in the character of the climate change and depend on regional influences.

58 GEOSCIENCES↗
DOE OSTI2016

Matching ecohydrological processes and scales of banded vegetation patterns in semiarid catchments

While the claim that water-carbon interactions result in spatially coherent vegetation patterning is rarely disputed in many arid and semiarid regions, the significance of the detailed water pathways and other high frequency variability remain an open question. How the short temporal scale meteorological fluctuations form the long-term spatial variability of available soil water in complex terrains due to the various hydrological, land surface, and vegetation dynamic feedbacks frames the scope of the work here. Knowledge of the detailed mechanistic feedbacks among soil, plants, and the atmosphere will lead to advances in our understanding of plant water availability in arid and semiarid ecosystems and will provide insights for future model development concerning vegetation pattern formation. In this paper, quantitative estimates of water fluxes and vegetation productivity are provided for a semiarid ecosystem with established vegetation bands on hillslopes using numerical simulations. A state-of-the-science process based ecohydrological model is used, which resolves hydrological and plant physiological processes at the relevant space and time scales, for relatively small periods (e.g., decades) of mature ecosystems (i.e., spatially static vegetation distribution). To unfold the mechanisms that shape the spatial distribution of soil moisture, plant productivity and the relevant surface/subsurface and atmospheric water fluxes, idealized hillslope numerical experiments are constructed, where the effects of soil type, slope steepness, and overland flow accumulation area are quantified. Those mechanisms are also simulated in the presence of complex topography features on landscapes. Finally, the main results are (a) short temporal scale meteorological variability and accurate representation of the scales at which each ecohydrological process operates are crucial for the estimation of the spatial variability of soil water availability to the plant root zone; (b) water fluxes such as evapotranspiration, infiltration, runoff-run-on, and subsurface soil water movement have a dynamic short temporal scale behavior that determines the long-term spatial organization of plant soil water availability in ecosystems with established vegetation patterns; and (c) hypotheses concerning the hydrological responses that can lead to vegetation pattern formation have to accommodate realistic and physically based representations of the fast dynamics of key ecohydrological fluxes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Accurate and efficient prediction of fine-resolution hydrologic and carbon dynamic simulations from coarse-resolution models

The topography, and the biotic and abiotic parameters are typically upscaled to make watershed-scale hydrologic-biogeochemical models computationally tractable. However, upscaling procedure can produce biases when nonlinear interactions between different processes are not fully captured at coarse resolutions. Here, we applied the Proper Orthogonal Decomposition Mapping Method (PODMM) to downscale the field solutions from a coarse (7 km) resolution grid to a fine (220 m) resolution grid. PODMM trains a reduced-order model (ROM) with coarse-resolution and fine-resolution solutions, here obtained using PAWS+CLM, a quasi-3-D watershed processes model that has been validated for many temperate watersheds. Subsequent fine-resolution solutions were approximated based only on coarse-resolution solutions and the ROM. The approximation errors were efficiently quantified using an error estimator. By jointly estimating correlated variables and temporally varying the ROM parameters, we further reduced the approximation errors by up to 20%. We also improved the method's robustness by constructing multiple ROMs using different set of variables, and selecting the best approximation based on the error estimator. The ROMs produced accurate downscaling of soil moisture, latent heat flux, and net primary production with O(1000) reduction in computational cost. The subgrid distributions were also nearly indistinguishable from the ones obtained using the fine-resolution model. Compared to coarse-resolution solutions, biases in upscaled ROM solutions were reduced by up to 80%. This method has the potential to help address the long-standing spatial scaling problem in hydrology and enable long-time integration, parameter estimation, and stochastic uncertainty analysis while accurately representing the heterogeneities.

58 GEOSCIENCES↗
DOE OSTI2016

Radar imaging of shallow water bathymetry: A case study in the Yangtze Estuary

This study focuses on 2-dimensional (2-D) radar imaging of bathymetric features in the shallow water of the Yangtze Estuary using synthetic aperture radar (SAR) observations and model simulations. A validated 2-D shallow water numerical model simulates the barotropic current velocity, and the simulated current fields together with the relevant parameters of radar observations are then invoked in the radar imaging model as the input. The results show that variations in the simulated image intensity are mainly dominated by distinct radar backscatter anomalies caused by wave-current interactions in the vicinity of rapidly changing underwater topographies. The comparison between the simulated and observed SAR images shows a reasonable agreement, demonstrating that our approach may be implemented to monitor changes in the shallow water bathymetry of the Yangtze Estuary in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Isopycnal eddy mixing across the Kuroshio Extension: Stable versus unstable states in an eddying model

The Kuroshio Extension (KE) jet transitions between stable and unstable states on interannual time scales. Cross-jet eddy mixing in the two states is contrasted in the KE region (28°-240°N; 125°-165°E), using a global eddying 0.1° configuration of the Parallel Ocean Program with online numerical particles. The 4 year period chosen (June 1994 to May 1998) covers a full cycle of the stable state, unstable state and the transition period. Large values of cross-jet eddy diffusivities within the KE jet are concentrated in the upper 1000 m. In the upper ocean, elevated cross-jet mixing within the KE jet is mainly concentrated in the downstream part of the KE jet, where the jet is weak but eddy activity is strong. The simulated time-mean KE jet is more intense and extends further east in the stable state than in the unstable state. Consequently, strong cross-jet mixing within the KE jet is located west of 150°E during June 1996 to May 1997 (a typical unstable state), but east of 150°E during June 1995 to May 1996 (a typical stable state). However, average mixing within the KE jet is indistinguishable in the typical stable and unstable states. In the deep ocean, mixing is strongly influenced by topography, and thus their horizontal structures have less inter-annual variability than in the upper ocean. One caveat is that results here cover one representative cycle of the two states. To obtain the climate mean mixing structures for the stable or unstable state, one would need numerical output covering a period much longer than 4 years.

58 GEOSCIENCES↗
DOE OSTI2016

Analysis of WRF extreme daily precipitation over Alaska using self‐organizing maps

Abstract We analyze daily precipitation extremes from simulations of a polar‐optimized version of the Weather Research and Forecasting (WRF) model. Simulations cover 19 years and use the Regional Arctic System Model (RASM) domain. We focus on Alaska because of its proximity to the Pacific and Arctic oceans; both provide large moisture fetch inland. Alaska's topography also has important impacts on orographically forced precipitation. We use self‐organizing maps (SOMs) to understand circulation characteristics conducive for extreme precipitation events. The SOM algorithm employs an artificial neural network that uses an unsupervised training process, which results in finding general patterns of circulation behavior. The SOM is trained with mean sea level pressure (MSLP) anomalies. Widespread extreme events, defined as at least 25 grid points experiencing 99th percentile precipitation, are examined using SOMs. Widespread extreme days are mapped onto the SOM of MSLP anomalies, indicating circulation patterns. SOMs aid in determining high‐frequency nodes, and hence, circulations are conducive to extremes. Multiple circulation patterns are responsible for extreme days, which are differentiated by where extreme events occur in Alaska. Additionally, several meteorological fields are composited for nodes accessed by extreme and nonextreme events to determine specific conditions necessary for a widespread extreme event. Individual and adjacent node composites produce more physically reasonable circulations as opposed to composites of all extremes, which include multiple synoptic regimes. Temporal evolution of extreme events is also traced through SOM space. Thus, this analysis lays the groundwork for diagnosing differences in atmospheric circulations and their associated widespread, extreme precipitation events.

Glisan, Justin M.↗
DOE OSTI2017

Observational needs for estimating Alaskan soil carbon stocks under current and future climate

Abstract Representing land surface spatial heterogeneity when designing observation networks is a critical scientific challenge. Here we present a geospatial approach that utilizes the multivariate spatial heterogeneity of soil‐forming factors—namely, climate, topography, land cover types, and surficial geology—to identify observation sites to improve soil organic carbon (SOC) stock estimates across the State of Alaska, USA. Standard deviations in existing SOC samples indicated that 657, 870, and 906 randomly distributed pedons would be required to quantify the average SOC stocks for 0–1 m, 0–2 m, and whole‐profile depths, respectively, at a confidence interval of 5 kg C m −2 . Using the spatial correlation range of existing SOC samples, we identified that 309, 446, and 484 new observation sites are needed to estimate current SOC stocks to 1 m, 2 m, and whole‐profile depths, respectively. We also investigated whether the identified sites might change under future climate by using eight decadal (2020–2099) projections of precipitation, temperature, and length of growing season for three representative concentration pathway (RCP 4.5, 6.0, and 8.5) scenarios of the Intergovernmental Panel on Climate Change. These analyses determined that 12 to 41 additional sites (906 + 12 to 41; depending upon the emission scenarios) would be needed to capture the impact of future climate on Alaskan whole‐profile SOC stocks by 2100. The identified observation sites represent spatially distributed locations across Alaska that captures the multivariate heterogeneity of soil‐forming factors under current and future climatic conditions. This information is needed for designing monitoring networks and benchmarking of Earth system model results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

A decision tree algorithm for investigation of model biases related to dynamical cores and physical parameterizations: CESM/CAM EVALUATION BY DECISION TREES

An object-based evaluation method using a pattern recognition algorithm (i.e., classification trees) is applied to the simulated orographic precipitation for idealized experimental setups using the National Center of Atmospheric Research (NCAR) Community Atmosphere Model (CAM) with the finite volume (FV) and the Eulerian spectral transform dynamical cores with varying resolutions. Daily simulations were analyzed and three different types of precipitation features were identified by the classification tree algorithm. The statistical characteristics of these features (i.e., maximum value, mean value, and variance) were calculated to quantify the difference between the dynamical cores and changing resolutions. Even with the simple and smooth topography in the idealized setups, complexity in the precipitation fields simulated by the models develops quickly. The classification tree algorithm using objective thresholding successfully detected different types of precipitation features even as the complexity of the precipitation field increased. The results show that the complexity and the bias introduced in small-scale phenomena due to the spectral transform method of CAM Eulerian spectral dynamical core is prominent, and is an important reason for its dissimilarity from the FV dynamical core. The resolvable scales, both in horizontal and vertical dimensions, have significant effect on the simulation of precipitation. The results of this study also suggest that an efficient and informative study about the biases produced by GCMs should involve daily (or even hourly) output (rather than monthly mean) analysis over local scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Relative surface wave amplitude and phase anomalies from the Democratic People's Republic of Korea announced nuclear tests

Here, we performed relative locations of six event pairs based on surface wave (SW) and body wave (BW) differential traveltimes of the 9 September 2016, 6 January 2016, 12 February 2013, and 25 May 2009 announced North Korea nuclear explosions. The SW relative locations for the 25 May 2009 and 12 February 2013 events were inconsistent with the BWs when paired with other events, and only the 6 January 2016/9 September 2016 pair was consistent. Apparent SW phase shift is investigated with respect to the BW relative locations. The pairs formed with the 25 May 2009 and 12 February 2013 events, beneath the southeast slope of Mount Mant'ap, have the largest phase shifts and amplitude ratio deviations, whereas the least deviation was from the 6 January 2016 and 9 September 2016 event pair beneath the mountain peak. Regional moment tensors (MTs) predict the amplitude ratios but do not resolve the relative phase. We find that MTs with 10% difference in isotropic and rotated +CLVD can fit both relative phase and amplitude ratios. SW relative locations of highly isotropic and correlated explosion clusters can be affected by topography and small differences in MT.

58 GEOSCIENCES↗
DOE OSTI2017

Potential for Small Unmanned Aircraft Systems Applications for Identifying Groundwater-Surface Water Exchange in a Meandering River Reach: sUAS in Groundwater-Surface Water Study

The exchange of groundwater and surface water (GW-SW), including dissolved constituents and energy, represents a critical yet challenging characterization problem for hydrogeologists and stream ecologists. Here we describe the use of a suite of high spatial resolution remote sensing techniques, collected using a small unmanned aircraft system (sUAS), to provide novel and complementary data to analyze GW-SW exchange. sUAS provided centimeter-scale resolution topography and water surface elevations, which are often drivers of exchange along the river corridor. Additionally, sUAS-based vegetation imagery, vegetation-top elevation, and normalized difference vegetation index mapping indicated GW-SW exchange patterns that are difficult to characterize from the land surface and may not be resolved from coarser satellite-based imagery. We combined these data with estimates of sediment hydraulic conductivity to provide a direct estimate of GW “shortcutting” through meander necks, which was corroborated by temperature data at the riverbed interface.

54 ENVIRONMENTAL SCIENCES↗