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SToRM: A numerical model for environmental surface flows

SToRM (System for Transport and River Modeling) is a numerical model developed to simulate free surface flows in complex environmental domains. It is based on the depth-averaged St. Venant equations, which are discretized using unstructured upwind finite volume methods, and contains both steady and unsteady solution techniques. This article provides a brief description of the numerical approach selected to discretize the governing equations in space and time, including important aspects of solving natural environmental flows, such as the wetting and drying algorithm. The presentation is illustrated with several application examples, covering both laboratory and natural river flow cases, which show the model’s ability to solve complex flow phenomena.

Conference Paper↗

Integrated modeling approach for fate and transport of submerged oil and oil-particle aggregates in a freshwater riverine environment

The Enbridge Line 6B pipeline release of diluted bitumen into the Kalamazoo River downstream of Marshall, Michigan, U.S.A., in July 2010 was one of the largest oil spills into freshwater in North American history. A portion of the oil interacted with river sediment and submerged requiring the development and implementation of new approaches for detection and recovery of oil mixed with river sediment. Hydrodynamic and sediment transport modeling became an integral part of containment and recovery operations for decision support about the potential fate and migration of submerged oil and oiled sediment. Three models were developed for the U.S. Environmental Protection Agency to cover a range of spatial scales of interest to onsite operations. Two-dimensional (2D) hydrodynamic and sediment transport models from the Environmental Fluid Dynamics Code and the sediment bed model SEDZLJ1 were used to simulate potential resuspension, migration, and deposition of submerged oil and oiled sediment along a 38-mile reach of the Kalamazoo River affected by the oil from Marshall to Kalamazoo. An algorithm was added to SEDZLJ to represent three additional particle size classes of oilparticle aggregates (OPAs) with a range of sizes, specific gravities, and settling velocities. Field and laboratory experiments and flume tests were done to support the numerical modeling of OPAs. A three-dimensional hydrodynamic model was developed to simulate hydrodynamics and OPA tracking through Morrow Lake, the most downstream impoundment. This model incorporated wind and dam operations into high and low flow, lake drawdown, and containment simulations. Finally, a 2D unstructured grid model, HydroSed2D, was used to simulate flows and sediment transport along 1- to 2-mile segments of the Kalamazoo River around islands and through side channels and backwater areas that are particularly prone to submerged oil deposition. Integrated models could be developed quickly due to the availability of information and services combined with spill response operations that included: bathymetry and topography data, fieldbased geomorphic mapping of submerged oil, and discharge measured at U.S. Geological Survey streamflow gauges. Modeling results were included in a multiple-lines-of-evidence approach that was used by the Federal On-Scene Coordinator and operations staff for decision-making related to assessment and recovery of submerged oil, as well as net environmental benefit analysis. Similar modeling approaches will likely be useful for future oil spills in riverine environments.

Michigan↗

A technique for the reduction of banding in Landsat Thematic Mapper Images

The radiometric difference between forward and reverse scans in Landsat thematic mapper (TM) images, referred to as "banding," can create problems when enhancing the image for interpretation or when performing quantitative studies. Recent research has led to the development of a method that reduces the banding in Landsat TM data sets. It involves passing a one-dimensional spatial kernel over the data set. This kernel is developed from the statistics of the banding pattern and is based on the Wiener filter. It has been implemented on both a DOS-based microcomputer and several UNIX-based computer systems. The algorithm has successfully reduced the banding in several test data sets.

Photogrammetric Engineering and Remote Sensing↗

A digital system for surface reconstruction

A digital photogrammetric system, STEREO, was developed to determine three dimensional coordinates of points of interest (POIs) defined with a grid on a textureless and smooth-surfaced specimen. Two CCD cameras were set up with unknown orientation and recorded digital images of a reference model and a specimen. Points on the model were selected as control or check points for calibrating or assessing the system. A new algorithm for edge-detection called local maximum convolution (LMC) helped extract the POIs from the stereo image pairs. The system then matched the extracted POIs and used a least squares “bundle” adjustment procedure to solve for the camera orientation parameters and the coordinates of the POIs. An experiment with STEREO found that the standard deviation of the residuals at the check points was approximately 24%, 49% and 56% of the pixel size in the X, Y and Z directions, respectively. The average of the absolute values of the residuals at the check points was approximately 19%, 36% and 49% of the pixel size in the X, Y and Z directions, respectively. With the graphical user interface, STEREO demonstrated a high degree of automation and its operation does not require special knowledge of photogrammetry, computers or image processing.

Photogrammetric Engineering and Remote Sensing↗

Destriping of Landsat MSS images by filtering techniques

The removal of striping noise encountered in the Landsat Multispectral Scanner (MSS) images can be generally done by using frequency filtering techniques. Frequency domain filtering has, however, several problems, such as storage limitation of data required for fast Fourier transforms, ringing artifacts appearing at high-intensity discontinuities, and edge effects between adjacent filtered data sets. One way for circumventing the above difficulties is to design a spatial filter to convolve with the images. Because it is known that the striping always appears at frequencies of 1/6, 1/3, and 1/2 cycles per line, it is possible to design a simple one-dimensional spatial filter to take advantage of this a priori knowledge to cope with the above problems. The desired filter is the type of finite impulse response which can be designed by a linear programming and Remez's exchange algorithm coupled with an adaptive technique. In addition, a four-step spatial filtering technique with an appropriate adaptive approach is also presented which may be particularly useful for geometrically rectified MSS images.

Photogrammetric Engineering and Remote Sensing↗

Data management challenges in species distribution modeling

An important component in the fields of ecology and conservation biology is understanding the environmental conditions and geographic areas that are suitable for a given species to inhabit. A common tool in determining such areas is species distribution modeling which uses computer algorithms to determine the spatial distribution of organisms. Most commonly the correlative relationships between the organism and environmental variables are the primary consideration. The data requirements for this type of modeling consist of known presence and possibly absence locations of the species as well as the values of environmental or climatic covariates thought to define the species habitat suitability at these locations. These covariate data are generally extracted from remotely sensed imagery, interpolated/gridded historical climate data, or downscaled climate model output. Traditionally, ecologists and biologists have constructed species distribution models using workflows and data that reside primarily on their local workstations or networks. This workflow is becoming challenging as scientists increasingly try to use these modeling techniques to inform management decisions under different climate change scenarios. This challenge stems from the fact that remote sensing products, gridded historical climate, and downscaled climate models are not only increasing in spatial and temporal resolution but proliferating as well. Any rigorous assessment of uncertainty requires a computationally intensive sensitivity analysis accounting for various sources of uncertainty. The scientists fitting these models generally do not have the background in computer science required to take advantage of recent advances in web-service based data acquisition, remote high-powered data processing, or scientific workflow systems. Ecologists in the field of modeling are in need of a tractable platform that abstracts the inherent computational complexity required to incorporate the burgeoning field of coupled climate and ecological response modeling. In this paper we describe the computational challenges in species distribution modeling and solutions using scientific workflow systems. We focus on the Software for Assisted Species Modeling (SAHM) a package within VisTrails, an open-source scientific workflow system.

Bulletin of the Technical Committee on Data Engine↗

Synoptic evaluation of scale-dependent metrics for hydrographic line feature geometry

Methods of acquisition and feature simplification for vector feature data impact cartographic representations and scientific investigations of these data, and are therefore important considerations for geographic information science (Haunert and Sester 2008). After initial collection, linear features may be simplified to reduce excessive detail or to furnish a reduced-scale version of the features through cartographic generalization (Regnauld and McMaster 2008, Stanislawski et al. 2014). A variety of algorithms exist to simplify linear cartographic features, and all of the methods affect the positional accuracy of the features (Shahriari and Tao 2002, Regnauld and McMaster 2008, Stanislawski et al. 2012). In general, simplification operations are controlled by one or more tolerance parameters that limit the amount of positional change the operation can make to features. Using a single tolerance value can have varying levels of positional change on features; depending on local shape, texture, or geometric characteristics of the original features (McMaster and Shea 1992, Shahriari and Tao 2002, Buttenfield et al. 2010). Consequently, numerous researchers have advocated calibration of simplification parameters to control quantifiable properties of resulting changes to the features (Li and Openshaw 1990, Raposo 2013, Tobler 1988, Veregin 2000, and Buttenfield, 1986, 1989). This research identifies relations between local topographic conditions and geometric characteristics of linear features that are available in the National Hydrography Dataset (NHD). The NHD is a comprehensive vector dataset of surface 18 th ICA Workshop on Generalisation and Multiple Representation, Rio de Janiero, Brazil 2015 2 water features within the United States that is maintained by the U.S. Geological Survey (USGS). In this paper, geometric characteristics of cartographic representations for natural stream and river features are summarized for subbasin watersheds within entire regions of the conterminous United States and compared to topographic metrics. A concurrent processing workflow is implemented using a Linux high-performance computing cluster to simultaneously process multiple subbasins, and thereby complete the work in a fraction of the time required for a single-process environment. In addition, similar metrics are generated for several levels of simplification of the hydrographic features to quantify the effects of simplification over the various landscape conditions. Objectives of this exploratory investigation are to quantify geometric characteristics of linear hydrographic features over the various terrain conditions within the conterminous United States and thereby illuminate relations between stream geomorphological conditions and cartographic representation. The synoptic view of these characteristics over regional watersheds that is afforded through concurrent processing, in conjunction with terrain conditions, may reveal patterns for classifying cartographic stream features into stream geomorphological classes. Furthermore, the synoptic measurement of the amount of change in geometric characteristics caused by the several levels of simplification can enable estimation of tolerance values that appropriately control simplification-induced geometric change of the cartographic features within the various geomorphological classes in the country. Hence, these empirically derived rules or relations could help generate multiscale-representations of features through automated generalization that adequately maintain surface drainage variations and patterns reflective of the natural stream geomorphological conditions across the country.

Conference Paper↗

Remote measurement of surface-water velocity using infrared videography and PIV: a proof-of-concept for Alaskan rivers

Thermal cameras with high sensitivity to medium and long wavelengths can resolve features at the surface of flowing water arising from turbulent mixing. Images acquired by these cameras can be processed with particle image velocimetry (PIV) to compute surface velocities based on the displacement of thermal features as they advect with the flow. We conducted a series of field measurements to test this methodology for remote sensing of surface velocities in rivers. We positioned an infrared video camera at multiple stations across bridges that spanned five rivers in Alaska. Simultaneous non-contact measurements of surface velocity were collected with a radar gun. In situ velocity profiles were collected with Acoustic Doppler Current Profilers (ADCP). Infrared image time series were collected at a frequency of 10Hz for a one-minute duration at a number of stations spaced across each bridge. Commercial PIV software used a cross-correlation algorithm to calculate pixel displacements between successive frames, which were then scaled to produce surface velocities. A blanking distance below the ADCP prevents a direct measurement of the surface velocity. However, we estimated surface velocity from the ADCP measurements using a program that normalizes each ADCP transect and combines those normalized transects to compute a mean measurement profile. The program can fit a power law to the profile and in so doing provides a velocity index, the ratio between the depth-averaged and surface velocity. For the rivers in this study, the velocity index ranged from 0.82 – 0.92. Average radar and extrapolated ADCP surface velocities were in good agreement with average infrared PIV calculations.

Conference Paper↗

Probabilistic models of seafloor composition using multispectral acoustic backscatter: The benthic detectorists

We describe and compare two probabilistic models for task-specific seafloor characterization based on multispectral backscatter. We examine whether generative or discriminative approaches to supervised seafloor characterization do better at harnessing the greatly increased information about seafloor substrate composition that is encoded in the backscattering response across multiple frequencies. A Gaussian mixture model (GMM) is proposed as a generative model, and a fully-connected conditional random field (CRF) is proposed as a discriminative model. Either model uses input data derived from monospectral or multispectral backscatter without modification. The CRF approach considers both the relative backscatter magnitudes of different substrates as well as their relative proximity, and can be optimized using parameters. The GMM model, in contrast, includes no spatial information in its estimates, being based solely on relative backscatter magnitudes. Both GMM and CRF modeling approaches perform better with multispectral backscatter compared to monospectral, significantly outperforming all three monospectral frequencies. With multispectral backscatter inputs, based on average classification accuracies alone, there was little to choose between the two modeling approaches (classification accuracy of 81% and 83% for GMM and CRF models, respectively, evaluated using 50% of available bed observations to train and 50% to test the models). However, a CRF model that has been optimized with respect to its tunable parameters tends to produce higher posterior probabilities (i.e. greater certainty) for its classifications. Using monospectral backscatter inputs, the CRF model significantly outperformed the GMM model in terms of average classification accuracy. On balance, therefore, based on the evidence presented here, the CRF is suggested to be the superior approach for task-specific seafloor classification. Although further work using additional data is required to further examine this conclusion, the work presented here will guide and focus subsequent research efforts as more areas of the seafloor are mapped with the new technology. In order to facilitate these efforts, the algorithms presented here are encoded in a freely available python toolbox for Probabilistic acoustic Sediment Mapping, called PriSM , that can be used for both monospectral and multispectral backscatter. Finally, we show that application of the CRF model to the outputs of a geoacoustical model of seafloor scattering results in realistic substrate classification boundaries. This hybrid CRF and physics-based approach can predict the physical properties of the seafloor at a finer spatial resolution than is possible using the geoacoustical model alone.

Conference Paper↗

Earth's magnetic field complex: U.S. National activities during the Decade of Geopotential Field Research

The US geomagnetism community is supported by NASA, NOAA, USGS, NSF, DOD, and US universities. During the Decade of Geopotential Field Research, inaugurated in 1999 with the launch of the Danish satellite Ørsted on a US rocket, the US community has been involved in satellite mission development and analysis, instrument development, model development, and in the discovery and understanding of new processes with satellite magnetic signatures. The ESA Swarm mission has been a primary focus of the US community, with three US scientists on Swarm's Mission Advisory Group. Swarm will measure, for the first time, the E-W gradient of the magnetic field. One of us (T. Sabaka) is involved with the development of a Comprehensive inversion scheme as part of the SMART consortium. This effort is an outgrowth of the Comprehensive Model [1]. Swarm will also provide valuable observations for ionospheric specification and forecast. The geomagnetism group at NOAA (S. Maus, P. Alken and C. Manoj) has developed algorithms to estimate the strength of the eastward electric field (EEF). As the driver of the equatorial plasma fountain, the EEF is an important space weather parameter. ESA is considering the implementation of the EEF as a dedicated inversion chain in the Level-2 Facility. In 2006, NASA launched a minisatellite magnetometer constellation mission (ST-5) to test technologies and software. The ST-5 constellation featured the first along-track gradient measurements. NASA has also initiated efforts to study geomagnetism mission concepts after Swarm. One of the ideas under consideration is the systematic measurement of radial field gradients. Instrument development, and geomagnetic observatories, are also an integral part of the US effort. The past decade has seen significant advances in the development of a self-calibrating vector helium magnetometer, and in the automation of the US observatory network. Working in coordination with Intermagnet, the USGS Geomagnetism Program has made operational 1-second data acquisition at 13 of its magnetic observatories. The Program is also developing a realtime 1-minute and 1-hour Dst service. Within the past decade, US scientists have been leaders in the development of models that describe the global geomagnetic environment, including comprehensive models (the CM series), maps of the lithospheric field from satellite (MF-series), near surface maps of the lithospheric field (WDMAM-series), models of the thickness of the magnetic crust, the IGRF and World Magnetic Model series, ionospheric models such as the EEJM1, JVDM1, and the IRI, and data assimilation-based models (MoSST-series) that predict the future state of the geomagneic field.

Conference Paper↗

Distribution of regional pressure in the onshore and offshore Gulf of Mexico basin, USA

The U.S. Geological Survey (USGS) has created a comprehensive geopressure-gradient model of the regional pressure system spanning the onshore and offshore portions of the Gulf of Mexico, USA. The model was used to generate ten maps: five contour maps (Maps 1A - 5A) characterize the depth to the surface defined by the first occurrence of isopressure-gradients ranging from 0.60 psi/ft to 1.00 psi/ft, in 0.10-psi/ft increments, and five supporting maps (Maps 1B - 5B) display the spatial density of the data used to construct the isopressure-gradient maps. The boundary of the geopressure-gradient model represents the maximum extent of the calculated pressure-gradient data. The regional investigation, however, encompassed an area defined by the USGS Upper Jurassic-Cretaceous-Tertiary Composite Total Petroleum System Boundary, and the availability of offshore data. A description of the geopressure-gradient model, including related mathematical derivations, the data-quality control methodology, linear pressure interpolation calculations, and contouring algorithms is provided by Burke et al. (in press [a]; in press [b]); these references, as well as a summary of the geopressure-gradient model, are supplied in the online documentation .

Gulf of Mexico↗

USGS and DLR topographic mapping of Comet Borrelly

In the fall of 2001, NASA's Deep Space 1 (DS1) probe imaged Comet Borrelly during a flyby encounter. Three of the Borrelly images have geometry suitable to photogrammetrically map the nucleus, which form two stereopairs with an expected precision (EP) of ~410 m and ~670 m each. DS1 team members at the USGS and DLR have independently produced digital elevation models (DEMs) of Borrelly. Automatic stereo-matching algorithms were used by both USGS and DLR, but the USGS DEM was additionally manually edited in stereo. We accomplished a quantitative statistical comparison of the DEMs and found they have a standard deviation of 120 m, which is small compared to the EP above. There are systematic differences, we estimate the stereomatching error to only 0.20 pixel RMS, which is similar to the level of subpixel matching accuracy obtained in a wide variety of other mapping situations. The resulting DEMs enable a variety of applications such as perspective views, photometric modeling and studies of the energy balance of the nucleus. We hope to use the USGS DEM as a starting point to extrapolate the shape of the hidden side of the nucleus. This would not only let us determine the volume and moments of inertia of the nucleus, but would lead to a calculation of the insolation onto the nucleus averaged over an entire orbit, and thence to a model of the evolution of nuclear shape.

Conference Paper↗

Design and documentation of a Baltimore-Washington regional spatial database testbed for environmental model calibration and verification

Recent efforts by scientists and managers to inventory, map, and model impacts of human activities on the environment have focused on land transformation and urbanization processes. To test the efficacy of any single model, algorithm or procedure which defines land transformation processes a standard database calibration reference resource is required. Therefore, a set of georeferenced, spatially structured and well documented data sets has been designed for the Baltimore-Washington Region as a test and evaluation resource for the community of environmental modelers and global change scientists. Land transformation processes are being examined from a variety of perspectives and scales using a variety of indicator parameters and mensuration variables. Tools and techniques applied to land transformation assessments range from creation of simple population expansion maps to change detection calculations using remotely sensed satellite data. A variety of point and cell growth models have been applied to simulate the land transformation phenomenon. These activities have demonstrated the reality that urbanization and land transformation processes involve complex interacting variables. A team of scientists are expanding the efforts of the USGS Human Impacts on Land Transformation (HILT) project to build an Internet accessible "collaboratory" containing quality controlled spatially referenced calibration and validation databases. The Baltimore-Washington Regional Testbed provides for the calibration, verification, and validation for multiple scalar, temporal, thematic, and spectral assessments or models. This design and documentation procedures for creating the Baltimore-Washington Regional "Collaboratory" are presented in relation to its use for environmental modeling applications.

Maryland↗

Integrating magnetotellurics, soil gas geochemistry and structural analysis to identify hidden, high enthalpy, extensional geothermal systems

We applied magnetotellurics (MT), diagnostic structural affiliations, soil gas flux, and fluid geochemistry to assist in identifying hidden, high-enthalpy geothermal systems in extensional regimes of the U.S. Great Basin. We are specifically looking for high-angle, low-resistivity zones and dilatant geologic structures that can carry fluids from magmatic or high-grade metamorphic conditions in the deep crust upward to exploitable depths, and to verify the nature of the deep sources through soil gas and fluid compositions. The project was motivated by prior MT transect coverage of western and central Nevada centered upon the Dixie Valley producing geothermal system where such favorable indicators were first recognized. The high-angle MT structures are taken to be fluidized fault zones connecting deep magmatic/metamorphic activity with the geothermal system, but the concept required verification by testing at other systems. The project was set up with a two-phased organization. Phase I was carried out at the McGinness Hills system, central Nevada, where Ormat Inc flagship power facility is located and a considerable amount of pre-existing data were available. Resistivity models along MT transects also showed a strong low-resistivity upwelling originating from interpreted deep crustal magmatic underplating. Controlling structures on production as indicated by Ormat data and our new mapping were favorable to dilatancy, comprising an accommodation zone between major normal faults of opposing dip. A 3D MT survey and inversion confirmed the existence of the steep low-resistivity zone dipping ESE toward the deep crust and placed N-S bounds upon the feature. In cooperation with Ormat personnel, we sampled well fluids from production intervals for He isotope composition. Elevated 3He was verified through mass spectrometry analysis confirming a magmatic connection with the producing system. High CO2 soil gas flux including possibly metamorphic 13C and 14C component was measured over the area of dilatant structures. Hence, the triad of indicators posed above was confirmed in Phase I. Subsequently, Phase II of the project proceeded in the greenfield Kumiva-Blackrock Desert district of northwestern Nevada to see if a new system could be identified. Transect MT data also showed a low-resistivity upwelling originating from interpreted deep crustal magmatic underplating. An MT survey of 131 sites was imaged through 3D inversion using an in-house, DOE-supported finite element algorithm. Low resistivity upwellings that warranted follow up study occur under the flanks of the Seven Troughs Range, under Kumiva Playa immediately west of the Blue Wing Mountains, and under northern Granite Springs Valley. Structural assessment of the project area by Co-I J. Faulds at UNR provided numerous favorable Quaternary fault settings, which were correlated to the MT upwelling structures. Soil CO2 gas flux anomalies generally were not large but did show correlation with resistivity upwelling structure and favorable geological structures. Isotope analyses showed presence of possible inorganic/metamorphic 13C but 14C concentrations did not exceed background values. We view the initial concept of a confluence of low-resistivity upwelling, favorably dilatant 3D geological structure, and elevated soil gas flux including 13C component to be supported by the further evidence of this project although the indicators in the Phase II study were more diffuse. Mass balance calculations based upon 3He R/Ra values indicates that the proportion of magmatic fluids in a producing system is fairly low, 10-15% by volume. We suggest that the diagnostic MT geophysical structures denote zones of concentrated extensional deformation that increases permeability, potentially enabling a circulating upper crustal geothermal system, while at the same time connecting telltale deep component signatures to the upper crust. The northern Granite Springs Valley structure is receiving followup stu

Nevada↗

Object-based inversion of crosswell radar tomography data to monitor vegetable-oil injection experiment

Crosswell radar tomography methods can be used to dynamically image ground-water flow and mass transport associated with tracer tests, hydraulic tests, and natural physical processes. Dynamic imaging can be used to identify preferential flow paths and to help characterize complex aquifer heterogeneity. Unfortunately, because the raypath coverage of the interwell region is limited by the borehole geometry, the tomographic inverse problem is typically underdetermined, and tomograms may contain artifacts such as spurious blurring or streaking that confuse interpretation. We implement object-based inversion (using a constrained, non-linear, least-squares algorithm) as an alternative to pixel-based inversion approaches that utilize regularization (such as damping or smoothing criteria). Our approach requires pre- and post-injection travel-time data. Parameterization of the image plane comprises a small number of objects rather than a large number of pixels, resulting in an overdetermined problem that reduces the need for prior information. The nature and geometry of the objects are based on hydrologic insight into aquifer characteristics, the nature of the experiment, and the planned use of the geophysical results. The object-based inversion approach is demonstrated using synthetic and crosswell radar field data acquired during vegetable-oil injection experiments at a site in Fridley, Minnesota. The region where oil has displaced ground water is discretized as a stack of rectangles of variable horizontal extents. The inversion provides the geometry of the affected region and an estimate of the radar slowness change for each rectangle. Applying petrophysical models to these results and porosity from neutron logs, we estimate that the vegetable-oil emulsion saturation in various layers ranges from 60 to 90%. Further work is needed to assess the accuracy of the emulsion saturation estimates. Using synthetic- and field-data examples, the object-based inversion approach is shown to be an effective strategy for inverting crosswell radar tomography data acquired to monitor the emplacement of vegetable-oil emulsions. A principal advantage of object-based inversion is that it yields images that hydrologists and engineers can easily interpret and use for model calibration.

Conference Paper↗

Cross‐hole radar attenuation tomography using a frequency centroid down‐shift method: Consideration of non‐linear frequency dependence of EM wave attenuation

This paper presents a cross-hole radar attenuation tomography method based on analysis of the down-shift in the spectrum centroid frequency, and spectral broadening of the received radar signals. The method uses a parameter that combines centroid frequency down shift and variance increase for the projection function to construct the tomography algorithm. In comparison with other methods for estimating attenuation, the frequency down shift method is relatively insensitive to the effects of geometric spreading, antenna coupling, antenna radiation pattern,and instrument response, but the method requires the data to be broad-band so the frequency shift is easily measured. This method is well suited for difference tomography when electrically conductive tracers are used. The method was tested using cross-hole radar data acquired before and during a saline tracer injection experiment at the U.S.Geological Survey’s Fractured Rock Research Site at Mirror Lake, in Grafton County, New Hampshire. The attenuation-difference tomogram clearly outlines the location of the saline tracer within the tomography plane.

New Hampshire↗

Data collection network to support ecosystem forecasting for the Barataria Basin - Mississippi River domain

Ecosystem forecasting is limited by a number of uncertainties including inadequate initialization information, unknown boundary conditions, inaccurate model physics and atmospheric forcing functions, and inadequate algorithm development of geomorphic and ecological responses to hydrodynamic and geophysical processes. Monitoring can help reduce these uncertainties by providing numerical information on those variables that can improve simulation capabilities. A data collection network was designed for the Mississippi River, south of Tarbert Landing, Ms. to Venice, La., and for the inland and nearshore waters of Barataria Basin, La. The network considered existing monitoring efforts that effectively link oceanographic and water quality observations to system drivers to support ecosystem hindcasting, nowcasting, and forecasting capabilities. The design was driven by the diverse needs of the modeling community and utilized questionnaire surveys, workshops, and web- based applications to inventory past and present modeling applications, domains, and attributes. The use of existing monitoring stations, including variables measured and frequency of data collection, were also considered, as well as recommendations on where new monitoring stations should be located, what types of data should be collected, and at what temporal frequency. Compiled databases are presented as a series of GIS layers to represent overlap between existing and requested stations, and priorities are established for either maintaining or augmenting existing stations or deploying new stations. An optimization plan will be prepared from the results of this study that will provide a rationale for the ecosystem forecasting data collection network that includes a description of existing monitoring programs to support ecosystem forecasting and a set of justifiable locations for "megastations" that meet the needs of the modeling and assessment communities.

Louisiana↗

Habitat affinities and at-sea ranging behaviors among main Hawaiian Island seabirds: Breeding seabird telemetry, 2013–2016

Recent Hawaiʻi state clean energy policy mandates and federal interest in developing offshore renewable energy resources have prompted unsolicited lease requests for offshore wind energy infrastructure (OWEI) to be located in ocean waters off Hawaiʻi. This study describing at-sea ranging behaviors for five seabirds was intended to provide new information on Hawaiian breeding seabird distribution at sea, habitat utilization, and ranging behaviors within near-island waters and throughout outer continental shelf (OCS) waters surrounding the main Hawaiian Islands (MHI). We also estimate the percentage of time the five study species spent flying at altitudes equivalent to an expected rotor-swept-zone (RSZ; 30–194 m) for an offshore wind turbine and discuss potential collision risk from OWEI to the seabirds studied here. The MHI supports important seabird breeding populations and individual seabirds can now be equipped with a wide-variety of data loggers and location tracking devices that can provide complex, high-resolution information on movement patterns at sea. In this study, we used GPS loggers and temperature-depth-recorders (TDRs) to examine the at-sea distributions and ranging behaviors of five abundantly breeding species in the MHI: Red-tailed Tropicbird, Laysan Albatross, Wedge-tailed Shearwater, Brown Booby, and Red-footed Booby. We tracked these breeding seabirds from 14 different sites throughout the MHI; study colonies were located on the main islands of Maui, Oʻahu, Kauaʻi, and on associated islets. We used the Residence in Space and Time (RST) algorithm to classify behavior into resting, transiting, and searching/foraging (Torres et al. 2017). We used GPS altitude measurements to examine species-specific flight height and to estimate time spent flying in the RSZ. We mapped rediscretized tracking data for seabirds at each study colony according to behavioral class and trip type (when applicable) using kernel density estimates. During 2014–2016, we obtained GPS and TDR data from 59 and 34 Red-tailed Tropicbirds, respectively. Taken together, individuals revealed a bimodal (short- [~3 h, <100 km range] and long- [>3 d, >800 km range]) trip foraging strategy. While ranging at sea, we estimated that Red-tailed Tropicbirds spend 70.6% (95% confidence interval [CI] 70.1–71.0%) of flight time in the RSZ. TDR data for tropicbirds was noisy and we could not reliably identify dives. During 2014 and 2016, we obtained GPS data from 35 Laysan Albatrosses nesting on Kauaʻi and Oʻahu. Individuals during the mid- to late-chick rearing period engaged in a bimodal short- (<6 d, <400 km range) and long- (>6 d, >2,000 km range) trip foraging strategy. While ranging at sea, we estimated that Laysan Albatrosses spend 2.57% (95% CI 2.50–2.64%) of flight time in the RSZ. During 2013–2015, we obtained GPS and TDR data from 313 and 55 Wedge-tailed Shearwaters, respectively. Considering all the data together, individuals revealed a multi-modal trip duration foraging strategy consisting of intra-day (<24 h, <100 km range), short (<4 d, ~200 km range), and long (>4 d, ~100–400 km range) trips. While ranging at sea, we estimated that Wedge-tailed Shearwaters spend 5.20% (95% CI 5.13–5.27%) of flight time in the RSZ. Wedge-tailed Shearwaters dove to a mean (± SD) depth of 1.78 ± 1.35 m (median = 1.38 m); the deepest dive recorded was to 10.06 m. The mean dive duration for Wedge-tailed Shearwaters was 3.12 ± 3.44 s (median = 1.80 s). During 2014–2015, we obtained GPS and TDR data from 42 and 37 Brown Boobies, respectively. Almost all foraging trips (97%) were single-day trips and we did not detect any bimodality in the distribution of single-day trip durations. Brown Boobies foraged relatively close to their colony (<60 km range) and focused their at-sea use in nearshore, coastal waters off Kauaʻi and Niʻihau. While foraging at sea, we estimated that Brown Boobies spend 3.41% (95% CI 3.16–3.67%) of flight time in the RSZ

Hawaii↗