Research Posters

Titlesort icon Author(s) Keyword(s) Abstract
Relocating San Miguel Volcanic Seismic Events for Future Velocity and Tomographic Models
volcanology
seismology
San Miguel
velocity model
tomography

The San Miguel volcano lies near the city of San Miguel, El Salvador (13.43N and -88.26W). San Miguel volcano is an active volcano and presents a significant natural hazard for the city of San Miguel. Furthermore, the internal state and activity of active volcanoes remains an important component to understanding volcanic hazard. The main technology for addressing volcanic hazards and processes is through the analysis of data collected from the deployment of seismic sensors that record ground motion. By analyzing seismic data, we can create images of the internal structure of a volcano to address the location and state of the magma chamber. Six UTEP seismic stations were deployed around San Miguel volcano from 2007-2008 to define the magma chamber and assess the seismic and volcanic hazard. We will be utilizing this data to develop images of the earth structure beneath the volcano, studying the volcanic processes by identifying different sources, and investigating the role of earthquakes and faults in controlling the volcanic processes.

On Optimization Techniques for the One-Dimensional Seismic Problem
optimization
seismic

An optimization code is being developed by the Numerical Optimization Group at UTEP that is to be used with the Hole's Algorithm for solving one-dimensional seismic travel time tomography problem. The new code will offer the use of restrictions in material properties and parameters by applying Interior-Point Methodology. The current Hole's algorithm does not incorporate such restrictions explicitly in the formulation of the nonlinear least squares problem. Our goal is to incorporate our optimization algorithms into the Hole's algorithm. This work is being funded by NSF CyberShare Crest Center, Grant No. HRD-0734825.

GIS-tool to optimize site selection for establishing an eddy covariance and robotic tram system at the Jornada Experimental Range (JER), NM
Eddy Covariance
robotic tram system
site selection

Site selection is critical for establishing eddy covariance and robotic tram systems. These systems measure the exchange of carbon dioxide, water and energy across the land-atmosphere boundary (eddy covariance), and the optical properties of the land surface (robotic tram system). Both technologies have specific requirements that can increase/decrease uncertainty of data. Among them are: flat terrain, homogeneous canopy height, wind speed (>1.5m/s), regional and local representation of land cover types, avoidance of current and historical disturbance and, logistics. Currently, there are no established quantifiable methods or standards to optimize site selection of these systems and the subsequent impact on data integrity remains unknown. A multi criteria analysis was executed following site selection models that have been applied to environmental problems and spatial missions. For this particular scenario, the use of ARCGIS9.2 software allowed to overlay several raster images using a common measurement scale and weights, each according to its importance on the decision tool. The specific aim was to find a local and regional representative landscape of the study area that best fulfills instrumentation requirements, and to reduce sources of random errors by characterizing potential flux footprints variations due to changes in wind speed and direction, topography, and other environmental factors.

Formally Specifying and Validating Data Assurance Properties for Real Time Data Processing Applications
assurance
real time
formally

As global environmental conditions rapidly change, environmental scientists constantly use new data-intensive field-based instrument technologies to understand such changes. As the environmental sciences become more data driven, a need to develop mechanisms and procedures to verify the integrity of the data has increased. The quality of the data integrity verification mechanisms is as good as the quality of the properties specified. Thus, there is a need to develop an approach to allow scientists and non-software engineering domain experts to “formally” specify data assurance properties. This work defines an approach to formally specify real time data properties; and provides visualization of data properties that would allow users to validate whether the specified property captures the desired intent.

Crustal Structure of the Salton Trough: Integration of Receiver Functions, Gravity, and Magnetic Data
crustal structure
receiver function
gravity
magnetic

We have constructed new crustal scale models of a unique basin, the Salton Trough of southwestern California, which is inferred to be an incipient ocean basin. The Salton Trough is a polyphase basin with significant extension in addition to dextral shear. To further explore the origin and evolution of this basin, we have integrated receiver functions, gravity, and aeromagnetic data to create subsurface crustal scale models. Gravity data analyses show that lower crust is the source of the anomalies in the Salton Trough area. Receiver function data suggests the Moho is 22 km deep to the south of the Salton Sea and deepens to 32 km in the region east of the Salton Trough. Gravity modeling shows that the density of the lower crust is 2950 kg/m3, which is an indication for gabbroic composition, while the density of the upper crust varies from 2650 kg/m3 to 2450 kg/m3 and the depth of sedimentary and meta-sedimentary rocks appears to be 8-10 km. Most of magnetic anomalies show shallow relief and are low amplitude with some exceptions in the marginal areas, which suggests the absence of shallow buried mafic intrusions and deep basement. Slab window model fails to explain the low gravity, low magnetic anomalies along the coastal margin of the Salton Trough because of 1) the steep lateral decrease in the heat flow from the Coastal Ranges to the Great Valley, and 2) the source of the anomalies is in the crust; instead we refer these anomalies to the isostatic effect of the Peninsular Ranges. Gravity data filtering revealed an anomaly that crosses the Salton Trough in E-W direction and extends from the Pacific Ocean to Arizona. We tested several scenarios to explain this anomaly; we suggest that this anomaly represents a Jurassic rift flank.

Computational Methods in Epidemiology
Computational Methods
Epidemiology

There is an increasing interest in modeling risk associated with emerging infectious diseases (EIDs). Disease risks, (like risk associated with invasive species), are endogenous, however most model treat risk as exogenous and intrinsic. The SPIDER group, in collaboration with researchers from the University of Texas at El Paso (UTEP) and Arizona State University (ASU), will study models both to forecast and estimate the risk associated with emerging infectious diseases in humans livestock and plants. In this poster we present a simple example of how we can model infectious diseases.

Computational Knowledge and Resources for Research and Education
Computational Knowledge
Resources for Research
Education

To advance and integrate education and research in uncertainty, trust, and optimization support of cyberinfrastructures and to develop scientist-centered software services and tools that encourage collaborative and interdisciplinary research approaches.

A Social Networking Environment to Support Collaborative Scientific Research CI-Server

As scientific research becomes more collaborative, there is an emerging need to enhance the design of software for multi-disciplinary scientific teams. Coordination theory is an area of research that is being used to identify and model collaborative techniques in a tool called WFTalk. The goal of WFTalk is to provide models of collaborative techniques that can be embedded in software tools to facilitate discussing and meeting research goals.

A Runtime Data Verification Cyberinfrastructure for an Automated Robotic Tram System Measuring Surface Reflectance in the ArcticThis
artic
robotic tram system
surface
reflectance

Global change is amongst the greatest challenges facing humanity. Understanding the future state of the Earth System and how humans will need to adapt requires: Improved environmental observation capacity, more thorough understanding of environmental connectivity and, integration of such data into predictive models. Environmental science is becoming data driven. There is a need for improved mechanisms and procedures to verify the integrity of data streams and improve trust in and optimization of data and workflow.

A Primer in Seismology
Primer
Seismology

Seismology impacts society through applications including seismic explorations(seismic profiling), earthquake studies, and nuclear arms control. The fundamental data for seismological studies of the earth’s interior are the travel times of seismic waves. They depend on the characteristics of the media through which the seismic waves
propagate.

A new site for measuring multi-scale land-atmosphere carbon, water, and energy exchange at the Jornada experimental range

Deserts and semi-arid landscapes comprise 35% of the land surface area on Earth and an eminent challenge is to predict how global climate change will impact local to global-scale provisioning of ecosystems goods and services. Understanding the sources, sinks, pathways, and mechanisms controlling the cycling of carbon, water, and energy is key to meeting this challenge, which, in arid landscapes, remains poorly studied. This study utilizes and further advances a range of technologies and cyberinfrastructure tools at a new research site located on the Jornada Basin Experimental Range. Site-based infrastructure includes an eddy covariance tower that measures landscape level carbon, water, and energy exchange, a robotic tram system that measures atmospheric and ground based optical reflectance (400-1000nm), a group based sensor network, and an unmanned ground vehicle system that will remotely sense a range of ecological variables. A range of plant phenology measurements and multi-scale (leaf to landscape) will be made using methods developed in the Jornada LTER program to link ecosystem structural and functional attributes measured at the site and allow for inter-site comparisons with measurements being made at LTER sites. Plot to satellite level measurements or estimates of plant productivity and other measures will be made to permit scaling of ecosystems properties and processes.

A Fixed Point Algorithm for l1 large scale underdetermined systems
fixed point algorithm
large scale
underdetermined systems

Current data acquisition methods are often extremely wasteful. Many protocols acquire massive amounts of data which are then (in large part) discarded without much information by a subsequent compression stage (necessary for storage and transmission). It is possible to recover signals from far fewer measurements than was thought necessary! In practice, this means for example that high resolution imaging is possible with fewer sensors.

A Fast, Practical Alternative Towards Joint Inversion of Multiple Datasets
joint inversion
alternative

There are many sources of data for Earth tomography models. Currently, each of these datasets is processed separately, resulting in several different Earth models that have specific coverage areas, different spatial resolutions and varying degreesof accuracy. These models often provide complimentary geophysical information on earth structure. To combine the information derived from these complementary models requires a joint inversion method. While such methods are being developed, as a first step, we propose a practical solution to fuse the Earth models coming from different datasets.