STABILITY ANALYSIS AND HAZARD ASSESSMENT OF THE NORTHERN SLOPES OF SAN VICENTE VOLCANO IN CENTRAL EL SALVADOR

Geologic hazards affect the lives of millions of people worldwide every year. El Salvador is a country that is regularly affected by natural disasters, including earthquakes, volcanic eruptions and tropical storms. Additionally, rainfall-induced landslides and debris flows are a major threat to the livelihood of thousands. The San Vicente Volcano in central El Salvador has a recurring and destructive pattern of landslides and debris flows occurring on the northern slopes of the volcano. In recent memory there have been at least seven major destructive debris flows on San Vicente volcano. Despite this problem, there has been no known attempt to study the inherent stability of these volcanic slopes and to determine the thresholds of rainfall that might lead to slope instability. This thesis explores this issue and outlines a suggested method for predicting the likelihood of slope instability during intense rainfall events. The material properties obtained from a field campaign and laboratory testing were used for a 2-D slope stability analysis on a recent landslide on San Vicente volcano. This analysis confirmed that the surface materials of the volcano are highly permeable and have very low shear strength and provided insight into the groundwater table behavior during a rainstorm. The biggest factors on the stability of the slopes were found to be slope geometry, rainfall totals and initial groundwater table location. Using the results from this analysis a stability chart was created that took into account these main factors and provided an estimate of the stability of a slope in various rainfall scenarios. This chart could be used by local authorities in the event of a known extreme rainfall event to help make decisions regarding possible evacuation. Recommendations are given to improve the methodology for future application in other areas as well as in central El Salvador.

Risk analysis of light-frame wood construction due to multiple hazards

Light-frame wood buildings are widely built in the United States (U.S.). Natural hazards cause huge losses to light-frame wood construction. This study proposes methodologies and a framework to evaluate the performance and risk of light-frame wood construction. Performance-based engineering (PBE) aims to ensure that a building achieves the desired performance objectives when subjected to hazard loads. In this study, the collapse risk of a typical one-story light-frame wood building is determined using the Incremental Dynamic Analysis method. The collapse risks of buildings at four sites in the Eastern, Western, and Central regions of U.S. are evaluated. Various sources of uncertainties are considered in the collapse risk assessment so that the influence of uncertainties on the collapse risk of lightframe wood construction is evaluated. The collapse risks of the same building subjected to maximum considered earthquakes at different seismic zones are found to be non-uniform. In certain areas in the U.S., the snow accumulation is significant and causes huge economic losses and threatens life safety. Limited study has been performed to investigate the snow hazard when combined with a seismic hazard. A Filtered Poisson Process (FPP) model is developed in this study, overcoming the shortcomings of the typically used Bernoulli model. The FPP model is validated by comparing the simulation results to weather records obtained from the National Climatic Data Center. The FPP model is applied in the proposed framework to assess the risk of a light-frame wood building subjected to combined snow and earthquake loads. The snow accumulation has a significant influence on the seismic losses of the building. The Bernoulli snow model underestimates the seismic loss of buildings in areas with snow accumulation. An object-oriented framework is proposed in this study to performrisk assessment for lightframe wood construction. For home owners and stake holders, risks in terms of economic losses is much easier to understand than engineering parameters (e.g., inter story drift). The proposed framework is used in two applications. One is to assess the loss of the building subjected to mainshock-aftershock sequences. Aftershock and downtime costs are found to be important factors in the assessment of seismic losses. The framework is also applied to a wood building in the state of Washington to assess the loss of the building subjected to combined earthquake and snow loads. The proposed framework is proven to be an appropriate tool for risk assessment of buildings subjected to multiple hazards. Limitations and future works are also identified.

Arc-flash analysis of utility power systems

The electric utility business is an inherently dangerous area to work in with employees exposed to many potential hazards daily. One such hazard is an arc flash. An arc flash is a rapid release of energy, referred to as incident energy, caused by an electric arc. Due to the random nature and occurrence of an arc flash, one can only prepare and minimize the extent of harm to themself, other employees and damage to equipment due to such a violent event. Effective January 1, 2009 the National Electric Safety Code (NESC) requires that an arc-flash assessment be performed by companies whose employees work on or near energized equipment to determine the potential exposure to an electric arc. To comply with the NESC requirement, Minnesota Power’s (MP’s) current short circuit and relay coordination software package, ASPEN OneLinerTM and one of the first software packages to implement an arc-flash module, is used to conduct an arc-flash hazard analysis. At the same time, the package is benchmarked against equations provided in the IEEE Std. 1584-2002 and ultimately used to determine the incident energy levels on the MP transmission system. This report goes into the depth of the history of arc-flash hazards, analysis methods, both software and empirical derived equations, issues of concern with calculation methods and the work conducted at MP. This work also produced two offline software products to conduct and verify an offline arc-flash hazard analysis.

Analysis of spring break-up and its effects on a biomass feedstock supply chain in northern Michigan

Demand for bio-fuels is expected to increase, due to rising prices of fossil fuels and concerns over greenhouse gas emissions and energy security. The overall cost of biomass energy generation is primarily related to biomass harvesting activity, transportation, and storage. With a commercial-scale cellulosic ethanol processing facility in Kinross Township of Chippewa County, Michigan about to be built, models including a simulation model and an optimization model have been developed to provide decision support for the facility. Both models track cost, emissions and energy consumption. While the optimization model provides guidance for a long-term strategic plan, the simulation model aims to present detailed output for specified operational scenarios over an annual period. Most importantly, the simulation model considers the uncertainty of spring break-up timing, i.e., seasonal road restrictions. Spring break-up timing is important because it will impact the feasibility of harvesting activity and the time duration of transportation restrictions, which significantly changes the availability of feedstock for the processing facility. This thesis focuses on the statistical model of spring break-up used in the simulation model. Spring break-up timing depends on various factors, including temperature, road conditions and soil type, as well as individual decision making processes at the county level. The spring break-up model, based on the historical spring break-up data from 27 counties over the period of 2002-2010, starts by specifying the probability distribution of a particular county’s spring break-up start day and end day, and then relates the spring break-up timing of the other counties in the harvesting zone to the first county. In order to estimate the dependence relationship between counties, regression analyses, including standard linear regression and reduced major axis regression, are conducted. Using realizations (scenarios) of spring break-up generated by the statistical spring breakup model, the simulation model is able to probabilistically evaluate different harvesting and transportation plans to help the bio-fuel facility select the most effective strategy. For early spring break-up, which usually indicates a longer than average break-up period, more log storage is required, total cost increases, and the probability of plant closure increases. The risk of plant closure may be partially offset through increased use of rail transportation, which is not subject to spring break-up restrictions. However, rail availability and rail yard storage may then become limiting factors in the supply chain. Rail use will impact total cost, energy consumption, system-wide CO2 emissions, and the reliability of providing feedstock to the bio-fuel processing facility.

PROBABILISTIC MODELING OF RAINFALL INDUCED LANDSLIDE HAZARD ASSESSMENT IN SAN JUAN LA LAGUNA, SOLOLÁ, GUATEMALA

The municipality of San Juan La Laguna, Guatemala is home to approximately 5,200 people and located on the western side of the Lake Atitlán caldera. Steep slopes surround all but the eastern side of San Juan. The Lake Atitlán watershed is susceptible to many natural hazards, but most predictable are the landslides that can occur annually with each rainy season, especially during high-intensity events. Hurricane Stan hit Guatemala in October 2005; the resulting flooding and landslides devastated the Atitlán region. Locations of landslide and non-landslide points were obtained from field observations and orthophotos taken following Hurricane Stan. This study used data from multiple attributes, at every landslide and non-landslide point, and applied different multivariate analyses to optimize a model for landslides prediction during high-intensity precipitation events like Hurricane Stan. The attributes considered in this study are: geology, geomorphology, distance to faults and streams, land use, slope, aspect, curvature, plan curvature, profile curvature and topographic wetness index. The attributes were pre-evaluated for their ability to predict landslides using four different attribute evaluators, all available in the open source data mining software Weka: filtered subset, information gain, gain ratio and chi-squared. Three multivariate algorithms (decision tree J48, logistic regression and BayesNet) were optimized for landslide prediction using different attributes. The following statistical parameters were used to evaluate model accuracy: precision, recall, F measure and area under the receiver operating characteristic (ROC) curve. The algorithm BayesNet yielded the most accurate model and was used to build a probability map of landslide initiation points. The probability map developed in this study was also compared to the results of a bivariate landslide susceptibility analysis conducted for the watershed, encompassing Lake Atitlán and San Juan. Landslides from Tropical Storm Agatha 2010 were used to independently validate this study’s multivariate model and the bivariate model. The ultimate aim of this study is to share the methodology and results with municipal contacts from the author's time as a U.S. Peace Corps volunteer, to facilitate more effective future landslide hazard planning and mitigation.

GROUND-BASED AND SATELLITE REMOTE SENSING OF PAROXYSMAL ERUPTIONS AT ETNA VOLCANO, 2011-2012.

Mt Etna's activity has increased during the last decade with a tendency towards more explosive eruptions that produce paroxysmal lava fountains. From January 2011 to April 2012, 25 lava fountaining episodes took place at Etna's New South-East Crater (NSEC). Improved understanding of the mechanism driving these explosive basaltic eruptions is needed to reduce volcanic hazards. This type of activity produces high sulfur dioxide (SO2) emissions, associated with lava flows and ash fall-out, but to date the SO2 emissions associated with Etna's lava fountains have been poorly constrained. The Ultraviolet (UV) Ozone Monitoring Instrument (OMI) on NASA's Aura satellite and the Atmospheric Infrared Sounder (AIRS) on Aqua were used to measure the SO2 loadings. Ground-based data from the Observatoire de Physique du Globe de Clermont-Ferrand (OPGC) L-band Doppler radar, VOLDORAD 2B, used in collaboration with the Italian National Institute of Geophysics and Volcanology in Catania (INGV-CT), also detected the associated ash plumes, giving precise timing and duration for the lava fountains. This study resulted in the first detailed analysis of the OMI and AIRS SO2 data for Etna's lava fountains during the 2011-2012 eruptive cycle. The HYSPLIT trajectory model is used to constrain the altitude of the observed SO2 clouds, and results show that the SO2 emission usually coincided with the lava fountain peak intensity as detected by VOLDORAD. The UV OMI and IR AIRS SO2 retrievals permit quantification of the SO2 loss rate in the volcanic SO2 clouds, many of which were tracked for several days after emission. A first attempt to quantitatively validate AIRS SO2 retrievals with OMI data revealed a good correlation for high altitude SO2 clouds. Using estimates of the emitted SO2 at the time each paroxysm, we observe a correlation with the inter-paroxysm repose time. We therefore suggest that our data set supports the collapsing foam (CF) model [1] as driving mechanism for the paroxysmal events at the NSEC. Using VOLDORAD-based estimates of the erupted magma mass, we observe a large excess of SO2 in the eruption clouds. Satellite measurements indicate that SO2 emissions from Etnean lava fountains can reach the lower stratosphere and hence could pose a hazard to aviation. [1] Parfitt E.A (2004). A discussion of the mechanisms of explosive basaltic eruptions. J. Volcanol. Geotherm. Res. 134, 77-107.

SLOPE STABILITY ANALYSIS OF MOUNT MEAGER, SOUTH-WESTERN BRITISH COLUMBIA, CANADA

The Mount Meager Volcanic Complex (MMVC) in south-western British Columbia is a potentially active, hydrothermally altered massif comprising a series of steep, glaciated peaks. Climatic conditions and glacial retreat has led to the further weathering, exposure and de-buttressing of steep slopes composed of weak, unconsolidated material. This has resulted in an increased frequency of landslide events over the past few decades, many of which have dammed the rivers bordering the Complex. The breach of these debris dams presents a risk of flooding to the downstream communities. Preliminary mapping showed there are numerous sites around the Complex where future failure could occur. Some of these areas are currently undergoing progressive slope movement and display features to support this such as anti-scarps and tension cracks. The effect of water infiltration on stability was modelled using the Rocscience program Slide 6.0. The main site of focus was Mount Meager in the south- east of the Complex where the most recent landslide took place. Two profiles through Mount Meager were analysed along with one other location in the northern section of the MMVC, where instability had been detected. The lowest Factor of Safety (FOS) for each profile was displayed and an estimate of the volume which could be generated was deduced. A hazard map showing the inundation zones for various volumes of debris flows was created from simulations using LAHARZ. Results showed the massif is unstable, even before infiltration. Varying the amount of infiltration appears to have no significant impact on the FOS annually implying that small changes of any kind could also trigger failure. Further modelling could be done to assess the impact of infiltration over shorter time scales. The Slide models show the volume of material that could be delivered to the Lillooet River Valley to be of the order of 109 m3 which, based on the LAHARZ simulations, would completely inundate the valley and communities downstream. A major hazard of this is that the removal of such a large amount of material has the potential to trigger an explosive eruption of the geothermal system and renew volcanic activity. Although events of this size are infrequent, there is a significant risk to the communities downstream of the complex.