Volcanic processes and human exposure as elements to build a risk model for Volcan de Fuego, Guatemala

The activity of Fuego volcano during the 1999 - 2013 eruptive episode is studied through field, remote sensing and observatory records. Mapping of the deposits allows quantifying the erupted volumes and areas affected by the largest eruptions during this period. A wide range of volcanic processes results in a diversity of products and associated deposits, including minor airfall tephra, rockfall avalanches, lava flows, and pyroclastic flows. The activity can be characterized by long term, low level background activity, and sporadic larger explosive eruptions. Although the background activity erupts lava and ash at a low rate (~ 0.1 m3/s), the persistence of such activity over time results in a significant contribution (~ 30%) to the eruption budget during the studied period. Larger eruptions produced the majority of the volume of products during the studied period, mainly during three large events (May 21, 1999, June 29, 2003, and September 13, 2012), mostly in the form of pyroclastic flows. A total volume of ~ 1.4 x 108 m3 was estimated from the mapped deposits and the estimated background eruption rate. Posterior remobilization of pyroclastic flow material by stream erosion in the highly confined Barranca channels leads to lahar generation, either by normal rainfall, or by extreme rainfall events. A reassessment of the types of products and volumes erupted during the decade of 1970's allows comparing the activity happening since 1999 with the older activity, and suggests that many of the eruptive phenomena at Fuego may have similar mechanisms, despite the differences in scale between. The deposits of large pyroclastic flows erupted during the 1970's are remarkably similar in appearance to the deposit of pyroclastic flows from the 1999 - 2013 period, despite their much larger volume; this is also the case for prehistoric eruptions. Radiocarbon dating of pyroclastic flow deposits suggests that Fuego has produced large eruptions many times during the last ~ 2 ka, including larger eruptions during the last 500 years, which has important hazard implications. A survey was conducted among the local residents living near to the volcano, about their expectations of possible future crises. The results show that people are aware of the risk they could face in case of a large eruption, and therefore they are willing to evacuate in such case. However, their decision to evacuate may also be influenced by the conditions in which the evacuation could take place. If the evacuation represents a potential loss of their livelihood or property they will be more hesitant to leave their villages during a large eruption. The prospect of facing hardship conditions during the evacuation and in the shelters may further cause reluctance to evacuate. A short discussion on some of the issues regarding risk assessment and management through an early warning system is presented in the last chapter.

Invasion patterns of emerald ash borer and European earthworms in forested ecosystems

Invasive and exotic species present a serious threat to the health and sustainability of natural ecosystems. These species often benefit from anthropogenic activities that aid their introduction and dispersal. This dissertation focuses on invasion dynamics of the emerald ash borer, native to Asia, and European earthworms. These species have shown detrimental impacts in invaded forest ecosystems across the Great Lakes region, and continue to spread via human-assisted long distance dispersal and by natural modes of dispersal into interior forests from areas of introduction. Successful forest management requires that the impact and effect of invasive species be considered and incorporated into management plans. Understanding patterns and constraints of introduction, establishment, and spread will aid in this effort. To assist in efforts to locate introduction points of emerald ash borer, a multicriteria risk model was developed to predict the highest risk areas. Important parameters in the model were road proximity, land cover type, and campground proximity. The model correctly predicted 85% of known emerald ash borer invasion sites to be at high risk. The model’s predictions across northern Michigan can be used to focus and guide future monitoring efforts. Similar modeling efforts were applied to the prediction of European earthworm invasion in northern Michigan forests. Field sampling provided a means to improve upon modeling efforts for earthworms to create current and future predictions of earthworm invasion. Those sites with high soil pH and high basal area of earthworm preferred overstory species (such as basswood and maples) had the highest likelihood of European earthworm invasion. Expanding beyond Michigan into the Upper Great Lakes region, earthworm populations were sampled across six National Wildlife Refuges to identify potential correlates and deduce specific drivers and constraints of earthworm invasion. Earthworm communities across all refuges were influenced by patterns of anthropogenic activity both within refuges and in surrounding ecoregions of study. Forest composition, soil pH, soil organic matter, anthropogenic cover, and agriculture proximity also proved to be important drivers of earthworm abundance and community composition. While there are few management options to remove either emerald ash borer or European earthworms from forests after they have become well established, prevention and early detection are important and can be beneficial. An improved understanding the factors controlling the distribution and invasion patterns of exotic species across the landscape will aid efforts to determine their consequences and generate appropriate forest management solutions to sustain ecosystem health in the presence of these invaders.

Evaluation of flood risk in response to climate variability

Standard procedures for forecasting flood risk (Bulletin 17B) assume annual maximum flood (AMF) series are stationary, meaning the distribution of flood flows is not significantly affected by climatic trends/cycles, or anthropogenic activities within the watershed. Historical flood events are therefore considered representative of future flood occurrences, and the risk associated with a given flood magnitude is modeled as constant over time. However, in light of increasing evidence to the contrary, this assumption should be reconsidered, especially as the existence of nonstationarity in AMF series can have significant impacts on planning and management of water resources and relevant infrastructure. Research presented in this thesis quantifies the degree of nonstationarity evident in AMF series for unimpaired watersheds throughout the contiguous U.S., identifies meteorological, climatic, and anthropogenic causes of this nonstationarity, and proposes an extension of the Bulletin 17B methodology which yields forecasts of flood risk that reflect climatic influences on flood magnitude. To appropriately forecast flood risk, it is necessary to consider the driving causes of nonstationarity in AMF series. Herein, large-scale climate patterns—including El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO)—are identified as influencing factors on flood magnitude at numerous stations across the U.S. Strong relationships between flood magnitude and associated precipitation series were also observed for the majority of sites analyzed in the Upper Midwest and Northeastern regions of the U.S. Although relationships between flood magnitude and associated temperature series are not apparent, results do indicate that temperature is highly correlated with the timing of flood peaks. Despite consideration of watersheds classified as unimpaired, analyses also suggest that identified change-points in AMF series are due to dam construction, and other types of regulation and diversion. Although not explored herein, trends in AMF series are also likely to be partially explained by changes in land use and land cover over time. Results obtained herein suggest that improved forecasts of flood risk may be obtained using a simple modification of the Bulletin 17B framework, wherein the mean and standard deviation of the log-transformed flows are modeled as functions of climate indices associated with oceanic-atmospheric patterns (e.g. AMO, ENSO, NAO, and PDO) with lead times between 3 and 9 months. Herein, one-year ahead forecasts of the mean and standard deviation, and subsequently flood risk, are obtained by applying site specific multivariate regression models, which reflect the phase and intensity of a given climate pattern, as well as possible impacts of coupling of the climate cycles. These forecasts of flood risk are compared with forecasts derived using the existing Bulletin 17B model; large differences in the one-year ahead forecasts are observed in some locations. The increased knowledge of the inherent structure of AMF series and an improved understanding of physical and/or climatic causes of nonstationarity gained from this research should serve as insight for the formulation of a physical-casual based statistical model, incorporating both climatic variations and human impacts, for flood risk over longer planning horizons (e.g., 10-, 50, 100-years) necessary for water resources design, planning, and management.