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.

USING MOSSES TO ASSESS CONDITIONS IN NORTHERN WHITE CEDAR SWAMPS

Northern white cedar (Thuja occidentalis L.) (NWC) swamps are valuable both commercially and ecologically. Unfortunately, many NWC swamps are degraded and information about them is not abundant. Especially there have been no definitive studies about mosses in northern white cedar swamps and how they react to disturbances. Mosses are sensitive to changes in their environment and thus they could be used to assess ecosystem conditions of NWC swamps. The objective of this study was to determine if mosses could be used to asses conditions in NWC swamps and if there are differences between moss communities in disturbed and undisturbed sites. Seventeen sample plots were taken from 12 disturbed and undisturbed sites around upper Michigan and northern Minnesota in the summer of 2012. All mosses occurring on the plots were identified and several associated environmental parameters were measured. The main environmental conditions affecting moss communities were identified with non-metric multidimensional scaling (NMS). Multiple response permutation procedures (MRPP) were run to ascertain if there were significant differences in community composition between disturbances. Indicator species analysis was then done to identify species that are related to different types of disturbances. A one-way ANOVA was used to check for significant differences between species richness and moss cover of undisturbed and disturbed sites. Over all sixty-two moss species were identified. The results indicate that there was no significant difference in species richness or moss cover between disturbed and undisturbed sites. However, moss community composition was affected by disturbance and strongly divided by a wetness gradient. Dicranum fuscescens was found to indicate undisturbed conditions. Calliergon cordifolium and Climacium dendroides indicated disturbed sites with wet conditions. Brotherella recurvans and Eurhynchium pulchellum indicated swamps with other disturbances.