"The need obliged us" : culture as capacity during the Hurricane Stan emergency response. A case study from Tectitan, Huehuetenango, Guatemala

A major deficiency in disaster management plans is the assumption that pre-disaster civil-society does not have the capacity to respond effectively during crises. Following from this assumption a dominant emergency management strategy is to replace weak civil-society organizations with specialized disaster organizations that are often either military or Para-military and seek to centralize decision-making. Many criticisms have been made of this approach, but few specifically addresses disasters in the developing world. Disasters in the developing world present unique problems not seen in the developed world because they often occur in the context of compromised governments, and marginalized populations. In this context it is often community members themselves who possess the greatest capacity to respond to disasters. This paper focuses on the capacity of community groups to respond to disaster in a small town in rural Guatemala. Key informant interviews and ethnographic observations are used to reconstruct the community response to the disaster instigated by Hurricane Stan (2005) in the municipality of Tectitán in the Huehuetenango department. The interviews were analyzed using techniques adapted from grounded theory to construct a narrative of the events, and identify themes in the community’s disaster behavior. These themes are used to critique the emergency management plans advocated by the Guatemalan National Coordination for the Reduction of Disasters (CONRED). This paper argues that CONRED uncritically adopts emergency management strategies that do not account for the local realities in communities throughout Guatemala. The response in Tectitán was characterized by the formation of new organizations, whose actions and leadership structure were derived from “normal” or routine life. It was found that pre-existing social networks were resilient and easily re-oriented meet the novel needs of a crisis. New or emergent groups that formed during the disaster utilized social capital accrued by routine collective behavior, and employed organizational strategies derived from “normal” community relations. Based on the effectiveness of this response CONRED could improve its emergency planning on the local-level by utilizing the pre-existing community organizations rather than insisting that new disaster-specific organizations be formed.

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.