Mapas de susceptibilidad al deslizamiento en las microcuencas de los ríos Torres y Tibás, Costa Rica

Abstract

Costa Rica is a very mountainous territory, with faulting, steed slopes and climatic conditions, which promotes landslides generation that can be aggravated with trigger variables. Historically, Central valley has high susceptibility to landslides. To prevent a disaster is necessary to implement models that identify areas prone to earth movements. The Vahrson and Mora method was used during this study development, due to its ease of use and high implementation in America. This study aimed to develop maps of landslides susceptibility in the micro-basin of rivers Torres and Tibas. Torres River micro-basin is located in the province of San José and has 4952 ha approximately and the micro-basin of Tibás River covers about 4640 ha and is located in Heredia. To elaborate maps, data from passive slope elements, lithology and soil moisture were obtained, including active elements of seismic intensity and rain intensity. An influence index was defined for each factor and susceptibility maps were generated; active factors were added and multiplied by passive factors. Then, the resulting maps of the passive factors were multiplied with the resulting maps from the active factors to obtain the susceptibility map for each micro-basin. In the Torres River micro-basin the greatest area corresponded to average susceptibility (52,48% area) and only 1,34% had high susceptibility to suffer landslide. In the Tibás River micro-basin the average category regarding susceptibility represented a 52,09% area and 9,52% corresponded to high susceptibility area. Finally, land use was compared to landslide susceptible areas to identify land uses categories that were more likely to suffer landslides, being the categories of secondary forest and primary forest in the micro-basin of rivers Torres and Tibás respectability. Choosing regulatory measures is necessary in infrastructure construction and urban growth and natural resources protection in areas most likely to have mass removals.