Modelo morfométrico para determinar áreas susceptibles a procesos de ladera

Abstract

In tropical countries where both internal and external active geodynamic conditions exist and relief modeling is constantly changing, hillside processes are one of the most recurring natural hazards that cause human and economic losses each year. In Costa Rica, for example, these phenomena cause approximately 30% of the disasters that affect the country each year. The study area comprises a section of 52 km² in the extreme geographical coordinates: 10,23 ° N and 10,18 ° S; -84.23 ° W and -84.14 ° E; which is located on the northeast slope of the Poás volcano in Costa Rica and has the physical characteristics of rainfall above 2000 mm per year, intense tectonic dynamics associated with different tectonic faults and dense tropical vegetation. The objective of this work is to show a morphometric model to determine susceptible areas to hillslope processes, starting from the case study of the most affected region by the landslides triggered during the Cinchona Earthquake in 2009. The morphometry or geomorphometry is the quantitative analysis of the terrestrial surface; among its fundamental variables are altimetry or hypsometry, slope of the terrain and drainage density. The morphometric methods used are based on the approaches of Simonov (1985), Lugo (1988) and Zamorano (1990). Seven morphometric maps were developed that indirectly explain the geomorphological dynamics of this territory. Firstly, the cartography of dissection density, depth of dissection, relief energy and total erosion were performed. The density of the dissection calculates the concentration of river channels in a specific area, aiming to establish zones of greater or lesser concentration of river courses and therefore with greater river erosion. The depth of the dissection aims to measure the erosive capacity or activity of rivers vertically, as it analyzes the areas where river erosion has been more (or less) intense over time and provides an indirect relationship of the parameters that allow the dissection to increase, such as lithology, terrain inclination, precipitation and substrate weakness planes. The relief energy determines the maximum difference of the relative height in meters in a specific area and represents the potential energy that emerges from the relief. The total erosion determines zones with greater or less erosion of the recorded relief by means of the density of the curves of level in a determined area (by minimum spatial unit of analysis). All these parameters were analyzed from the three morphological regions that make up the study area (Poás volcanic complex, pyroclastic ramps and valley slopes), and then integrate these variables into the slope susceptibility map. Subsequently, the results of the map of susceptibility to hillside processes were compared with the coseismic mass movements of 2009, which resulted in that 98% of these phenomena coincided with the areas of frequent occurrence and maximum occurrence. In addition, the rupture surfaces of the gravitational processes of 2009 were used to validate this model with a real seismic event, giving 78% of prediction. It is possible to affirm that the model showed a very good performance to predict coseismic slope movements despite the fact that the model does not use any seismic parameters. It would then be expected that their verification with slope movements induced by extreme weather events would be equally acceptable. In view of the obtained results, it can be affirmed that the greatest virtue of the morphometric model is the use of easily obtained morphometric parameters from two fundamental variables: the hydrographic network and the elevation contours. It is for these reasons that the method can be applied in the territories of poor countries, by virtue of the provision of this base information. However, the limitation of the model is on the scale of the data sources and the size of the analysis cells that compose the grid of the study area. Finally, this model could be replicated in other regions or countries as a basic input for decision making in disaster risk management and land use planning.