Rehabitar la Montaña: strategies and processes for sustainable communities in the mountainous periphery of Medellín
Thousands of poor, marginal communities’ residents die due to landslide events every year. The quick urbanization of mountainous areas, combined with an increased frequency of landslide events induced by heavy rains due to climate change, is leading to increased deaths year after year, and the problem will only get worse. Landscape Architects, trained to analyze and intervene in situations with complex natural and social territorial dynamics, are in position to make positive contributions to mitigating risks in such situations. A collaborative effort between a team of landscape architects from Germany and Urbanists in Medellin Colombia is carrying out a four-phased research and implementation proposal to anticipate and mitigate risk in low-income settlements on Medellin's urban periphery. They propose five pilot projects to test risk mitigation strategies through monitoring and early warning systems, drainage improvements, urban agriculture, slope forestation, and developing sites with the supplied services.
A mathematical approach for assessing landslide vulnerability
A natural phenomenon (hazard) may be characterized in terms of temporal, spatial and magnitude probabilities. The effects of the interaction between the hazard and the exposed element depend on the intensity of the hazard and on the resistance, sometimes called susceptibility, of the element at risk, which describes the propensity of a building or other infrastructure to suffer damage from a specific hazard impact. Consequently, a modern concept of vulnerability must consider the intensity of the hazard as well as the structural resistance of the exposed infrastructure. This concept is referred to as physical vulnerability, and the most accepted definition is a representation of the expected degree of loss quantified on a scale of 0 (no damage) to 1 (total destruction). Thus, this work presents a mathematical model for landslide physical vulnerability assessment, here named the T-Model, based on the “Principle of Natural Proportionality” and calibrated with field observations of the massive rainfall-triggered landslide event that occurred in Nova Friburgo, Brazil in November of 2011. The model was also calibrated for a flow-type movement that is based on field observations of the failure of a tailing dam that affected the district of Bento Rodrigues, Brazil in November of 2015. The results showed a good agreement between predictions and the observed level of damages. Thus, it is possible to conclude that from a mathematical point of view, the model may be qualified as universal. It is recognized that a real universal objective model for vulnerability to landslides is not practical at present. More important than the model itself is the methodology that is presented here, which leads the user to take qualitative damage information from the field and develop it into a quantitative mathematical framework. Potential users of the T-Model must be cautious regarding the values of parameters that are presented in this paper. The T-Model is just a modest proposal that requires further calibration and deep expert criticisms.
Velocity moments in alongshore bottom stress parameterizations
The time-averaged alongshore bottom stress is an important component of nearshore circulation models. In a widely accepted formulation the bottom stress is proportional to , the time average of the product of the instantaneous velocity magnitude |u→| and the instantaneous alongshore velocity component υ. Both mean and fluctuating (owing to random, directionally spread waves) velocities contribute to . Direct estimation of requires a more detailed specification of the velocity field than is usually available, so the term is parameterized. Here direct estimates of based on time series of near-bottom currents observed between the shoreline and 8-m water depth are used to test the accuracy of parameterizations. Common parameterizations that are linear in the mean alongshore current significantly underestimate for moderately strong alongshore currents, resulting in overestimation of a drag coefficient determined by fitting modeled (with a linearized bottom stress) to observed alongshore currents. A parameterization based on a joint-Gaussian velocity field with the observed velocity statistics gives excellent overall agreement with the directly estimated and allows analytic investigation of the statistical properties of the velocity field that govern . Except for the weakest flows, depends strongly on the mean alongshore current and the total velocity variance but depends only weakly on the mean wave angle, wave directional spread, and mean cross-shore current. Several other nonlinear parameterizations of are shown to be more accurate than the linear parameterizations and are adequate for many modeling purposes.