Estimación de pérdidas económicas directas provocadas por inundación. Aplicación de las curvas inundación-daños en países en desarrollo

Las inundaciones son los desastres causados por fenómenos naturales que más daños provocan a diferentes sectores, como son los de la vivienda, comercial, agrícola, turístico e industrial. Este último es un sector que sufre importantes daños, pero que no ha sido estudiado ya que se le consideraba como poco vulnerable y con capacidad de adaptación ante desastres naturales. La implementación de una metodología para calcular los daños directos tangibles en función de la altura de lámina de agua alcanzada vs daños económicos, permite tener estimaciones de las pérdidas económicas causadas por inundaciones. Este trabajo muestra el estado del arte e identifica las investigaciones referentes al cálculo de daños provocados por inundación y su aplicación en países en desarrollo como lo es México.

Elaboración de un mapa de inventario de inestabilidades de los taludes del Polígono Industrial Santiago Payá (Alcoy, Alicante)

Los mapas de inventario de movimientos de ladera se realizan durante las primeras etapas de investigación de los procesos de inestabilidad de laderas y de zonas inestables. Estos mapas resultan de gran utilidad dado que facilitan las tareas de prevención y el análisis de estabilidad. En el presente trabajo se muestra la metodología seguida para elaborar un mapa de inventario de movimientos de ladera en el Polígono Industrial de Santiago Payá situado en el término municipal de Alcoy (Alicante) así como la cartografía resultante.

An evolutionary approach to the delineation of functional areas based on travel-to-work flows

This paper presents a new approach to the delineation of local labor markets based on evolutionary computation. The aim of the exercise is the division of a given territory into functional regions based on travel-to-work flows. Such regions are defined so that a high degree of inter-regional separation and of intra-regional integration in both cases in terms of commuting flows is guaranteed. Additional requirements include the absence of overlap between delineated regions and the exhaustive coverage of the whole territory. The procedure is based on the maximization of a fitness function that measures aggregate intra-region interaction under constraints of inter-region separation and minimum size. In the experimentation stage, two variations of the fitness function are used, and the process is also applied as a final stage for the optimization of the results from one of the most successful existing methods, which are used by the British authorities for the delineation of travel-to-work areas (TTWAs). The empirical exercise is conducted using real data for a sufficiently large territory that is considered to be representative given the density and variety of travel-to-work patterns that it embraces. The paper includes the quantitative comparison with alternative traditional methods, the assessment of the performance of the set of operators which has been specifically designed to handle the regionalization problem and the evaluation of the convergence process. The robustness of the solutions, something crucial in a research and policy-making context, is also discussed in the paper.

Grouping genetic operators for the delineation of functional areas based on spatial interaction

The delineation of functional economic areas, or market areas, is a problem of high practical relevance, since the delineation of functional sets such as economic areas in the US, Travel-to-Work Areas in the United Kingdom, and their counterparts in other OECD countries are the basis of many statistical operations and policy making decisions at local level. This is a combinatorial optimisation problem defined as the partition of a given set of indivisible spatial units (covering a territory) into regions characterised by being (a) self-contained and (b) cohesive, in terms of spatial interaction data (flows, relationships). Usually, each region must reach a minimum size and self-containment level, and must be continuous. Although these optimisation problems have been typically solved through greedy methods, a recent strand of the literature in this field has been concerned with the use of evolutionary algorithms with ad hoc operators. Although these algorithms have proved to be successful in improving the results of some of the more widely applied official procedures, they are so time consuming that cannot be applied directly to solve real-world problems. In this paper we propose a new set of group-based mutation operators, featuring general operations over disjoint groups, tailored to ensure that all the constraints are respected during the operation to improve efficiency. A comparative analysis of our results with those from previous approaches shows that the proposed algorithm systematically improves them in terms of both quality and processing time, something of crucial relevance since it allows dealing with most large, real-world problems in reasonable time.