Risk-based methodology for parameter calibration of a reservoir flood control model

Flash floods are of major relevance in natural disaster management in the Mediterranean region. In many cases, the damaging effects of flash floods can be mitigated by adequate management of flood control reservoirs. This requires the development of suitable models for optimal operation of reservoirs. A probabilistic methodology for calibrating the parameters of a reservoir flood control model (RFCM) that takes into account the stochastic variability of flood events is presented. This study addresses the crucial problem of operating reservoirs during flood events, considering downstream river damages and dam failure risk as conflicting operation criteria. These two criteria are aggregated into a single objective of total expected damages from both the maximum released flows and stored volumes (overall risk index). For each selected parameter set the RFCM is run under a wide range of hydrologic loads (determined through Monte Carlo simulation). The optimal parameter set is obtained through the overall risk index (balanced solution) and then compared with other solutions of the Pareto front. The proposed methodology is implemented at three different reservoirs in the southeast of Spain. The results obtained show that the balanced solution offers a good compromise between the two main objectives of reservoir flood control management

Análisis de la eficiencia de los sistemas de colonias de hormigas para problemas de accesibilidad

A pesar de los avances en materia de predicción, los desastres naturales siguen teniendo consecuencias devastadoras. Entre los principales problemas a los que se enfrentan los equipos de ayuda y rescate después de un desastre natural o provocado por el hombre se encuentra la planificación de las tareas de reparación de carreteras para conseguir la máxima ventaja de los limitados recursos económicos y humanos. En la presente Tesis Fin de Máster se intenta dar solución al problema de la accesibilidad, es decir, maximizar el número de supervivientes que consiguen alcanzar el centro regional más cercano en un tiempo mínimo mediante la planificación de qué carreteras rurales deberían ser reparadas dados unos recursos económicos y humanos limitados. Como se puede observar, es un problema combinatorio ya que el número de planes de reparación y conexiones entre las ciudades y los centros regionales crece de forma exponencial con el tamaño del problema. Para la resolución del problema se comienza analizando una adaptación básica de los sistemas de colonias de hormigas propuesta por otro autor y se proponen múltiples mejoras sobre la misma. Posteriormente, se propone una nueva adaptación más avanzada de los sistemas de colonias de hormiga al problema, el ACS con doble hormiga. Este sistema hace uso de dos tipos distintos de hormigas, la exploradora y la trabajadora, para resolver simultáneamente el problema de encontrar los caminos más rápidos desde cada ciudad a su centro regional más cercano (exploradora), y el de obtener el plan óptimo de reparación que maximice la accesibilidad de la red (trabajadora). El algoritmo propuesto se ilustra por medio de un ejemplo de gran tamaño que simula el desastre natural ocurrido en Haití, y su rendimiento es comparado con la combinación de dos metaheurísticas, GRASP y VNS.---ABSTRACT---In spite of the advances in forecasting, natural disaster continue to ocasionate devastating consequences. One of the main problems relief teams face after a natural or man-made disaster is how to plan rural road repair work to take maximum advantage of the limited available financial and human resources. In this Master´s Final Project we account for the accesability issue, that is, to maximize the number of survivors that reach the nearest regional center in a minimum time by planning whic rural roads should be repaired given the limited financial and human resources. This is a combinatorial problem since the number of possible repairing solutions and connections between cities and regional centers grows exponentially with the size of the problem. In order to solve the problem, we analyze the basic ant colony system adaptation proposed by another author and point out multiple improvements on it. Then, we propose a novel and more advance adaptation of the ant colony systems to the problem, the double- ant ACS. This system makes use of two diferent type of ants, the explorer and the worker, to simultaneously solve the problem of finding the shorthest paths from each city to their nearest regional center (explorer), and the problem of identifying the optimal repairing plan that maximize the network accesability (worker). The proposed algorithm is illustrated by means of a big size example that simulates the natural disaster occurred in Haiti, and its performance is compared with a combination of two metaheuristics, GRASP and VNS.

Arquitectura para volver a vivir

This article describes how architecture can help communities to recover themselves after the strike of a natural disaster. Este artículo describe cómo la arquitectura puede ayudar a las comunidades a recuperarse después de un desastre natural.

An Ant Colony System adaptation to deal with accessibility issues after a disaster

One of the main problems relief teams face after a natural or man-made disaster is how to plan rural road repair work tasks to take maximum advantage of the limited available financial and human resources. Previous research focused on speeding up repair work or on selecting the location of health centers to minimize transport times for injured citizens. In spite of the good results, this research does not take into account another key factor: survivor accessibility to resources. In this paper we account for the accessibility issue, that is, we maximize the number of survivors that reach the nearest regional center (cities where economic and social activity is concentrated) in a minimum time by planning which rural roads should be repaired given the available financial and human resources. This is a combinatorial problem since the number of connections between cities and regional centers grows exponentially with the problem size, and exact methods are no good for achieving an optimum solution. In order to solve the problem we propose using an Ant Colony System adaptation, which is based on ants? foraging behavior. Ants stochastically build minimal paths to regional centers and decide if damaged roads are repaired on the basis of pheromone levels, accessibility heuristic information and the available budget. The proposed algorithm is illustrated by means of an example regarding the 2010 Haiti earthquake, and its performance is compared with another metaheuristic, GRASP.