Ana-Gabriela Núñez, Sebastián Cedillo, Andrés Alvarado Martínez, & Ma Carmen Penadés. (2020). Towards the Building of a Resilient City able to Face Flood Risk Scenarios. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 593–601). Blacksburg, VA (USA): Virginia Tech.
Abstract: Despite the efforts that have been made to inform the community about the possible environmental risks, there is still a general lack of information. Currently, we are working on a flood risk scenario focused on a proposal towards a resilient culture together with the support of Information Technologies (IT) as a way to manage information. The goal is twofold: (i) on the one hand, to manage data in a small scenario to analyze and process the data collected from sensors in different sites in a micro-basin. Data get from data processing such as flow and velocity will then be the input data for hydraulic models to predict floods downstream; (ii) on the other hand, to publicize the predictions and the data already processed means people can benefit from information on flood risks, and the different participants may change their perception and consider cooperating in improving resilience.
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Tom Ritchey. (2006). Modeling multi-hazard disaster reduction strategies with computer-Aided morphological analysis. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 339–346). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: Disaster Risk Management (DRM) is a multi-dimensional problem complex requiring knowledge and experience from a wide range of disciplines. It also requires a methodology which can collate and organize this knowledge in an effective, transparent manner. Towards this end, seven specialists from the social, natural and engineering sciences collaborated in a facilitated workshop in order to develop a prototype multi-hazard disaster reduction model. The model, developed with computer-Aided morphological analysis (MA), makes it possible to identify and compare risk reduction strategies, and preparedness and mitigation measures, for different types of hazards. Due to time constraints, the model is neither complete nor accurate-but only represents a proof-of-principle. The workshop was sponsored by the Earthquake Disaster Mitigation Research Center (EDM) in Kobe, in January, 2005.
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