Interdependent infrastructures and multi-mode attacks and failures: improving the security of urban water systems and fire response

This dissertation examines the interdependence between urban water distribution systems and urban fire response. The focus on interdependent critical infrastructures is driven by concern for security of water systems and the effects on related infrastructures if water distribution systems are damaged by terrorist attack or natural disaster. A model of interdependent infrastructures (principally water distribution systems and fire response) is developed called the Model of Urban Fire Spread (MUFS). The model includes the capacity to simulate firefighting water demands in a community water system hydraulic model, building-to-building urban fire spread, and suppression activities. MUFS is an improvement over previous similar models because it allows simulation of urban fires at the level of individual buildings and it permits simulation of interdependent infrastructures working in concert. MUFS is used to simulate a series of multi-mode attacks and failures (MMAFs) ? events which disable the water distribution system and simultaneously ignite an urban fire. The consequences of MMAF scenarios are analyzed to determine the most serious modes of infrastructure failure and urban fire ignition. Various methods to determine worst-case configurations of urban fire ignition points are also examined. These MMAF scenarios are used to inform the design of potential mitigation measures to decrease the consequences of the urban fire. The effectiveness of mitigation methods is determined using the MUFS simulation tool. Novel metrics are developed to quantify the effectiveness of the mitigation methods from the time-series development of their consequences. A cost-benefit analysis of the various mitigation measures is conducted to provide additional insight into the methods? effectiveness and better inform the decision-making process of selecting mitigation methods. Planned future work includes further refinement of the representation of fire propagation and suppression in MUFS and investigation of historical MMAF events to validate simulation predictions. Future efforts will continue development of appropriate optimization methods for determining worst-case MMAF scenarios. This work should be of interest to water utility managers and emergency planners, who can adapt the methodology to analyze their communities? vulnerability to MMAFs and design mitigation techniques to meet their unique needs, as well as to researchers interested in infrastructure modeling and disaster simulation.