Vulnerability assessment of water supply systems for insufficient fire flows

Water supply systems’ vulnerability towards physical, chemical, biological, and cyber threats was recognized and was under study long before September 11, 2001. But greater attention toward security measures for water supply systems was focused after the incidents of September 11, 2001. In response to those events, several acts have been passed by the United States Congress, and numerous vulnerability assessment tools and methodologies for water systems have been developed. Although water supply systems are vulnerable to many forms of terrorist acts, most of the vulnerability analysis studies on these systems have been for chemical and biological threats. Because of the interdependency of water supply infrastructure and emergency fire response, any substantial damage in a water system would be a significant threat towards the community. In this study, attention is focused toward physical threats on water supply systems during a fire flow condition, and a methodology is developed to determine the vulnerable components of a water supply system during a fire event. The methodology utilizes dynamic programming optimization procedure to determine maximized disruption of fire flows as a function of number of attacks and/or failures in the water distribution system. Disruption is quantified at specific fire hydrants in two schemes using normalized values of (1) available flow and (2) available pressure and distance to the nearest operational fire hydrant. It is found that the pressure-based quantity is inferior to the flow-based one. However, using the flow-based disruption metric, clear functions of disruption versus failure number can be determined that exhibit discernable properties of robustness and resiliency – and the sequential failures in each. This methodology is applied to the water supply system of Micropolis, a virtual city developed by Brumbelow et al. (2005), and vulnerability analysis is performed with fire at several possible locations. On the basis of the results, three mitigation strategies are proposed to harden specific sets of water mains and more simulations are performed on the hardened water supply system to assess its changed vulnerability. The results from the simulations of the mitigation strategies show that the recommendations on specific mitigation measures reduce the serious consequences from such threats

A Risk-based Optimization Modeling Framework for Mitigating Fire Events for Water and Fire Response Infrastructures

The purpose of this dissertation is to address risk and consequences of and effective mitigation strategies for urban fire events involving two critical infrastructures- water distribution and emergency services. Water systems have been identified as one of the United States' critical infrastructures and are vulnerable to various threats caused by natural disasters or malevolent actions. The primary goals of urban water distribution systems are reliable delivery of water during normal and emergency conditions (such as fires), ensuring this water is of acceptable quality, and accomplishing these tasks in a cost-effective manner. Due to interdependency of water systems with other critical infrastructures-e.g., energy, public health, and emergency services (including fire response)- water systems planning and management offers numerous challenges to water utilities and affiliated decision makers. The dissertation is divided into three major sections, each of which presents and demonstrates a methodological innovation applied to the above problem. First, a risk based dynamic programming modeling approach is developed to identify the critical components of a water distribution system during fire events under three failure scenarios: (1) accidental failure due to soil-pipe interaction, (2) accidental failure due to a seismic activity, and (3) intentional failure or malevolent attack. Second, a novel evolutionary computation based multi-objective optimization technique, Non-dominated Sorting Evolution Strategy (NSES), is developed for systematic generation of optimal mitigation strategies for urban fire events for water distribution systems with three competing objectives: (1) minimizing fire damages, (2) minimizing water quality deficiencies, and (3) minimizing the cost of mitigation. Third, a stochastic modeling approach is developed to assess urban fire risk for the coupled water distribution and fire response systems that includes probabilistic expressions for building ignition, WDS failure, and wind direction. Urban fire consequences are evaluated in terms of number of people displaced and cost of property damage. To reduce the assessed urban fire risk, the NSES multi-objective approach is utilized to generate Pareto-optimal solutions that express the tradeoff relationship between risk reduction, mitigation cost, and water quality objectives. The new methodologies are demonstrated through successful application to a realistic case study in water systems planning and management