Integrating CIP/DSS with EPANET and GIS to determine health, economic & worried well impacts from chemical/biological contaminants released into a public water distribution system

The water infrastructure systems of major cities in the United States are all potentially vulnerable to attack or accidental contamination from a biological or chemical toxin. To protect against such an attack or accidental contamination, academic and government research has looked for better ways to secure the water infrastructure.;Methods used include computerized simulations to model the spread of biological or chemical contaminants through a water distribution system. Developed a methodology for determining local and external worker population at each node to better understand those who would be exposed for 24hrs (local) and those exposed between 9am-5pm (external workers). Simulations of a direct attack by a knowledgeable adversary on the Dallas Water Utility (DWU) water distribution system with chemical or biological materials could result in over 30,000 deaths and 61,000 injured based on a worst case scenario. Armed with this information, government and local officials are made aware of potential dangers and can aid in the prevention of such an event and plan the process of response if an event does occur. Although much progress has been made, not addressed by research to date is the issue of infrastructure interdependencies. Critical infrastructures such as the hospital and economic sectors are closely inter-connected to the water infrastructure, therefore if the water sector is affected, the other infrastructures will be affected as well.;When integrated with EPANET and GIS, CIP/DSS highlights the direct and indirect effects the water infrastructure has on other infrastructures. CIP/DSS provides needed insight into the interconnection between infrastructures during a contamination event within a large water utility. The health and economic sectors are particularly affected during simulated contamination events causing great disruption in the day to day activities of these two sectors. The "worried well effect" describing an increase in the healthy seeking medical attention caused by the threat of contamination was also modeled showing its potential for major disruption to the hospital and economic sectors. Finally, the use of an Early Warning Systems (EWS) was also simulated showing a marked decrease in deaths and injuries compared to simulations without an EWS and further strengthening the argument for an EWS in all major water distribution systems.