Using TEVA to Assess Impact of Model Skeletonization on Contaminant Consequence Assessment and Sensor Placement Design

Drinking water systems are known to be vulnerable to contamination by toxic substancs, whether the contaminants are introduced intentionally during a terrorist attack, or unintentionally through accidental cross-connections or backflow incidents. Understanding the vulnerability of drinking water distribution systems to contaminant intrusion is currently a major research focus within the federal government and across the water community. The EPA's National Homeland Security Research Center (NHSRC) developed the Threat Ensemble Vulnerability Assessment (TEVA) Research Program to analyze the vulnerability of drinking water distribution systems to contaminant threats and develop a methodology to design Contamination Warning Systems (CWS). The TEVA Research Program, the NHSRC and its collaborators at the University of Cincinnati, Argonne National Laboratory, Sandia National Laboratories developed software that accomplishes this task. The software tool uses quantitative health impacts data from probabilistic or exhaustive consequence assessments to optimally locate and evaluate CWS designs for a drinking water distribution system. Both the characterization of the potential impacts from contaminant attacks and the designing of CWS rely on calibrated hydraulic models developed by the water community for modeling and simulating contaminant transport. Distribution system models, however, vary widely in detail and, therefore, their representation of the actual system also varies. A complete representation of the distribution system model, especially given any large or even medium-sized city, can be enormously complex and very difficult to model. As a result, "skeletonization" is the process most often used to select the most significant attributes of the hydraulic network that accurately represent the behavior of the system. The underlying assumption is that those portions of the network that are not modeled are accounted for within the parts of the system that are represented by the model. The level of detail of a distribution system model can be described by the number of junctions and pipes in the model as compared to their numbers in the actual system that the model represents. The TEVA model for assessing the spatial and temporal distribution of health impacts in a distribution system has been previously described. Furthermore, the strategic placement of sensors in a distribution system to monitor water quality as part of a CWS has been well studied and described. The purpose of this paper is to evaluate the effects that varying levels of model detail have on estimating potential health impacts from an intentional contamination event, on a water system community. Additionally, the performance of sensor monitoring designs developed for six skeletonized models are compared to designs developed for an "all-pipes-model". Mean and maximum, or worst case, health impacts for each of the sensor designs from the skeletonized models are compared to the performance of the sensor designs developed for the "all-pipes-model". Given that most distribution systems are represented by models that are skeletonized to some degree, this paper examines the effectiveness of sensor designs developed for skeletonized models to protect public health.