During a chemical, biological, or radiological (CBR) event, there is an immediate need for information on the transport of the agent so that evacuation and containment protocols can be executed. Real-time plume evolution had previously been tracked through either physical detection of the plume by embedded sensors or by predictions made using simplified computational models. In order to leverage the positive attributes of these two approaches, a project was initiated to interface, for the first time, real-time sensor data with a nomograph-based, user-friendly software called CT-Analyst to provide full hindcasting capabilities. As part of this effort, this thesis was charged with coordinating the field validations of this integrated system, including correlating field and model-predicted concentrations, developing sampling and release protocols by projecting the rate at which the plume will move through demonstration sites, and assessing and processing the wind field data used to drive the computational model.