Improving real-time monitoring technologies introduces new tasks to the data analyst such as rapid identification of contamination source locations based on the data collected from monitoring stations. In theory, this problem is an ill posed problem which has non-unique solutions due to the irreversible nature of contaminant transformation and transport processes. In this study, we propose a methodology that utilizes a classification routine which associates the observations on a contaminant spill with one or more of the candidate spill locations in the river network. This approach consists of a training step followed by a sequential elimination of the candidate spill locations which lead to the identification of potential spill locations. In this process the training of the monitoring system may require a significant simulation time. However, this is performed only once. The statistical elimination for the ranking of the candidate locations is a rapid process. The proposed methodology is applied to the Altamaha river system in the State of Georgia, USA. The results show that the proposed approach may be effectively used for the preliminary planning of the contaminant source investigation studies in complex river systems.