Identification of reactive contaminant sources in a water distribution system under the conditions of data uncertainties

Water distribution systems are designed for fast and efficient transport of the drinking water and mixing of chlorine to maintain the required disinfectant levels in the system. Thus, any contaminant if injected in the system would also spread quickly through the network and can have serious impact on public health if consumed. Contaminant injected during any intentional contamination event can be chemical or biological, the nature of which may remain unknown. Practically it's not possible to monitor any system for the presence of all possible chemical or biological contaminants. However, the distribution systems are routinely monitored for several water quality parameters like chlorine, pH, etc. Any contaminant injected in the system would react with water and chlorine leading to the increased degradation of the chlorine levels in the system. In our past work we developed methodology to use routine chlorine measurements as a surrogate to identify a contamination event in a WDS. An evolutionary algorithm based approach simulation-optimization was developed to identify the contaminant source characteristics (i.e., location of the contaminant source, time of start of injection and injection pattern) during a contamination event under conditions of uncertainty about the reaction kinetics of the contaminant in the system. The investigation was extended to study the source characterization problem under different uncertain reaction conditions. We present here a detailed analysis of source characterization problem for the reactive contaminants and the simulation-optimization methodology developed. Case studies carried out on a number of water distributions systems will be reported.