DEVELOPMENT OF A PREDICTIVE MODEL FOR TASTE AND ODOR EPISODES IN REGIONAL DRINKING WATER RESERVOIRS
The water utilities regularly collect water samples for characterization and regulation and agreed to collect additional samples to deliver to our research lab for further analysis. The samples were filtered for DNA extraction, so that qPCR and ion chromatography could be performed to examine the amount of geosmin synthase present, along with key anions in the water samples. This data was then entered into R Studio to develop a classification and regression tree (CART) model for predictive purposes. CART modeling gives an output that is a nonlinear decision tree, which was chosen due to the ability to show the nonlinear behavior of most aquatic systems.
Though the dataset is not complete, preliminary data has been entered into the software to run CART models for each utility with the water variables found. Our lab has confidence that these predictive models will have the power to allow utilities time to prepare responses to the compounds in the taste and odor episodes to prevent distrust from the public. In the coming months, a comprehensive dataset will be entered into the software and statistical measures will be evaluated to determine the fit of the model for each utility. Once these models are complete, manuscripts will be put together and can be used by the utilities along with the academic community in the future.