Analyzing The Effluent For A Municipal Water Supplier: A Comparison Of The Periodicity Of The Time Series Data Forecasting Techniques

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Published by Franklin Publishing Company in Franklin Business and Law Journal, volume 2013 issue 2, 2013. Bryant users may access this article here.


Franklin Publishing Company

Publication Source

Franklin Business and Law Journal


The authors obtained effluent (clean water output) data from the Providence Water Supply Board (PWSB) as well as meteorological data for an 11 year period. It was our goal to create a forecasting model for the effluent or discharge for future periods. In addition, we discovered a strong relationship between maximum daily temperature and the amount of effluent, as might be expected. However, we also noted that the relationship was somewhat curvilinear. We further examined the data with a time series graph, an autocorrelation plot, and a partial autocorrelation plot. Ultimately, we wanted to compare linear regression and Autoregressive Integrated Moving Average (ARIMA) modeling as predictive models for effluent data. We also wanted to identify the best predictive periodicity that would fit the water data.