Impact Evaluation of Wet-Weather Events on Influent Flow and Loadings of a Water Resource Recovery Facility

Since the introduction of environmental legislation and directives in Europe, the impact of combined sewer overflows (CSO) on receiving water bodies has become a priority concern in water and wastewater treatment industry. Time-consuming and expensive local sampling and monitoring campaigns have been carried out to estimate the characteristic flow and pollutant concentrations of CSO water. This study focused on estimating the frequency and duration of wet-weather events and their impacts on influent flow and wastewater characteristics of the largest Italian water resource recovery facility (WRRF) in Castiglione Torinese. Eight years (viz. 2009–2016) of routinely collected influent data in addition to the arithmetic mean daily precipitation rates (PI) of the plant catchment area, were elaborated. Relationships between PI and volumetric influent flow rate (Q_in), chemical oxygen demand (COD), ammonium concentration (N-NH₄) and total suspended solids (TSS) are investigated. Time series data mining (TSDM) method is implemented for segmentation of time series by use of sliding window algorithm to partition the available records associated with wet and dry weather events based on the daily variation of PI time series. Appling the methodology in conjunction with results obtained from data reduction techniques, a wet-weather definition is proposed for the plant. The results confirm that applied methodology on routinely collected plant data can be considered as a good substitute for time-consuming and expensive sampling campaigns and plant monitoring programs usually conducted for accurate emergency response and long-term preparedness for extreme climate conditions.