Modelling Impact of Extreme Rainfall on Sanitary Sewer System by Predicting Rainfall Derived Infiltration/Inflow

Extreme climate events are becoming more intense in Melbourne in recent years. This increasing intensity of excessive rainfall has an adverse effect on the sewer network by causing sewage overflow hazards. Extreme rainfall events increase flow into the sewer system, both directly (inflow) and through infiltration into sewer. As a result of this Rainfall Derived Infiltration and Inflow (RDII), Sanitary Sewer Overflows (SSOs) may occur. These SSOs carry inherent risks to human health as well as lead to environmental pollution. This paper demonstrates a rigorous and efficient procedure of predicting RDII in a sewer system in Melbourne, Australia by using the Sanitary Sewer Overflow Analysis and Planning (SSOAP) toolbox. The SSOAP toolbox is a new freely available tool designed by the U.S. Environmental Protection Agency (EPA) for modeling of RDII. In the SSOAP toolbox, the U.S. EPA Storm Water Management Model (SWMM5) is incorporated for the hydraulic routing of the sanitary sewer system. For RDII flow estimation, SSOAP implements the synthetic unit hydrograph (SUH) method. In the literature, this procedure is recommended as the most accurate and industry standard methodology of determining RDII. The simplest SUH contains three triangular hydrographs to describe the fast, medium, and slow RDII responses. Each hydrograph has total of three parameters named R,T,K. R is the fraction of rainfall volume entering the sewer system as RDII during and immediately after the rainfall event, T is the time to peak, and K is the ratio of the time of recession to T. This method is known as the RTK unit hydrograph curve-fitting analysis. In the SSOAP toolbox, the three main input data used for RDII prediction are flow, rainfall and sewershed data. The SSOAP toolbox analyses rainfall and flow data and identifies dry weather flow (DWF) and wet weather flow (WWF) periods. RDII flow components for storm events are defined by hydrograph decomposition of measured flow data. The tool estimates R, T, K parameters for each rainfall/flow monitoring event and generates RDII hydrographs. This paper provides an in-depth description of RDII analysis using the SSOAP toolbox for a case study catchment in Glenroy suburb It is located within the larger Pascoe Vale catchment in northern Melbourne. It is a residential area. The main reason for choosing this particular area as the case study is that the sanitary sewer pipes are quite old; therefore, the problem of SSOs are common. Three flow meters were used for flow data collection and rainfall data were obtained from the Bureau of Meteorology for a nearby rain gauge station. As the downstream flow meter location is the most critical point (as it receives wastewater flow from the whole catchment), the paper focuses on flow data from the downstream flow meter location for the RDII analysis. Two storm events have been analyzed for calibration of the RDII unit hydrograph parameters (namely, the R,T,K parameters). This paper presents a simple calibration procedure of RTK parameters. The SSOAP toolbox provides automated calibration using a visual approach. The main purpose of this automatic visual calibration is that the simulated RDII flows closely match the RDII time series generated by decomposing the measured flow data. The SSOAP toolbox is shown to be a useful software for RDII analysis, as the simple, interactive and visual approach facilitates easy determination of the R,T,K parameters, rather than use of the complicated numerical techniques used in the past. Moreover, this study demonstrates the accuracy of the generation of R,T,K parameters using this software. As part of future research, these R,T,K parameters or the RDII hydrographs will act as input to a sewer simulation model like SWMM5 for the hydraulic analysis of existing sewer system. This would help in identifying locations which are at risk or prone to SSOs.