Rainfall derived infiltration and inflow (RDII) are extraneous water in a sanitary sewer system that are originated from rainfall in a surface runoff form. Most RDII enters sanitary sewer systems through illegal connections or mechanical faults, especially in aged sewer systems. In this study, the physical process of three primary RDII sources: roof downspout, sump pump, and leaky lateral, are investigated using physics-based models. These three sources represent three different flow paths: direct connection of impervious catchments, mixed flow through coarse porous media followed by a direct connection, and percolated flow through compacted soil, respectively. Due to the differences in medium and the flow paths, flow responses of these three RDII sources differ in time and magnitude, and they can be distinctly identified from each other. The typical flow response of each RDII source is represented as an Impulse Response Function (IRF) that is a flow response to a pre-specified representative rainfall computed using physics-based models. The total RDII flow hydrograph is presented as a combination of these three IRFs, and the weighting factors of each IRF is calibrated using a genetic algorithm (GA) technique in a test sewer catchment. The results may shed light on identifying the contributions of different RDII sources in a sewershed and help public water managers to understand the local RDII issues better, which in turn facilitates more effective management of a sewer system.

Rainfall derived infiltration and inflow (RDII) are extraneous water in a sanitary sewer system that are originated from rainfall in a surface runoff form. Most RDII enters sanitary sewer systems through illegal connections or mechanical faults especially in aged sewer systems. In this study, the physical process of three major RDII sources: roof downspout, sump pump, and leaky lateral, are investigated using physics-based models. These three sources represent three different flow paths: direct connection of impervious catchments, mixed flow through course porous media followed by a direct connection, and percolated flow through compacted soil, respectively. Due to the differences in medium and the flow paths, flow responses of these three RDII sources differ in time and magnitude and they can be distinctly identified from each other. The typical flow response of each RDII source is represented as an Impulse Response Function (IRF) that is a flow response to a pre-specified representative rainfall computed using physics-based models. The total RDII flow hydrograph is presented as a combination of these three IRFs and the weighting factors of each IRF is calibrated using a genetic algorithm (GA) technique in a test sewer catchment. The results may shed light on identifying the contributions of different RDII sources in a sewershed and help public water managers to better understand the local RDII issues which in turn facilitates a more effective management of a sewer system.

Rainfall derived infiltration and inflow (RDII) are extraneous water in a sanitary sewer system that are originated from rainfall in a surface runoff form. Most RDII enters sanitary sewer systems through illegal connections or mechanical faults especially in aged sewer systems. In this study, the physical process of three major RDII sources: roof downspout, sump pump, and leaky lateral, are investigated using physics-based models. These three sources represent three different flow paths: direct connection of impervious catchments, mixed flow through course porous media followed by a direct connection, and percolated flow through compacted soil, respectively. Due to the differences in medium and the flow paths, flow responses of these three RDII sources differ in time and magnitude and they can be distinctly identified from each other. The typical flow response of each RDII source is represented as an Impulse Response Function (IRF) that is a flow response to a pre-specified representative rainfall computed using physics-based models. The total RDII flow hydrograph is presented as a combination of these three IRFs and the weighting factors of each IRF is calibrated using a genetic algorithm (GA) technique in a test sewer catchment. The results may shed light on identifying the contributions of different RDII sources in a sewershed and help public water managers to better understand the local RDII issues which in turn facilitates a more effective management of a sewer system.