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Urban expansion and the increasing frequency and intensity of extreme precipitation events bring new challenges to stormwater collection systems. One underrecognized issue is the occurrence of transient flow conditions that lead to adverse multiphase flow interactions (AMFI): essentially, the formation, collapse, and uncontrolled release of air pockets within stormwater system flows. While the fundamental physics of AMFI have been evaluated in laboratory experiments and idealized modeling studies, much less is known about their development in real or simulated stormwater networks, and about the roles played by rainfall and network properties. A necessary precursor to AMFI is the development of pressurized flow conditions within a network. The goal of this study is to understand how spatiotemporal rainfall variability affects the occurrence of pressurized conditions in a stormwater drainage network in the Richmond district of San Francisco, California. High-resolution bias-corrected radar rainfall fields for 24 recent storms were used as the independent variable of EPA-SWMM simulations. Model analyses indicate that the incidence of pressurized flow increases with storm intensity and is more sensitive to rainfall temporal variability than spatial variability. This research provides a reference for analyzing AMFI precursors in other networks and may have important implications for the improvement of stormwater infrastructures. 

The EPA’s StormWater Management Model (SWMM) has been applied across the globe for citywide stormwater modeling due to its robustness and versatility. Recent research indicated that SWMM, with proper setup, can be applied in the description of more dynamic flow conditions, such as rapid inflow conditions. However, stormwater systems often have geometric discontinuities that can pose challenges to SWMM model accuracy, and this issue is poorly explored in the current literature. The present work evaluates the performance of SWMM 5 in the context of a real-world stormwater tunnel with a geometric discontinuity. Various combinations of spatiotemporal discretization are systematically evaluated along with four pressurization algorithms, and results are benchmarked with another hydraulic model using tunnel inflow simulations. Results indicated that the pressurization algorithm has an important effect on SWMM’s accuracy in conditions of sudden diameter changes. From the tested pressurization algorithms, the original Preissmann slot algorithm was the option that yielded more representative results for a wider range of spatiotemporal discretizations. Regarding spatiotemporal discretization options, intermediate discretization, and time steps that lead to Courant numbers equal to one performed best. Interestingly, the traditional SWMM’s link-node approach also presented numerical instabilities despite having low continuity errors. Results indicated that although SWMM can be effective in simulating rapid inflow conditions in tunnels, situations with drastic geometric changes need to be carefully evaluated so that modeling results are representative.