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This content will become publicly available on January 1, 2026

Title: Evaluating SWMM Modeling Performance for Rapid Flows on Tunnels with Geometric Discontinuities
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.  more » « less
Award ID(s):
2048607
PAR ID:
10636809
Author(s) / Creator(s):
; ; ; ; ;
Publisher / Repository:
American Society of Civil Engineers
Date Published:
Journal Name:
Journal of Hydraulic Engineering
Volume:
151
Issue:
1
ISSN:
0733-9429
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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