Using SWMM for emergency response planning: A case study evaluating biological agent transport under various rainfall scenarios and urban surfaces
Journal Article
·
· Journal of Hazardous Materials
- US Environmental Protection Agency (EPA), Durham, NC (United States). Office of Research and Development
- Argonne National Laboratory (ANL), Argonne, IL (United States)
To assist in emergency preparedness for a biological agent terrorist attack or accidental pathogen release, potential contaminant levels and migration pathways of spores spread by urban stormwater were evaluated using a Storm Water Management Model (SWMM) of U.S. Coast Guard Base Elizabeth City, North Carolina. The high temporal-spatial resolution SWMM model was built using spore concentrations in stormwater runoff from asphalt, grass, and concrete collected from a point-scale field study. The subsequent modeled contamination scenarios included a notional plume release and point releases mimicking the field study under three rainfall conditions. The rainfall scenarios included a 6-hour natural rainfall event on Dec. 8, 2021 and two design storms (2-year and 100-year events). The observed spore concentrations from asphalt and concrete from the actual field experiment were applied to calibrate the washoff parameters in the SWMM model, using an exponential washoff function. The calibrated washoff coefficient (c1) and exponent (c2) were 0.01 and 1.00 for asphalt, 0.05 and 1.45 for grass, and 2.45 and 1.00 for concrete, respectively. The calibrated SWMM model simulated spore concentrations in runoff at times and magnitudes similar to the field study data. In the point release modeled scenario, the concrete surface generated 55.6% higher average spore concentrations than asphalt. Similarly, in the field experiment, a 175% (p < 0.05) higher average spore concentration in surface runoff was observed from concrete than from asphalt. Here, this study demonstrates how SWMM may be used to evaluate spore washoff from urban surfaces under different precipitation amounts, intensities, and durations, and how visualized spatial migration pathways in stormwater runoff may be used for emergency planning and remediation.
- Research Organization:
- Argonne National Laboratory (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- US Department of Homeland Security (DHS); USDOE; USEPA
- Grant/Contract Number:
- AC02-06CH11357
- OSTI ID:
- 2427997
- Journal Information:
- Journal of Hazardous Materials, Journal Name: Journal of Hazardous Materials Vol. 458; ISSN 0304-3894
- Publisher:
- ElsevierCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Similar Records
Knowledge techniques for the analysis of urban runoff using SWMM
Bayes_Opt-SWMM: A Gaussian process-based Bayesian optimization tool for real-time flood modeling with SWMM
Storm water modeling at Lawrence Livermore National Laboratory
Thesis/Dissertation
·
Thu Dec 31 23:00:00 EST 1987
·
OSTI ID:6969363
Bayes_Opt-SWMM: A Gaussian process-based Bayesian optimization tool for real-time flood modeling with SWMM
Journal Article
·
Tue Jun 18 20:00:00 EDT 2024
· Environmental Modelling and Software
·
OSTI ID:2378088
Storm water modeling at Lawrence Livermore National Laboratory
Technical Report
·
Wed May 01 00:00:00 EDT 1996
·
OSTI ID:576768