A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Stormwater Detention System Parameter Sensitivity and Uncertainty Analysis Using SWMM
A U.S. EPA (EPA) model was developed for the Cathedral Run stormwater wetland (Philadelphia, Pennsylvania). This research presents a formal sensitivity analysis of hydraulic and hydrologic model parameters contributing uncertainty with the multiobjective generalized sensitivity analysis (MOGSA) algorithm. The parameters identified as significant include: percent routed (), subcatchment soils, subcatchment width, wetland soils, and the flood weir coefficient. These results suggest that this model is well parameterized for detailed simulations of stormwater control installations, and contests the existence of a globally sensitive set of parameters. This research demonstrates that detailed models of stormwater control installations are significantly affected by uncertainty related to parameters beyond traditional calibration (i.e., runoff generation) parameters. The authors present a monitoring design based on wetland water surface elevation. The simplified monitoring scheme obtained statistically significant calibration data as determined through MOGSA. The generalized likelihood uncertainty estimation (GLUE) algorithm was then applied to develop marginal posterior model parameter distributions and two-dimensional (2D) probability spaces using a formal Bayesian likelihood function. The GLUE results demonstrate the importance of uncertainty and equifinality within the context of stormwater wetland modeling.
Stormwater Detention System Parameter Sensitivity and Uncertainty Analysis Using SWMM
A U.S. EPA (EPA) model was developed for the Cathedral Run stormwater wetland (Philadelphia, Pennsylvania). This research presents a formal sensitivity analysis of hydraulic and hydrologic model parameters contributing uncertainty with the multiobjective generalized sensitivity analysis (MOGSA) algorithm. The parameters identified as significant include: percent routed (), subcatchment soils, subcatchment width, wetland soils, and the flood weir coefficient. These results suggest that this model is well parameterized for detailed simulations of stormwater control installations, and contests the existence of a globally sensitive set of parameters. This research demonstrates that detailed models of stormwater control installations are significantly affected by uncertainty related to parameters beyond traditional calibration (i.e., runoff generation) parameters. The authors present a monitoring design based on wetland water surface elevation. The simplified monitoring scheme obtained statistically significant calibration data as determined through MOGSA. The generalized likelihood uncertainty estimation (GLUE) algorithm was then applied to develop marginal posterior model parameter distributions and two-dimensional (2D) probability spaces using a formal Bayesian likelihood function. The GLUE results demonstrate the importance of uncertainty and equifinality within the context of stormwater wetland modeling.
Stormwater Detention System Parameter Sensitivity and Uncertainty Analysis Using SWMM
Knighton, James (author) / Lennon, Edward (author) / Bastidas, Luis (author) / White, Eric (author)
2016-03-28
Article (Journal)
Electronic Resource
Unknown
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