Impact of SWMM Catchment Discretization: Case Study in Syracuse, New York

Abstract

This study examined how the level of catchment discretization influenced the model parameterization and output uncertainty of the Storm Water Management Model (SWMM) 5.0. Two catchment delineations for a highly urbanized sewershed in Syracuse, New York were developed: (1) the macroscale model containing a minimum required number of subcatchments to retain the original sewer network properties; and (2) the microscale model in which each subcatchment was defined for a unique soil and land-use combination. For both scales, the model parameters were calibrated and the uncertainty of model outputs was quantified using the generalized likelihood uncertainty estimation (GLUE) methodology. Then, calibrated posterior parameter sets were applied at micro- and macroscales individually to a second sewershed, which was also delineated at both micro- and macroscales, to test observed versus simulated flows. The results indicated that the catchment disaggregation level had a great impact on both parameterization and simulation results, and the majority of the parameters were sensitive to the modeling scales. Overall, the posterior parameters calibrated based on the microdelineation resulted in a higher degree of reduction in output uncertainties for both calibrated and validated sewersheds. Hence, it can be argued that the calibrated parameters obtained, based upon the macrodelineation, would result in reduced confidence in simulated runoff for another site unique in its characteristics, whereas the posterior parameters derived from the microdelineation could provide a higher confidence level in terms of parameter transferability for modeling other, particularly ungauged sites.