Calibration of Rainfall-Runoff Model in Urban Watersheds for Stormwater Management Assessment
Publication: Journal of Water Resources Planning and Management
Volume 140, Issue 6
Abstract
Physically based semidistributed rainfall-runoff models are an important tool for assessing decentralized green infrastructure alternatives in controlling combined sewer overflows (CSO). Few studies have analyzed reliable calibration methods of highly detailed rainfall-runoff models at the subcatchment level. This research presents calibration of the storm water management model version 5 (SWMM5) using high temporal resolution rainfall and flow data to perform a 10-month continuous simulation on a physically distributed urban catchment. Detailed analyses of parameters that physically represent the area in the SWMM5 model were done using remote sensing and geographical information systems techniques. Parallel computing and a multi-search driver were implemented along with a model-independent parameter estimation (PEST) method, to find global optima and accelerate the calibration process. PEST internal settings were tuned for the continuous SWMM5 estimation problem using one month of rainfall data. Subsequently, parameter calibration was carried out with 10 months of rainfall data and model validation was performed with 5 months of data. The overall calibration and validation of the SWMM5 model was good with a Nash-Sutcliffe efficiency coefficient greater than 0.5 and a total volume runoff error of less than 5%. Time offset bias from the rainfall data affected negatively the Nash-Sutcliffe efficiency because of highly variable storm cells. This study shows it is possible to reproduce accurately the urban runoff from a highly detailed, semidistributed SWMM5 model, even when the calibration process is restricted to physical parameters and not allowed to distort the geometric representation of the project area.
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Acknowledgments
The writers gratefully acknowledge the financial support from the Metropolitan Sewer District of Greater Cincinnati through a research grant to the University of Cincinnati. N.A.M.M. acknowledges a tuition scholarship from the University of Cincinnati. The authors are thankful for MSDGC support in providing rainfall, sewer configuration, and GIS data. The authors would also like to thank Dr. John Doherty for providing access to PES,T and Dr. Steven Burian for providing access to the GIS codes used in this research.
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Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 140 • Issue 6 • June 2014
Copyright
© 2014 American Society of Civil Engineers.
History
Received: Oct 4, 2012
Accepted: Jun 4, 2013
Published online: Mar 17, 2014
Published in print: Jun 1, 2014
Discussion open until: Aug 17, 2014
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