This is a Preprint and has not been peer reviewed. This is version 3 of this Preprint.
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Abstract
Continual improvements in publicly available global geospatial datasets provide an opportunity for deriving urban drainage networks and simulation models of these networks (UDMs) worldwide. We present SWMManywhere, which leverages such datasets for generating synthetic UDMs and creating a Storm Water Management Model for any urban area globally. SWMManywhere’s highly modular and parameterised approach enables significant customisation to explore hydraulicly feasible network configurations. Key novelties of our workflow are in network topology derivation that accounts for combined effects of impervious area and pipe slope. We assess SWMManywhere by comparing pluvial flooding, drainage network outflows, and design with known networks. The results demonstrate high quality simulations are achievable with a synthetic approach even for large networks. Our extensive sensitivity analysis shows that the locations of manholes, outfalls, and underlying street network are the most sensitive parameters. We find widespread sensitivity across all parameters without clearly defined values that they should take, thus, recommending an uncertainty driven approach to synthetic drainage network modelling. This study showcases significant potential of SWMManywhere for research and industry applications to provide drainage network models in urban areas where traditional approaches are impractical.
DOI
https://doi.org/10.31223/X5GT5X
Subjects
Engineering
Keywords
Algorithmic network generation, Urban drainage, Sensitivity analysis, Synthetic networks, Hydraulic modelling, Network topology
Dates
Published: 2024-10-11 11:52
Last Updated: 2024-10-24 15:56
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CC-By Attribution-NonCommercial-NoDerivatives 4.0 International
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