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Automated Urban Rainfall–Runoff Model Generation with Detailed Land Cover and Flow Routing
Constructing hydrological models for large urban areas is time consuming and laborious due to the requirements for high-resolution data and fine model detail. An open-source algorithm using adaptive subcatchments is proposed to automate Storm Water Management Model (SWMM) construction. The algorithm merges areas with homogeneous land cover and a common outlet into larger subcatchments, while retaining small-scale details where land cover or topography is more heterogeneous. The method was tested on an 85-ha urban catchment in Helsinki, Finland. A model with adaptive subcatchments reproduced the observed discharge at the catchment outlet with high model-performance indices emphasizing the strength of the proposed method. Computation times of the adaptive model were substantially lower than those of a corresponding model with uniformly sized high-resolution subcatchments. Given that high-resolution land cover and topography data are available, the proposed algorithm provides an advanced method for implementing SWMM models automatically even for large urban catchments without a substantial manual workload. Simultaneously, the high-resolution land cover details of the catchments can be maintained where they matter the most.
Automated Urban Rainfall–Runoff Model Generation with Detailed Land Cover and Flow Routing
Constructing hydrological models for large urban areas is time consuming and laborious due to the requirements for high-resolution data and fine model detail. An open-source algorithm using adaptive subcatchments is proposed to automate Storm Water Management Model (SWMM) construction. The algorithm merges areas with homogeneous land cover and a common outlet into larger subcatchments, while retaining small-scale details where land cover or topography is more heterogeneous. The method was tested on an 85-ha urban catchment in Helsinki, Finland. A model with adaptive subcatchments reproduced the observed discharge at the catchment outlet with high model-performance indices emphasizing the strength of the proposed method. Computation times of the adaptive model were substantially lower than those of a corresponding model with uniformly sized high-resolution subcatchments. Given that high-resolution land cover and topography data are available, the proposed algorithm provides an advanced method for implementing SWMM models automatically even for large urban catchments without a substantial manual workload. Simultaneously, the high-resolution land cover details of the catchments can be maintained where they matter the most.
Automated Urban Rainfall–Runoff Model Generation with Detailed Land Cover and Flow Routing
Niemi, Tero J. (author) / Kokkonen, Teemu (author) / Sillanpää, Nora (author) / Setälä, Heikki (author) / Koivusalo, Harri (author)
2019-02-27
Article (Journal)
Electronic Resource
Unknown
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