Here we present the results of a global sensitivity analysis (GSA) applied for a microscale hydrodynamic model, which combines pipe infrastructure and small scale source treatments in terms of raingardens (RGs). The aim is to identify the most influential model parameters to support the decision for future measurement installation sites and smart water control. For the model creation and simulation, the Storm Water Management Model (SWMM) is used. For the GSA method the Elementary Effect Test (EET) is applied, were uncertainties to 18 model input parameters, comprising 10 subcatchment and 8 Low Impact Development (LID) parameters, are assigned and analysed by 1,900 simulations. The model’s responses are evaluated at four main RGs and for two model outputs: Inflow and Surface runoff at the RGs. First results show that the most sensitive factors are the Depression Storage Impervious and the Soil Hydraulic Conductivity for the Inflow and Surface Runoff at RGs, respectively.

Parameter Sensitivity of a Microscale Hydrodynamic Model

Palermo S. A.;Piro P.
2019

Abstract

Here we present the results of a global sensitivity analysis (GSA) applied for a microscale hydrodynamic model, which combines pipe infrastructure and small scale source treatments in terms of raingardens (RGs). The aim is to identify the most influential model parameters to support the decision for future measurement installation sites and smart water control. For the model creation and simulation, the Storm Water Management Model (SWMM) is used. For the GSA method the Elementary Effect Test (EET) is applied, were uncertainties to 18 model input parameters, comprising 10 subcatchment and 8 Low Impact Development (LID) parameters, are assigned and analysed by 1,900 simulations. The model’s responses are evaluated at four main RGs and for two model outputs: Inflow and Surface runoff at the RGs. First results show that the most sensitive factors are the Depression Storage Impervious and the Soil Hydraulic Conductivity for the Inflow and Surface Runoff at RGs, respectively.
978-3-319-99866-4
Elementary Effect Test
LID
Sensitivity
SWMM
Uncertainty
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11770/289970
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