Uncertainty in sewer sediment deposit modelling: Detailed vs simplified modelling approaches |
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Affiliation: | 1. School of Mathematics and Statistics, Hefei Normal University, Hefei 230061, China;2. Key Laboratory of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China |
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Abstract: | The paper presents the results of a study in which the uncertainty levels associated with a detailed and a simplified/parsimonious sewer sediment modelling approach have been compared. The detailed approach used an Infoworks CS sewer network model combined with a user developed sediment transport code and the simplified approach used a conceptual sewer flow and quality model. The two approaches have been applied to a single case study sewer network and the simulation results compared. The case study was selected as moderate storm events had occurred during a 2 year rainfall and sewer flow monitoring period. Flooding had been observed and this was thought to be caused by significant solids accumulation in the sewer network. As a result sediment deposit measurements were carried out over a 6 month period. Model simulations were made of this period and predictions obtained of sediment deposit location and depth. The uncertainty analysis of both modelling approaches was carried out using Monte Carlo based computational methods. This was a limitation for the detailed approach with regards to computational time. Use of the simplified model was not constrained by this issue and so a more conventional assessment of the uncertainty was possible. The simplified approach, due to its structure, only provided a temporal estimate of uncertainty at the final section of the catchment. The detailed approach enabled an assessment of uncertainty at an individual pipe scale but only at the end of the simulation period. A comparison of the uncertainty estimations from both methods at the final section of the catchment and the end of the simulation period indicated comparable values of predicted uncertainty. Therefore a complementary use of both approaches would allow reasonably comparable estimations of levels of uncertainty at both a spatial and temporal scale. The use of such modelling approaches may provide a useful decision-making tool for sewer system management. |
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