Quantifying Roughness Coefficient Uncertainty in Urban Flooding Simulations through a Simplified Methodology
AbstractA methodology is presented which can be used in the evaluation of parametric uncertainty in urban flooding simulation. Due to the fact that such simulations are time consuming, the following methodology is proposed: (a) simplification of the description of the physical process; (b) derivation of a training data set; (c) development of a data-driven surrogate model; (d) use of a forward uncertainty propagation scheme. The simplification comprises the following steps: (a) unit hydrograph derivation using a 2D hydrodynamic model; (b) calculation of the losses in order to determine the effective rainfall depth; (c) flood event simulation using the principle of the proportionality and superposition. The above methodology was implemented in an urban catchment located in the city of Athens, Greece. The model used for the first step of the simplification was FLOW-R2D, whereas the well-known SWMM software (US Environmental Protection Agency, Washington, DC, USA) was used for the second step of the simplification. For the training data set derivation, an ensemble of 100 Unit Hydrographs was derived with the FLOW-R2D model. The parameters which were modified in order to produce this ensemble were the Manning coefficients in the two friction zones (residential and urban open space areas). The surrogate model used to replicate the unit hydrograph derivation, using the Manning coefficients as an input, was based on the Polynomial Chaos Expansion technique. It was found that, although the uncertainties in the derived results have to be taken into account, the proposed methodology can be a fast and efficient way to cope with dynamic flood simulation in an urban catchment. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Bellos, V.; Kourtis, I.M.; Moreno-Rodenas, A.; Tsihrintzis, V.A. Quantifying Roughness Coefficient Uncertainty in Urban Flooding Simulations through a Simplified Methodology. Water 2017, 9, 944.
Bellos V, Kourtis IM, Moreno-Rodenas A, Tsihrintzis VA. Quantifying Roughness Coefficient Uncertainty in Urban Flooding Simulations through a Simplified Methodology. Water. 2017; 9(12):944.Chicago/Turabian Style
Bellos, Vasilis; Kourtis, Ioannis M.; Moreno-Rodenas, Antonio; Tsihrintzis, Vassilios A. 2017. "Quantifying Roughness Coefficient Uncertainty in Urban Flooding Simulations through a Simplified Methodology." Water 9, no. 12: 944.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.