An advanced tool integrating failure and sensitivity analysis to novel modeling for stormwater flooding volume

Abstract. An innovative tool for modelling specific flood volume was presented, which can be applied to assess the need for stormwater network modernisation as well as for advanced flood risk assessment. Field measurements for a catchment area in Kielce, Poland were used to apply the model and demonstrate its usefulness. This model extends the capabilities of recently developed statistical and/or machine learning hydrodynamic models developed from multiple runs of the U.S. EPA’s Storm Water Management Model (SWMM) model. The extensions enable inclusion of: 1) characteristics of the catchment, and its stormwater network, calibrated model parameters expressing catchment retention and the capacity of the sewer system, (2) extended sensitivity analysis and (3) risk analysis. Sensitivity coefficients of calibrated model parameters include correction coefficients for percentage area, flow path, depth of storage, impervious area, Manning roughness coefficients for impervious areas, and Manning roughness coefficients for sewer channels. Sensitivity coefficients were determined with regard to rainfall intensity and characteristics of the catchment and stormwater network. Extended sensitivity analysis enabled an evaluation of the variability of the specific flood volume and sensitivity coefficients within a catchment, in order to identify the most vulnerable areas threatened by flooding, Thus, the model can be used to identify areas particularly susceptible to stormwater network failure and the sections of the network where corrective actions should be taken to reduce the probability of system failure. The developed simulator to determine a specific flood volume represents an alternative approach to the SWMM model that, unlike current approaches, is calibratable with limited topological data availability, therefore generates a lower cost due to the less amount and specificity of data required.