Abstract

This paper presents a probabilistic methodology that allows the study of the interactions between changes in rainfall dynamics and impervious areas in urban catchment on a long- and short-term basis. The proposed probabilistic model predict future storm overflows while taking into account the dynamics of changes in impervious areas and rainfall. In this model, a logistic regression method was used to simulate overflow resulting from precipitation events based on average rainfall intensity and impervious area. The adopted approach is universal (as it can be used in other urban catchments) and is a significant simplification of classic solutions; a hydrodynamic model is used to analyse the operation of the overflow. For the rainfall simulations, a rainfall generator based on the Monte Carlo method was used. In this method, a modification that allows the simulation of changes taking place in rainfall dynamics, including the effects of climate change, was introduced. This method provides the opportunity to expand and modify probabilistic models in which outflow from the catchment is modelled to predict the functioning of reservoirs and to design sewer networks that have the ability to deal with future rainfall dynamics, including moderate, strong, and violent downpours according to the Sumner scale. To verify the simulation results with a probabilistic model, an innovative concept using a hydrodynamic model was considered. This verification considers the changes in the impervious area in the period covered by the simulations and is limited using standard calculation procedures. In practice, the model presented in this work creates opportunities for defining the concept of sustainable development in urban catchments while taking into account the factors mentioned above. From the perspective of landscaping, this is important because it creates the opportunity to limit the impacts of climate change and area urbanization on the receiving waters.

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Authors (6)