Modelling of Inflow and Infiltration into Wastewater Systems with Regression and Random Forest

Sammanfattning: The aim of this thesis was to evaluate the validity of statistical modelling, with regards to flow in wastewater systems based on precipitation. A wastewater system, which is a system of pump-stations connected via pipes, is affected by precipitation as rainwater enters the system. The rainwater that enters the system can sometimes, especially if the precipitation is heavy, increase the flow by several hundred percent. The goal with the models created for this report was, to first predict how much rainwater there was in the wastewater system based on precipitation, and second, to examine where in a geographical grid this rainwater entered the system. For the first goal a linear regression model was applied, this model showed that it was indeed possible to predict excess water in the system, but large errors for individual time points where to be expected, especially for light precipitation. For the second goal a random forest model was applied. This model however gave no additional insight beyond what an initial correlation study between precipitation in different parts of the geographical grid and flow had already shown. The areas in the geographical grid pointed out by both the random forest model and the initial correlation study were not the actual uptake areas of the pump-station these models were applied to. This leads to the conclusion that for the data set used, and with the models applied in the manner in which they were in this thesis, it was not possible to predict where rainwater enters the system.