Identification of urban drainage network rainfall-runoff black-box models

The problem of calibrating conceptual models for the design of urban drainage networks is analyzed and the use of black-box identification methods is proposed and applied to experimental data. Both linear (ARX and state space) and nonlinear (polynomial and neural NARX) models are considered and their performance in the simulation and prediction of the network flow from rainfall measurements is evaluated.