ABSTRACT
This chapter introduces some of the more novel concepts in urban drainage modelling. It discusses models that are not physically based and rely more on data and less on fundamental physical equations. The chapter summarises approaches to modelling that can be considered alternative to more traditional, physically based models. An empirical model is based on observation rather than theory. It usually represents the real system by simple relationships that rely for their accuracy on parameters that are calibrated using observed data. Artificial neural networks are a product of developments in artificial intelligence. A stochastic model includes randomness. Unlike a deterministic model, it does not necessarily give the same output for the same input. Unlike other typical urban water models that simulate actual water flows, Urban Water Optioneering Tool (UWOT) adopts an alternative approach based on the generation, aggregation, and transmission of demand signals, starting from household water appliances and moving towards the source.
