Introduction
Model calibration is used to ensure that modelled outputs sufficiently represent available observed values. The extent to which modelled values match observed values is quantified using an objective function such as the Nash Sutcliffe Efficiency (NSE) coefficient. Source has several objective functions to choose from - see the UG chapter Calibration Wizard for catchments for a description of available objective functions. The process of calibration involves adjusting model parameters through multiple model runs until a satisfactory value of the chosen Objective Function is obtained. The choice of parameters and appropriate Objective Function is key to this process.
Calibration of urban demand models can be challenging as there are hundreds of parameters that can be varied. Fortunately, the values of many parameters are well informed by the available input data. Due to the large number of parameters and the resulting high degree of parameter non-uniqueness, calibration using standard automatic optimisation algorithms is unlikely to be successful. It is proposed that a process of manual parameter adjustment is adopted, focussing on sensitive parameters that are known to have a high degree of uncertainty.