Note: This is documentation for version 5.16 of Source. For a different version of Source, select the relevant space by using the Spaces menu in the toolbar above">Note: This is documentation for version 5.16 of Source. For a different version of Source, select the relevant space by using the Spaces menu in the toolbar above

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Background

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.

A key issue in urban demand calibration is understanding the split between Indoor and Outdoor demands in the study area. Indoor demands are more consistent, with long term changes occurring mostly as a result of population growth and also the implementation of changes in end-use efficiencies. Outdoor demands are more variable, affected by seasonal variations as well as restrictions on water use.





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