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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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