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Abstract
Estimation of parameter values is an essential step in the application of catchment modelling systems. This step is time-consuming and requires considerable effort. While a variety of approaches have been developed to accelerate the process, this paper proposes a method to reduce significantly the number of parameters for a large catchment when a semi-distributed catchment modelling system is applied. Past studies have reported on the use of a scaling parameter to adjust parameter values from their initial values, introduced herein is the use of a scaling parameter together with a variation coefficient. This enables the spatial variation of changes in parameter values across the catchment to be considered. A case study was conducted for a 14,000 km2 catchment to assess the validity of this approach where the focus of the catchment modelling was the prediction of a design flood statistic. This catchment was divided into 155 subcatchments with 5 sensitive parameters per subcatchment. Hence, a total of 775 parameters needed to be considered. Using the proposed approach, the number of parameters considered during the calibration was reduced to 8 coefficients which was reasonable for a calibration and validation process that also enabled an estimate of the parameter variability.
Acknowledgements
Support for the first author was provided by a VIED-UTS scholarship. The support of both the Australian and Vietnamese partners in this scholarship scheme is gratefully acknowledged.