Author(s): M. S. Gibbs; G. C. Dandy; H. R. Maier
Linked Author(s):
Keywords: Rainfall-runoff modelling; Sensitivity Analysis; Multi-Objective Optimisation; Genetic Algorithms; Ungauged Catchments
Abstract: Many regions of interest for water resources planning and management do not have extensive flow records for calibration of surface water models. In these cases, an understanding of the significance of the various parameters involved is beneficial for model development. To investigate this, the Soil Moisture Accounting model in HEC-HMS has been applied to four catchments in Southern Australia. A Multi-Objective Genetic Algorithm has been used to identify regions of good parameter values, before the Extended Fourier Amplitude Sensitivity Test has been used to investigate the impact of model parameters, as well as the interactions between parameters, on measures of predictive performance. The surface storage parameters were found to have little influence on model performance, and hence could potentially be set to constant values for the catchments considered. Conversely, the soil and tension storage parameters have the largest influence on model performance, and therefore should be the focus of model parameterisation for ungauged catchments.
Year: 2011