Calibration of a modified SFB model for twenty-five Australian catchments using simulated annealing

Simulated annealing is used to calibrate a conceptual rainfall-runoff model (a modification of Boughton's SFB model) by fitting modelled monthly runoff to historical data. The problem to be solved is that of finding the global minimum of a multivariate function that has many extraneous local minima, a situation in which conventional optimisation methods are ineffective. The model estimates runoff from daily rainfall and daily potential evaporation estimates for a catchment. The 25 catchments used for the study cover a wide range of climatic types, including humid tropical, humid subtropical, arid, semiarid, Mediterranean and marine west-coast. The catchments differ in the number and type of model processes activated, which is indicated by the parameters fitted. A parsimonious approach was adopted where only the sensitive model parameters for a catchment were fitted. The objective function which quantifies discrepancies between the computed and observed streamflows was carefully selected to satisfy the least squares assumptions. Finally, a case study is presented to illustrate the fitting process and highlight some of the difficulties that may be encountered. It is shown that simulated annealing is able to fit six or seven sensitive parameters of the modified SFB model by locating the global minimum of the objective function. (C) 1997 Elsevier Science B.V.