Comparison of automatic calibration techniques for simulating streamflow in tropical catchment

Efficacy of hydrological model strongly depends on model calibration. A number of methods has been developed and employed for optimization of hydrological model so that model can replicate the observed streamflow accurately. A study has been carried out in this paper to find the best parameter optimization method for the calibration of a daily rainfall-runoff model for streamflow simulation of a tropical catchment. For the purpose, seven well known parameter optimization methods namely, Uniform Random Search, Pattern Search, Multi Start Pattern Search, Rosenbrock Method, Multi Start Rosenbrock Search, Genetic Algorithm and Suffled Complex Evaluation are used for the calibration of a conceptual hydrological model known as SIMHYD. Performance of the methods is evaluated by using Nash-Sutcliff coefficient and correlation coefficient. The result indicates that evolutionary algorithm based optimization techniques can optimize the model parameters more accurately for precise calibration of model and reliable prediction of daily streamflow in a tropical catchment