Comparison of Newton-type and direct search algorithms for calibration of conceptual rainfall-runoff models
Hendrickson, J. D., Sorooshian, S., & Brazil, L. (1988). Comparison of Newton-type and direct search algorithms for calibration of conceptual rainfall-runoff models. AGU Water Resources Research, 24(5), 691-700.
An examination of the calibration aspect of conceptual rainfall-runoff models was undertaken using the Sacramento soil moisture accounting model and a study comparing the performance of a Newton-type optimization algorithm with that of a direct search algorithm. Results indicate that the direct search algorithm is the more robust of the two because the Newton-type algorithm is more susceptible to poor conditioning of the response surface. Graphical studies of the response surface of the model's parameter space confirmed the presence of discontinuities and a rough-textured surface, particularly in the derivatives.