Improving the shuffled complex evolution scheme for optimization of complex nonlinear hydrological systems: Application to the calibration of the Sacramento soil‐moisture accounting model

[1] An innovative algorithm, shuffled complexes with principal components analysis (SP‐UCI), is developed to overcome a critical deficiency of the shuffled complex evolution scheme: population degeneration. Population degeneration means that, during the evolutionary search process, the population of search particles may degenerate into a subspace of the full parameter space, thereby missing the capacity of fully exploring the parameter space. Being confined in a subspace may even lead the particle population to converge to nonstationary points, which is a fatal malfunction. To overcome this problem, SP‐UCI employs the principal components analysis to detect the occurrence of population degeneration and remedy the adverse effects. The ensemble of calibrations of the Sacramento soil moisture accounting model with the SP‐UCI method over the Leaf River basin, Mississippi, retrieves the optimal parameter values with the lowest recorded root‐mean‐squared error of simulated daily runoff against the observation. Moreover, the result also provides consistent (narrow ranges) model parameter distribution, which results in a better understanding of the model’s behavior, given the watershed’s hydrologic features.