Comparison of Parameter Sensitivity Analysis Methods for Lumped Watershed Model

Four sensitivity analysis methods: (1) local analysis using parameter estimation software (PEST), (2) regional sensitivity analysis (RSA), (3) analysis of variance (ANOVA), and (4) Sobol's method were compared to identify effective parameter sensitivity analysis approaches that will improve our understanding of lumped hydrologic models. The methods' relative performance in terms of efficiencies and effectiveness have been analyzed and compared in a broad scope. The lumped Sacramento soil moisture accounting model (SAC-SMA) and the SNOW-17 were applied to two medium sized watersheds within the Juniata River Basin in Pennsylvania to quantify model parameter sensitivities in this study. The repeatability, robustness, efficiency, and ease-of-use of the four sensitivity methods were comprehensively evaluated. It was found in this study that ANOVA and Sobol's method outperformed RSA and PEST. Sobol's method is more robust but computationally expensive relative to ANOVA.