Accounting for seasonal dependence in hydrological model errors and prediction uncertainty

Abstract

Streamflows often vary strongly with season, and this leads to seasonal dependence in hydrological model errors and prediction uncertainty. In this study, we introduce three error models to describe errors from a monthly rainfall-runoff model: a seasonally invariant model, a seasonally variant model, and a hierarchical error model. The seasonally variant model and the hierarchical error model use month-specific parameters to explicitly account for seasonal dependence, while the seasonally invariant model does not. A Bayesian prior is used in the hierarchical error model to account for potential variation and connection among model parameters of different months. The three error models are ap..