Simultaneous Calibration of Hydrologic Model Structure and Parameters Using a Blended Model

Abstract

AbstractThe advent of hydrological modeling frameworks that support multiple model structures using the same software enables both model structure and model parameters to be calibrated and assessed. To date, the identification of optimal model structure has typically been performed manually. Here, a continuous (rather than discrete) treatment of model structure is used, which enables simultaneous automatic calibration of model structure and parameters using a conventional real‐valued decision variable optimization algorithm (the dynamically dimensioned search algorithm, DDS). The method, referred to herein as blended model structure calibration (BMSC), relies upon the calculation of each hydrologic flux (e.g., for infiltration) as a weighted average of fluxes generated from multiple process algorithm options. This method is applied to 12 lumped MOPEX catchment models and compared to the calibration of 108 fixed model structures, representing all possible permutations of fixed model structures with the given process options in this study. The BMSC method consistently identified near‐optimal model structure (as evaluated using average model rank performance) at significantly lower computational cost than calibrating the collective of fixed structure models. The BMSC method also provides a useful tool in identifying dominant processes and model structures in catchments.