Catchment responses to plausible parameters and input data under equifinality in distributed rainfall-runoff modeling

In a hydrological simulation using a complex model, equifinality is likely to occur in many different ways, due to various sources associated with the model structure, parameter as well as data uncertainties involved in modeling process. This study aims to demonstrate the equifinality problem in streamflow prediction with a distributed rainfall-runoff model and also investigate the effect of parameter and input uncertainties on an internal catchment response in time and space under the equifinality condition. For this objective, several experiments were carried out step by step as follows. First, we estimated plausible parameter sets, which lead to similarly good objective function values, using the shuffled complex evolution metropolis (SCEM-UA) algorithm and also generated plausible input scenarios with different spatial patterns from radar rainfall field, which showed minimum runoff errors. Then, we adopted a computational tracer method based on a time-space accounting scheme, combined with a distributed model for analyzing how a catchment behaves under a given equifinality condition by parameter and input uncertainties. It was found that the global responses of a catchment to the predefined equifinality factors were very similar; all simulated hydrographs were almost identical in spite of the different model parameter values and different spatial patterns of rainfall data. On the other hand, the internal catchment responses, tracked by the computational tracer method, were sensitive to plausible scenarios. The results of the internal catchment behavior show that the distributed rainfall-runoff model has multiple alternative flow pathways, providing identical hydrographs in time and space when the rainfall over the catchment transforms into runoff. Our approach can be used to understand catchment responses to various uncertainty sources by visualizing the spatiotemporal runoff generation process at the watershed scale.