Multi-model approach in a variable spatial framework for streamflow simulation

Accounting for the variability of hydrological processes and climate conditions between catchments and within catchments remains a challenge in rainfall-runoff modelling. Among the many approaches developed over the past decades, multi-model approaches provide a way to consider the uncertainty linked to the choice of model structure and its parameter estimates. Semi-distributed approaches make it possible to account explicitly for spatial variability while maintaining a limited level of complexity. However, these two approaches have rarely been used together. Such a combination would allow us to take advantage of both methods. The aim of this work is to answer the following question: what is the possible contribution of a multi-model approach within a variable spatial framework compared to lumped single models for streamflow simulation?To this end, a set of 121 catchments with limited anthropogenic influence in France was assembled, with precipitation, potential evapotranspiration, and streamflow data at the hourly time step over the period 1998-2018. The semi-distribution set-up was kept simple by considering a single downstream catchment defined by an outlet and one or more upstream sub-catchments. The multi-model approach was implemented with 13 rainfall-runoff model structures, three objective functions, and two spatial frameworks, for a total of 78 distinct modelling options. A simple averaging method was used to combine the various simulated streamflow at the outlet of the catchments and sub-catchments. The lumped model with the highest efficiency score over the whole catchment set was taken as the benchmark for model evaluation.Overall, the semi-distributed multi-model approach yields better performance than the different lumped models considered individually. The gain is mainly brought about by the multi-model set-up, with the spatial framework providing a benefit on a more occasional basis. These results, based on a large catchment set, evince the benefits of using a multi-model approach in a variable spatial framework to simulate streamflow.