Abstract
<strong class="journal-contentHeaderColor">Abstract.</strong> 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 take into account 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 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 calibration options and two spatial frameworks, for a total of 78 distinct modelling options. A simple average method was used to combine the various simulated streamflow at the outlet of the catchments and sub-catchments. The most efficient lumped model on a given catchment 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 in a variable spatial framework to simulate streamflow.
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