Soft combination of local models in a multi-objective framework

Conceptual hydrologic models are useful tools as they provide an interpretable representation of the hydrologic behaviour of a catchment. Their representation of catchment's hydrological processes and physical characteristics, however, implies a simplification of the complexity and heterogeneity of reality. As a result, these models may show a lack of flexibility in reproducing the vast spectrum of catchment responses. Hence, the accuracy in reproducing certain aspects of the system behaviour may be paid in terms of a lack of accuracy in the representation of other aspects. By acknowledging the structural limitations of these models, we propose a modular approach to hydrological simulation. Instead of using a single model to reproduce the full range of catchment responses, multiple models are used, each of them assigned to a specific task. While a modular approach has been previously used in the development of data driven models, in this study we show an application to conceptual models. The approach is here demonstrated in the case where the different models are associated with different parameter realizations within a fixed model structure. We show that using a 'composite' model, obtained by a combination of individual 'local' models, the accuracy of the simulation is improved. We argue that this approach can be useful because it partially overcomes the structural limitations that a conceptual model may exhibit. The approach is shown in application to the discharge simulation of the experimental Alzette River basin in Luxembourg, with a conceptual model that follows the structure of the HBV model.