The influence of conceptual model structure on model performance: a comparative study for 237 French catchments

Abstract

Abstract. Models with a fixed structure are widely used in hydrological studies and operational applications. For various reasons, these models do not always perform well. As an alternative, flexible modelling approaches allow the identification and refinement of the model structure as part of the modelling process. In this study, twelve different conceptual model structures from the SUPERFLEX framework are compared with the fixed model structure GR4H, using a large set of 237 French catchments and discharge-based performance metrics. The results show that, in general, the flexible approach performs better than the fixed approach. However, the flexible approach has a higher chance of inconsistent results when calibrated on two different periods. When analysing the subset of 116 catchments where the two approaches produce consistent performance over multiple time periods, their average performance relative to each other is almost equivalent. From the point of view of developing a well-performing fixed model structure, the findings favour models with parallel reservoirs and a power function to describe the reservoir outflow. In general, conceptual hydrological models perform better on larger and/or wetter catchments than on smaller and/or drier catchments. The model structures performed poorly when there were large climatic differences between the calibration and validation periods, in catchments with flashy flows, and in catchments with unexplained variations in low flow measurements.

Incremental model breakdown to assess the multi-hypotheses problem

“…Further, it became clearer what causes those problems, by examining the model piece by piece as proposed by Clark et al (2016). Therefore, this method can be seen as a useful third way, in addition to step-wise model building (Bai et al, 2009;Westerberg and Birkel, 2015) and the comparison 10 of predefined structures (van Esse et al, 2013;, to explore the realm of multiple hypotheses. We propose future research should consider an automatic assemblage of model structures to test not only a manually manageable number of models but rather scan a larger variety of feasible combinations.…”

“…Most of these studies built their models incremental from bottom up to find out, if small modifications allow a better simulation (Bai 25 et al, 2009;Westerberg and Birkel, 2015). Others compared predefined model structures (van Esse et al, 2013;. In all cases, researchers stopped improving the models once a sufficient performance was reached.…”

“…van Esse et al, 2013;Fenicia et al, 2008;Gharari et al, 2014;Hublart et al, 2015;. Most of these studies built their models incremental from bottom up to find out, if small modifications allow a better simulation (Bai 25 et al, 2009;Westerberg and Birkel, 2015).…”

“…SUPERFLEX , Structure for Unifying Multiple Modelling Alternatives (SUMMA) (Clark et al, 2015b(Clark et al, , 2015a, or the Catchment Modelling Framework 10 (CMF) (Kraft et al, 2011). SUPERFLEX targets the construction of lumped conceptual models (van Esse et al, 2013;Gharari et al, 2014). SUMMA and CMF support the generation of multi scale approaches from plot over hillslope to basins and from lumped to fully distributed models.…”

State-space representation of a bucket-type rainfall-runoff model: a case study with State-Space GR4 (version 1.0)

“…It is widely used for various hydrological applications in France (Grouillet et al, 2016;van Esse et al, 2013) and in other countries (Dakhlaoui et al, 2017;Seiller et al, 2017). It has shown good performances on a wide range of catchments (Coron et al, 2012).…”