Abstract
This study investigates how the performance of a set of models depends on the catchments to which these models are applied. It examines (i) whether it is possible to identify a single best model for each of the catchments, or whether results are dominated by equifinality; and (ii) whether the ranking of model performance can be related to a set of predictors, such as climate and catchment characteristics. In order to explore these questions, we applied 12 model structures to 99 catchments in Germany, ranging in size from 10 km2 to 1826 km2. We examined model performance in terms of streamflow predictions, based on various indices. Our results indicate that for some catchments many structures perform equally well, whereas for other catchments a single structure clearly outperforms the others. We could not identify clear relationships between relative model performance and catchment characteristics. This result led us to conclude that for the spatial scales considered, it is difficult to base the selection of a lumped conceptual model based on a priori assessment, and we recommend a posteriori selection based on model comparisons.
Highlights
Understanding the key factors that control similarities and differences in catchment response behavior is an important objective of hydrological science
“Since dominant runoff processes are expected to vary between catchments of different substrate, climate, and land use, it would be anticipated that different model structures may perform better in different catchments” [11]
The first two classes reflect the different points of view on the general applicability of hydrological models, where the first class represents the perception that different models are appropriate in different regions, as shown in some studies e.g., [15,16]
Summary
Understanding the key factors that control similarities and differences in catchment response behavior is an important objective of hydrological science. This objective underlies, for example, the research initiative of “catchment classification,” which aims to develop the theoretical framework to sort the variability in “space, time, and process” of catchment systems [1]. Different authors have criticized the use of off-the-shelf models in favor of “flexible” approaches that can be adapted to the dominant processes of the catchments [7,8,9,10]. “Since dominant runoff processes are expected to vary between catchments of different substrate, climate, and land use, it would be anticipated that different model structures may perform better in different catchments” [11]
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