Analysis of the behavior of a rainfall-runoff model using three global sensitivity analysis methods evaluated at different temporal scales

Summary The effect of 11 parameters on the discharge of a conceptual rainfall–runoff model was analyzed for a small Austrian catchment. The sensitivities were computed using three methods: Sobol’s indices, the mutual entropy and regional sensitivity analysis (RSA). The calculations were carried out for different temporal scales of evaluation ranging from daily to a multiannual period. A comparison of the methods shows that the mutual entropy and the RSA methods give more robust results than Sobol’s method, which shows a higher variability in the sensitivities when they are calculated using different data sets. While all sensitivity methods are suitable for identifying the most sensitive parameters of a model, there are increasing differences in the results when the parameters become less important and also when shorter temporal scales are considered. A correlation analysis further indicated that the periods in which the parameter sensitivity rankings did not agree between the different methods are characterized by a higher impact of the parameters interactions on the modeled discharge. An analysis of the parameter sensitivity across the scales showed that the number of important parameter decreases when longer evaluation periods are considered. For instance, it was observed that all parameters were important at least during 1 day a daily scale, while at a yearly scale only the parameters characterizing the soil storage and the recession constants for interflow and percolation had high sensitivities. With respect to the impact of the interactions between parameters on the model results, it was observed that the largest effect is related to the parameters describing the size of the soil storage, the interflow and the percolation flow recession constants. Further, it was observed that there is a positive correlation between the importance of the interactions and the measured discharge. While the study focuses on quantitative sensitivity measures, it is also highlighted that graphical RSA analyses provide additional information regarding the parameter ranges associated with different discharge levels. This information can be used for increasing the understanding of the mechanisms by which the parameters affect the model results.

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