Addressing ten questions about conceptual rainfall–runoff models with global sensitivity analyses in R

Sensitivity analysis (SA) is generally recognized as a worthwhile step to diagnose and remedy difficulties in identifying model parameters, and indeed in discriminating between model structures. An analysis of papers in three journals indicates that SA is a standard omission in hydrological modeling exercises. We provide some answers to ten reasonably generic questions using the Morris and Sobol SA methods, including to what extent sensitivities are dependent on parameter ranges selected, length of data period, catchment response type, model structures assumed and climatic forcing. Results presented demonstrate the sensitivity of four target functions to parameter variations of four rainfall–runoff models of varying complexity (4–13 parameters). Daily rainfall, streamflow and pan evaporation data are used from four 10-year data sets and from five catchments in the Australian Capital Territory (ACT) region. Similar results are obtained using the Morris and Sobol methods. It is shown how modelers can easily identify parameters that are insensitive, and how they might improve identifiability. Using a more complex objective function, however, may not result in all parameters becoming sensitive. Crucially, the results of the SA can be influenced by the parameter ranges selected. The length of data period required to characterize the sensitivities assuredly is a minimum of five years. The results confirm that only the simpler models have well-identified parameters, but parameter sensitivities vary between catchments. Answering these ten questions in other case studies is relatively easy using freely available software with the Hydromad and Sensitivity packages in R.