Impact of model simplifications on soil erosion predictions: application of the GLUE methodology to a distributed event-based model at the hillslope scale
Abstract
In this paper, we analyse how the performance and calibration of a distributed event-based soil erosion model at the hillslope
scale is affected by different simplifications on the parameterizations used to compute the production of suspended sediment by
rainfall and runoff. Six modelling scenarios of different complexity are used to evaluate the temporal variability of the
sedimentograph at the outlet of a 60 m long cultivated hillslope. The six scenarios are calibrated within the generalized likelihood
uncertainty estimation framework in order to account for parameter uncertainty, and their performance is evaluated against
experimental data registered during five storm events. The Nash–Sutcliffe efficiency, percent bias and coverage performance
ratios show that the sedimentary response of the hillslope in terms of mass flux of eroded soil can be efficiently captured by a
model structure including only two soil erodibility parameters, which control the rainfall and runoff production of suspended
sediment. Increasing the number of parameters makes the calibration process more complex without increasing in a noticeable
manner the predictive capability of the model.