Abstract
Every application of soil erosion models brings the need of proper
parametrization, i.e., finding physically or conceptually plausible
parameter values that allow a model to reproduce measured values. No
universal approach for model parametrization, calibration and validation
exists, as it depends on the model, spatial and temporal resolution and
the nature of the datasets used. We explored some existing options for
parametrization, calibration and validation for erosion modelling
exemplary with a specific dataset and modelling approach. A modified
version of the Morgan-Morgan-Finney (MMF) model was selected,
representing a balanced position between physically-based and empirical
modelling approaches. The resulting calculator for soil erosion (CASE)
model works in a spatially distributed way on the timescale of
individual rainfall events. A dataset of 142 high-intensity rainfall
experiments in Central Europe (AT, HU, IT, CZ), covering various slopes,
soil types and experimental designs was used for calibration and
validation with a modified Monte-Carlo approach. Subsequently, model
parameter values were compared to parameter values obtained by
alternative methods (measurements, pedotransfer functions, literature
data). The model reproduced runoff and soil loss of the dataset in the
validation setting with R 2 adj of
0.89 and 0.76, respectively. Satisfactory agreement for the water phase
was found, with calibrated saturated hydraulic conductivity (k
sat) values falling within the interquartile range of k
sat predicted with 14 different PTFs, or being within
one order of magnitude. The chosen approach also well reflected specific
experimental setups contained in the dataset dealing with the effects of
consecutive rainfall and different soil water conditions. For the
sediment phase of the tested model agreement between calibrated
cohesion, literature values and field measurements were only partially
in line. For future applications of similar model applications or
datasets, the obtained parameter combinations as well as the explored
methods for deriving them may provide guidance.