Evaluation of PESERA in two contrasting environments

The performance of the Pan-European Soil Erosion Risk Assessment (PESERA) model was evaluated by comparison withexisting soil erosion data collected in plots under different land uses and climate conditions in Europe. In order to identify the mostimportant sources of error, the PESERA model was evaluated by comparing model output with measured values as well as byassessing the effect of the various model components on prediction accuracy through a multistep approach. First, the performanceof the hydrological and erosion components of PESERA was evaluated separately by comparing both runoff and soil loss predictionswith measured values. In order to assess the performance of the vegetation growth component of PESERA, the predictions of themodel based on observed values of vegetation ground cover were also compared with predictions based on the simulated vegetationcover values. Finally, in order to evaluate the sediment transport model, predicted monthly erosion rates were also calculatedusing observed values of runoff and vegetation cover instead of simulated values. Moreover, in order to investigate the capabilityof PESERA to reproduce seasonal trends, the observed and simulated monthly runoff and erosion values were aggregated atdifferent temporal scale and we investigated at what extend the model prediction error could be reduced by output aggregation.PESERA showed promise to predict annual average spatial variability quite well. In its present form, short-term temporal variationsare not well captured probably due to various reasons. The multistep approach showed that this is not only due to unrealisticsimulation of cover and runoff, being erosion prediction also an important source of error. Although variability between theinvestigated land uses and climate conditions is well captured, absolute rates are strongly underestimated. A calibration procedure,focused on a soil erodibility factor, is proposed to reduce the significant underestimation of soil erosion rates.