The performance of the Pan-European Soil Erosion Risk Assessment (PESERA) model was evaluated by comparison with existing soil erosion data collected in plots under different land uses and climate conditions in Europe. In order to identify the most important sources of error, the PESERA model was evaluated by comparing model output with measured values as well as by assessing the effect of the various model components on prediction accuracy through a multistep approach. First, the performance of the hydrological and erosion components of PESERA was evaluated separately by comparing both runoff and soil loss predictions with measured values. In order to assess the performance of the vegetation growth component of PESERA, the predictions of the model based on observed values of vegetation ground cover were also compared with predictions based on the simulated vegetation cover values. Finally, in order to evaluate the sediment transport model, predicted monthly erosion rates were also calculated using observed values of runoff and vegetation cover instead of simulated values. Moreover, in order to investigate the capability of PESERA to reproduce seasonal trends, the observed and simulated monthly runoff and erosion values were aggregated at different 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 variations are not well captured probably due to various reasons. The multistep approach showed that this is not only due to unrealistic simulation of cover and runoff, being erosion prediction also an important source of error. Although variability between the investigated 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.
Evaluation of the PESERA model in two contrasting environments
VACCA, ANDREA;
2009-01-01
Abstract
The performance of the Pan-European Soil Erosion Risk Assessment (PESERA) model was evaluated by comparison with existing soil erosion data collected in plots under different land uses and climate conditions in Europe. In order to identify the most important sources of error, the PESERA model was evaluated by comparing model output with measured values as well as by assessing the effect of the various model components on prediction accuracy through a multistep approach. First, the performance of the hydrological and erosion components of PESERA was evaluated separately by comparing both runoff and soil loss predictions with measured values. In order to assess the performance of the vegetation growth component of PESERA, the predictions of the model based on observed values of vegetation ground cover were also compared with predictions based on the simulated vegetation cover values. Finally, in order to evaluate the sediment transport model, predicted monthly erosion rates were also calculated using observed values of runoff and vegetation cover instead of simulated values. Moreover, in order to investigate the capability of PESERA to reproduce seasonal trends, the observed and simulated monthly runoff and erosion values were aggregated at different 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 variations are not well captured probably due to various reasons. The multistep approach showed that this is not only due to unrealistic simulation of cover and runoff, being erosion prediction also an important source of error. Although variability between the investigated 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.
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