Evaluation of field-scale and catchment-scale soil erosion models

One of the tasks of the International Geosphere–Biosphere Programme–Global Change and Terrestrial Ecosystems (IGBP–GCTE) Soil Erosion Network is to determine the suitability of modelling approaches for the estimation of soil erosion under global change. To achieve this, current erosion models are being evaluated in a series of GCTE meetings. This paper presents a synthesis of results from the first two meetings, which focused upon models for soil erosion by water at field and catchment scales, respectively. Apart from this comparison, discussions were held on model use and quality. The main conclusions from these discussions are included here as well. For both sets of evaluations, common datasets which had been split into a `training setʹ and a `testing setʹ were prepared and distributed to the participating modellers. For the `testing setʹ data, measured values for runoff and sediment yield (field-scale models) or for erosion only (catchment-scale models) were withheld from the modellers. The data used for the field-scale evaluation represented 73 site-years from seven sites in three countries: six field-scale erosion models took part in the evaluation. For the catchment-scale evaluation, data for 10 events on a 40 ha catchment in the Netherlands was used to evaluate seven catchment models. Conclusions from both field-scale and catchment-scale exercises include the following:• ation is desirable for many models, and necessary for some. Calibration is most effective if the event(s) to be estimated lie inside the range of calibration events; discharge is generally better predicted than peak discharge and both are better predicted than sediment discharge; ntinuous-simulation models, long-term average results are better simulated than results for individual time periods. In general, results are less good for shorter time periods, although there are exceptions; for certain events models may not perform well (absolute results), correlation coefficients between observed and predicted values are acceptable (relative results); atchment scale, the predicted spatial runoff pattern is as important as a correct prediction of the net output; he discussions it was clear that additional `softʹ information, in particular regarding the change in soil structure as a result of agricultural activities and/or climate, greatly improves the quality of input data and model results.