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In mixed oak-beech forests in the undulating Keuper region of Luxembourg extensive areas of the forest floor are litter-free or covered with worm casts during many months of the year. This creates an opportunity for splash erosion or erosion by (saturation) overland flow. A systematic investigation of the occurrence and seasonality of the litter-free areas resulting from the action of the earthworm species Lumbricus terrestris, L. was undertaken in a forest with poorly to imperfectly drained, silty clay loam soils. This forest exhibits microtopographic depressions of a few hundred square metres which are damper than the immediate surroundings and which seem to favour the activity of L. terrestris. A vegetation survey showed that the depressions also have a slightly different vegetation from the immediate surroundings. The activity of L . terrestris, which pulls leaves from the surface into its hole, was followed by establishing 11 plots, 5 x 5 m in size, and surveying these with monthly intervals during a year. The percentage of bare soil ranged from zero during the winter for all plots to a maximum of 60 per cent in July and August for some plots. Rates of leaf removal were found to follow trends in soil moisture content. The relationship observed between the occurrence of bare soil and composition of the understorey vegetation allowed the vegetation map of the forest to be used to estimate the area of exposed soil.The effects of the cast producing species AUolobophoru nocturnu, Sav. and A. longa, Ude. were studied in a mixed oak-beech forest with sandy loam to sandy clay loam soils. These soils are moderately well drained. Cast production was measured within a fenced-off area of 50 x 45 m, in which 10 plots of 1 mZ each were located at random. A fine nylon netting 30 cm above the soil surface prevented splash erosion of the newly formed casts between the monthly visits. The cast material was collected, dried and weighed. Splash erosion of the casts was investigated with 50 cm high splash collectors. The percentage of bare soil in front of the splash boards was estimated from photographs. From the limited data available the yearly rate of cast production appears to be approximately 1.5 kg/m2 (15 ton/ha). No significant correlations were obtained so far in most cases between amount of soil caught in the splash traps and percentage of soil covered with worm casts.

Monte Carlo procedures were used to evaluate the effects of spatial variations in the values of the infiltration parameter on the results of the ANSWERS distributed runoff and erosion model. Simulation results obtained were compared with measured values. Field infiltration measurements indicated spatial correlation at much smaller distances than the size of an element. Therefore, at first only the error of the mean had to be taken into consideration for block infiltration rates. Consequently, not only single hydrographs were produced, but also error bands. Secondly, nine other hypothetical spatial correlation structures were also evaluated using Monte Carlo methods. In particular at low nugget variances, increasing spatial correlation of infiltration resulted in increasing coefficients of variation in model outputs.In general, rainstorms with low rainfall intensities were more difficult to simulate accurately than extreme events with high rainfall intensities. This is explained by the greater influence of the infiltration uncertainties at low rainfall intensities.

The linkage of the model ANSWERS and a Geographical Information System to simulate surface runoff and soil erosion is described. The GIS can be used to provide (such as slope and aspect), store, change, and display data needed for simulation models. Conservation scenarios can be designed within the CIS and evaluated by the model. The results can be compared with other scenarios and displayed in the CIS.Model output is very sensitive to small changes of several input variables, such as infiltration, antecedent soil moisture, and soil roughness. Detailed information about rainfall intensities during an event is needed. Sensitivity and insufficient input data make the validation of ANSWERS difficult. The major constraint for accurate modelling is the degree to which reliable location-specific estimates of the input variables can be made. As models are made increasingly realistic, they need more and better data, which are not always available.

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