This study presents a sensitivity analysis of the soil erosion model LISEM, whereby not only the sensitivity to parameter values is considered, but attention is focused on the effects of process descriptions and the routing of overland flow
. As erosion models include a wide range of processes (i.e. rainfall, interception, surface storage, overland flow, soil erosion and deposition), this implies that only a relatively small fraction of all possible variations is explored here.
Spatially distributed data for erosion model calibration and validation : the Ganspoel and Kinderveld datasets
Bassin-versant ; Belgique ; Distribution spatiale ; Ecoulement ; Erosion des sols ; Loess ; Modèle ; Précipitation ; Ravinement ; Utilisation agricole du sol
Agricultural land use ; Belgium ; Gully erosion ; Loess ; Model ; Precipitation ; Runoff ; Soil erosion ; Spatial distribution ; Watershed
The AA. describe a dataset that offers possibilities for improved evaluation and parameterisation of spatially distributed soil erosion models. The dataset combines rainfall, runoff and sediment discharge data collected at the outlet and field
surveys within the catchments that describe soil surface charcteristics and soil erosion features. The paper dicusses and illustrates the use of the dataset to narrow uncertainties associated with model predictions.
Belgique ; Erosion des sols ; Expérimentation ; Granulométrie ; Modèle ; Pente de versant ; Ruissellement ; Transport sédimentaire
Belgium ; Experimentation ; Grain size distribution ; Model ; Rill wash ; Sediment transport ; Slope gradient ; Soil erosion
specifically, the study investigates to what extent sediment deposition (both total mass and sediment quality) can be predicted using the simple theory for flows with a shear stress below the threshold value, and which modelling approach can best be used once