Bunzel et al. (2014) studied landscape parameters driving aquatic pesticide exposure and effects in four Federal States of Germany using an index to identify regions with high potential negative effects for macroinvertebrates. Both, forested upstream reaches and riparian buffer strips >5 m had reducing effects on the pesticide risk to macroinvertebrates.
Soil loss rates decrease exponentially as vegetation cover increases. Other land use and management factors affect soil loss, e. g. type of crop and tillage practice. The C-factor (cover-management factor) is one parameter out of five to estimate risk of soil erosion within the Universal Soil Loss Equation (USLE) and its revised version, the RUSLE. In comparison to bare fallow land, the C-factor describes how land cover, crops and crop management cause soil loss. Calculated soil loss ratios (SLRs) are computed as a product of five sub-factors: prior land use, canopy cover, surface cover, surface roughness and soil moisture. These sub-factors include variables, such as residue cover, canopy cover, canopy height, below-ground biomass (root mass plus incorporated residue) and time. The SLRs are calculated for several time intervals during a year and multiplied by the corresponding percentage of annual rainfall erosivity to estimate the C-factor. This approach is feasible on plot- to field scale.
For larger spatial scales, simplified methods, like assigning uniform C-factors from literature to a landcover map, or mapping vegetation parameters using image classification, were developed.
LANDUM, a hybrid C-factor land use and management model covers an area of 4,381,376 km² of EU-28 (Panagos et al., 2015). The model is based on a literature review, remote sensing data at high spatial resolution (e. g. CORINE land cover), and statistical data on agricultural and management practices. The model is designed as tool for policy makers to assess the effect of future land use and crop rotation scenarios on soil erosion by water. The impact of land use changes (deforestation, arable land expansion) and the effect of policies can potentially be quantified with LANDUM. The C-factor data and the statistical input data used are available from the European Soil Data Centre (Panagos et al., 2015).
Factors describing the degree of soil cover by vegetation therefore could be useful as indicator for erosion and thus for pesticide and nitrogen runoff.