Cover Management Factor

What is Cover Management (C-factor)?

Besides vegetation cover, several other land use and management factors affect soil loss, such as type of crop, tillage practice, etc.The influence of land use and management is often parameterisedin the cover-management factor (C-factor). The C-factor is amongthe five factors that are used to estimate the risk of soil erosionwithin the Universal Soil Loss Equation (USLE) and its revised version, the RUSLE. The C-factor is perhaps the most important factorwith regard to policy and land use decisions, as it represents con-ditions that can be most easily managed to reduce erosion. C-factor accounts for how land cover, crops and crop management cause soil loss to vary from those losses occurring in bare fallow areas. The C-factor is perhaps the most important factor with regard to policy and land use decisions, as it represents conditions that can be most easily managed to reduce erosion. The bare plot (novegetation) with till up and down the slope is taken as a referencecondition, with a C-factor value of 1. The soil loss from differentland-cover types is compared to the loss from the reference plotand the results are given as a ratio. The C-factor value for a par-ticular land-cover type is the weighted average of those soil lossratios (SLRs), and ranges between 0 and 1. A hybrid C-factor Land Use and Management (LANDUM) model has been developed for this European-scale study.

LANDUM model

Land Use and Management (LANDUM) model is based on a literature review, remote sensing data at high spatial resolution, and statistical data on agricultural and management practices. The LANDUM model for C-factor estimation is differentiated between a) arable lands and b) all other land uses (non-arable). In arable lands, the C-factor is estimated based on the crop composition at Regional level. Using the crop statistics from EUROSTAT for 17 crops, we have calculated the C-factor value in arable lands per NUTS2 region. In a second step, we quantify the effect of management practices (tillage practices, cover crops, plant residues) on reducing soil loss from agricultural lands. In non-arable lands, the C-factor is assigned to a range of values based on the literature review. Then, we have used Remote Sensing data (Vegetation density) as a proxy to calibrate at a pixel level the C-factor. The influence of vegetation density can be quantified by the use of biophysical parameters derived from MERIS satellite images

C-factor in Europe

Land use and management influence the magnitude of soil loss. Among the different soil erosion risk factors, the cover-management factor (C-factor) is the one that policy makers and farmers can most readily influence in order to help reduce soil loss rates. The present study proposes a methodology for estimating the C-factor in the European Union (EU), using pan-European datasets (such as CORINE Land Cover), biophysical attributes derived from remote sensing, and statistical data on agricultural crops and practices. In arable lands, the C-factor was estimated using crop statistics (% of land per crop) and data on management practices such as conservation tillage, plant residues and winter crop cover. The C-factor in non-arable lands was estimated by weighting the range of literature values found according to fractional vegetation cover, which was estimated based on the remote sensing dataset Fcover. The mean C-factor in the EU is estimated to be 0.1043, with an extremely high variability; forests have the lowest mean C-factor (0.00116), and arable lands and sparsely vegetated areas the highest (0.233 and 0.2651 respectively). Conservation management practices (reduced/no tillage, use of cover crops and plant residues) reduce the C-factor by on average 19.1% in arable lands. The methodology is designed to be a 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 (such as the Common Agricultural Policy and the push to grow more renewable energy crops) can potentially be quantified with the proposed model. The C-factor data per land use and country can be found in the publication while the C-factor maps (at 100m pixel resolution) are available for download here.

Data

 The C-factor dataset is in Raster format. The public user can download 2 datasets: 

  1. Cover management factor (C-factor) in the European Union at 100m resolution
  2.  A shapefile where the user can map the:
  •  Cover-Management factor (C-factor) in arable lands at regional (NUTS2) level in the European Union
  •  Influence of Tillage practices on C-factor reduction
  •  Influence of plant residues on C-factor reduction
  •  Influence of cover crops on C-factor reduction

To get access to the data, please compile the Request form; instructions will then follow how to download the datasets

 Information: Panos Panagos and Pasquale Borrelli
European Commission, Institute of Environment and Sustainability, Land Resource Management Unit

References:
A complete description of the methodology and the application in Europe is described in the paper:
Panagos, P., Borrelli, P., Meusburger, C., Alewell, C., Lugato, E., Montanarella, L., 2015. Estimating the soil erosion cover-management factor at European scale. Land Use policy journal. 48C, 38-50. , doi:10.1016/j.landusepol.2015.05.021 

 

C-factor

Fig. 1:C-factor map of the European Union

 

Tillage Practices Plant Residues Cover Crops

Fig. 2: Infuence of Tillage Practices, Plant Residues and Cover Crops in reducing soil erosion.

 

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Title: Soil erosion by water (RUSLE2015)
Resource Type: Datasets, Soil Threats Data
Theme/Sub-Theme:
Network/Cooperations:
Project/s:
Registration requested: Request Form
Continent:
Year: 2015
Scale:
Keywords:

Title: Cover Management factor (C-factor) for the EU
Resource Type: Datasets, Soil Threats Data
Theme/Sub-Theme:
Network/Cooperations:
Project/s:
Registration requested: Request Form
Continent:
Year: 2015
Publisher: European Commission, Joint Research Centre
Scale:
Keywords: