An indicator to reflect the mitigating effect of Common Agricultural Policy on soil erosion
Introduction
Understanding the importance of harmonized pan-European assessment tools to estimate soil loss by water erosion (Robinson et al., 2017), Joint Research Centre (JRC) of the European Commission launched the LAND Use and Management model (LANDUM) in 2015 (Panagos et al., 2015a). LANDUM is the land use and land management component of the 100 m resolution RUSLE-based pan-European soil erosion risk modelling platform (Panagos et al., 2015b). The integrated cover-management factor (C) covers all 28 Member States of the European Union, in total 4.38 million km2, incorporating the information collected in the 2010 EU Farm Structure Survey (FSS) (Panagos et al., 2015a). In the (R)USLE-type equations (Alewell et al., 2019), C-factor estimates (or simulates) the combined effect of all interrelated land cover and land management measures (Wischmeier and Smith, 1965). It ranges from 0 to 1 depending on the ground cover representing the soil loss ratio (SLR). Generally, C-factor values close to zero are typically found in areas with up to 100 % ground cover whereas values close to one are typical for a bare plot (no vegetation) with till up and down the slope which is taken as a reference condition (C-factor = 1) (Borrelli et al., 2018a). Accordingly, the SLR is inversely proportional to the soil surface cover because soil surface cover intercepts raindrops and hinders surface runoff by slowing down rainwater.
According to RUSLE handbook (Renard et al., 1997), C-factor is a product of five sub-factors, i.e. canopy, surface cover, surface roughness, prior land use and antecedent soil moisture. In large-scale modelling applications, the estimation of the multiple C-factor sub-factor parameters and their dynamic change over time has traditionally been the most challenging component of the USLE-type equations (Borrelli et al., 2016; Schönbrodt et al., 2010). This has been critical as the C-factor together with the conversation support practice factor (P, describe the anthropogenic influence on the soil erosion process) is the key parameter to understand the delta between potential erosion under pristine and actual land conditions. In other words, the effect of cropping and management practices (hereinafter also referred to as measures) on erosion rates.
To date, C-factor calculation for large-scale RUSLE-based modelling applications generally relies on simple attributions of C-factor values derived from land use literature, digital cover maps (Bakker et al., 2008; Märker et al., 2008; Borrelli et al., 2014, among others) or vegetation indices obtained from remote sensing (Schönbrodt et al., 2010; Zhang et al., 2011; Ganasri and Ramesh, 2016, among others). A review of existing techniques was recently published (Benavidez et al., 2018). LANDUM introduced a new hybrid approach based on information derived from experimental/ literature data combined with CORINE Land Cover (CLC) inventory, remote sensing data and agricultural inventory data to describe crop systems and management practices across Europe. This approach was subsequently replicated in the RUSLE-based Global Soil Erosion Modelling platform (GloSEM) (Borrelli et al., 2017).
This study aims to integrate the results of the 2016 EU Farm Structure Survey (FSS) in LANDUM in order to (i) derive a pan-European indicator on the recent developments of soil conservation practices across Europe (2010–2016) and (ii) estimate the effect of reduced tillage, cover crops and plant residues to reduce soil loss rates at NUTS2 and national level.
Section snippets
Material and methods
LANDUM model estimates annual C-factor values in arable and non-arable lands following two different approaches (Fig. 1). Lands such as bare rocks, wetlands, beaches, glaciers, water bodies and artificial areas are not taken into consideration given their negligible effect from a soil erosion prospective. Those non-erosive lands account c.a. 9.7 % of EU total lands. Arable and non-arable lands are spatially defined by pan-European CORINE Land Cover 2006 database (100 m cell size). The CORINE
C-factor map of 2016
The LANDUM-based modelling approach provides estimates of the RUSLE cover-management factor (also known as C-factor) on a 100 × 100 m grid cell basis for the erodible EU-28 land surface (ca. 0.39 billion cells; ∼3.9 million km2); covering ∼90.3 % of European Union’s land surface. Non-erodible surface (such as bare rocks, glaciers, large rivers, lakes, and urban areas) cover the remaining 9.7 % of the land surface and were described as ‘No Data’.
The average C-factor value predicted by LANDUM for
Conclusions
The LANDUM model integrates the best available pan-European datasets and estimates the RUSLE C-factor at NUTS2 level combining the extent, types and spatial distribution of crops, soil conservation measures, natural and semi-natural vegetation measured by satellite imaging with agricultural inventory data. The elaboration of the EU Farm Structure Survey data 2016 and CORINE Land Cover2012 in the GIS-based LANDUM model allowed to update the knowledge about the most recent changes in land use and
References (21)
- et al.
The response of soil erosion and sediment export to land-use change in four areas of Europe: the importance of landscape pattern
Geomorphology
(2008) - et al.
Effect of Good Agricultural and Environmental Conditions on erosion and soil organic carbon balance: a national case study
Land Use Policy
(2016) A step towards a holistic assessment of soil degradation in Europe: Coupling on-site erosion with sediment transfer and carbon fluxes
Environ. Res.
(2018)- et al.
Geoscience Frontiers Assessment of soil erosion by RUSLE model using remote sensing and GIS - a case study of Nethravathi Basin
Geosci. Front.
(2016) - et al.
Assessment of land degradation susceptibility by scenario analysis: a case study in Southern Tuscany, Italy
Geomorphology
(2008) - et al.
The new assessment of soil loss by water erosion in Europe
Environ. Sci. Policy
(2015) - et al.
European Soil Data Centre: response to European policy support and public data requirements
Land Use Policy
(2012) - et al.
Using the USLE: chances, challenges and limitations of soil erosion modelling
Int. Soil Water Conserv. Res.
(2019) - et al.
A Review of the (Revised) Universal Soil Loss Equation ((R)USLE): With a View to Increasing Its Global Applicability and Improving Soil Loss Estimates 6059–6086
(2018) - et al.
Modeling soil erosion and river sediment yield for an intermountain drainage basin of the Central Apennines, Italy
Catena
(2014)
Cited by (37)
Including land management in a European carbon model with lateral transfer to the oceans
2024, Environmental ResearchFrom regional to parcel scale: A high-resolution map of cover crops across Europe combining satellite data with statistical surveys
2023, Science of the Total EnvironmentA field parcel-oriented approach to evaluate the crop cover-management factor and time-distributed erosion risk in Europe
2023, International Soil and Water Conservation ResearchCitation Excerpt :Within the research domain of soil erosion modelling, the (Revised) Universal Soil Loss Equation ((R)USLE) crop cover and management factor (C-factor) links a relative erosion risk to the on-site land management decisions such as the cultivated crop, tillage method and cover crop application (Wischmeier & Smith, 1978). The parameter itself, along with its encapsulated information, has determined it a useful index for the majority of multi-scale global modelling studies (Borrelli et al., 2021), as well as, for example, broad-scale policy evaluations of the impact of the Common Agricultural Policy on soil erosion in Europe (Borrelli & Panagos, 2020). The implication of the seasonal effect of vegetation is incorporated into the C-factor by combining the temporal distribution of rainstorm energy with the protective vegetation cover at each phase of the crop-growth and management cycle.