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Elsevier, European Journal of Agronomy, (76), p. 149-159, 2016

DOI: 10.1016/j.eja.2015.11.004

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Integrating simulation data from a crop model in the development of an agri-environmental indicator for soil cover in Switzerland

Journal article published in 2015 by Lucie Büchi ORCID, Alain Valsangiacomo, Enguerrand Burel, Raphaël Charles
This paper is available in a repository.
This paper is available in a repository.

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Abstract

Agriculture generates important impacts on the environment, which can be evaluated with agri-environmental indicators. A key element of environment protection in agriculture is the maintenance of a dense soil cover for the longest possible period. Notably, soil cover is known to diminish erosion risks and nitrate leaching. In this study, an agri-environmental indicator for soil cover is presented, which integrates data from the crop model STICS to quantify vegetation growth dynamics. Simulations were conducted with STICS for the major crops cultivated in Switzerland across several contrasting pedoclimatic situations. They were then integrated with data for crop residue cover to evaluate soil cover at the field and farm levels in the framework of a farm network survey. At the field level, for the period from the harvest of the previous crop through the harvest of the main crop, the highest soil cover was achieved by silage maize and winter barley. A high variability between fields was observed, due to the diversity of cultural practices during the period preceding the seeding of the main crops. Some crops, winter wheat in particular, showed a high number of days with insufficient soil cover (under 30%), leading to potential environmental risks. This shows the crucial need of promoting conservation agriculture principles (permanent soil cover, minimum soil disturbance, diversification of crop rotation) in arable systems to better protect the soils and the environment. The soil cover indicator presented here provided a continuous quantification of soil cover, whereas most of the currently used indicators provide qualitative or roughly quantitative results.