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  Generating a rule-based global gridded tillage dataset

Porwollik, V., Rolinski, S., Heinke, J., Müller, C. (2019): Generating a rule-based global gridded tillage dataset. - Earth System Science Data, 11, 2, 823-843.
https://doi.org/10.5194/essd-11-823-2019

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Porwollik, Vera1, Author              
Rolinski, Susanne1, Author              
Heinke, Jens1, Author              
Müller, Christoph1, Author              
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1Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: Tillage is a central element in agricultural soil management and has direct and indirect effects onprocesses in the biosphere. Effects of agricultural soil management can be assessed by soil, crop, and ecosystemmodels, but global assessments are hampered by lack of information on the type of tillage and their spatialdistribution. This study describes the generation of a classification of tillage practices and presents the spatiallyexplicit mapping of these crop-specific tillage systems for around the year 2005.Tillage practices differ by the kind of equipment used, soil surface and depth affected, timing, and their pur-pose within the cropping systems. We classified the broad variety of globally relevant tillage practices intosix categories: no-tillage in the context of Conservation Agriculture, traditional annual, traditional rotational,rotational, reduced, and conventional annual tillage. The identified tillage systems were allocated to griddedcrop-specific cropland areas with a resolution of 5 arcmin. Allocation rules were based on literature findings andcombine area information on crop type, water management regime, field size, water erosion, income, and aridity.We scaled reported national Conservation Agriculture areas down to grid cells via a probability-based approachfor 54 countries. We provide area estimates of the six tillage systems aggregated to global and country scale. Wefound that 8.67 Mkm2of global cropland area was tilled intensively at least once a year, whereas the remaining2.65 Mkm2was tilled less intensely. Further, we identified 4.67 Mkm2of cropland as an area where ConservationAgriculture could be expanded to under current conditions.The tillage classification enables the parameterization of different soil management practices in various kindsof model simulations. The crop-specific tillage dataset indicates the spatial distribution of soil managementpractices, which is a prerequisite to assess erosion, carbon sequestration potential, as well as water, and nutrientdynamics of cropland soils. The dynamic definition of the allocation rules and accounting for national statistics,such as the share of Conservation Agriculture per country, also allow for derivation of datasets for historical andfuture global soil management scenarios. The resulting tillage system dataset and source code are accessible viaan open-data repository (DOIs: https://doi.org/10.5880/PIK.2019.009 and https://doi.org/10.5880/PIK.2019.010,Porwollik et al., 2019a, b).

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 Dates: 2019
 Publication Status: Finally published
 Pages: -
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 Rev. Type: Peer
 Identifiers: DOI: 10.5194/essd-11-823-2019
PIKDOMAIN: RD2 - Climate Resilience
eDoc: 8350
Research topic keyword: Mitigation
Research topic keyword: Sustainable Development
Model / method: Open Source Software
Model / method: LPJmL
Regional keyword: Global
Organisational keyword: RD2 - Climate Resilience
Working Group: Land Use and Resilience
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Title: Earth System Science Data
Source Genre: Journal, SCI, Scopus, p3, oa
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Pages: - Volume / Issue: 11 (2) Sequence Number: - Start / End Page: 823 - 843 Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals2_126
Publisher: Copernicus