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Spatially Explicit Soil Compaction Risk Assessment of Arable Soils at Regional Scale: The SaSCiA-Model

Author

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  • Michael Kuhwald

    (Department of Geography, Landscape Ecology and Geoinformation Science, Kiel University, Ludewig-Meyn-Str. 14, 24118 Kiel, Germany)

  • Katja Dörnhöfer

    (Department of Geography, Earth Observation and Modelling, Kiel University, Ludewig-Meyn-Str. 14, 24118 Kiel, Germany)

  • Natascha Oppelt

    (Department of Geography, Earth Observation and Modelling, Kiel University, Ludewig-Meyn-Str. 14, 24118 Kiel, Germany)

  • Rainer Duttmann

    (Department of Geography, Landscape Ecology and Geoinformation Science, Kiel University, Ludewig-Meyn-Str. 14, 24118 Kiel, Germany)

Abstract

Soil compaction caused by field traffic is one of the main threats to agricultural landscapes. Compacted soils have a reduced hydraulic conductivity, lower plant growth and increased surface runoff resulting in numerous environmental issues such as increased nutrient leaching and flood risk. Mitigating soil compaction, therefore, is a major goal for a sustainable agriculture and environmental protection. To prevent undesirable effects of field traffic, it is essential to know where and when soil compaction may occur. This study developed a model for soil compaction risk assessment of arable soils at regional scale. A combination of (i) soil, weather, crop type and machinery information; (ii) a soil moisture model and (iii) soil compaction models forms the SaSCiA-model (Spatially explicit Soil Compaction risk Assessment). The SaSCiA-model computes daily maps of soil compaction risk and associated area statistics for varying depths at actual field conditions and for entire regions. Applications with open access data in two different study areas in northern Germany demonstrated the model’s applicability. Soil compaction risks strongly varied in space and time throughout the year. SaSCiA allows a detailed spatio-temporal analysis of soil compaction risk at the regional scale, which exceed those of currently available models. Applying SaSCiA may support farmers, stakeholders and consultants in making decision for a more sustainable agriculture.

Suggested Citation

  • Michael Kuhwald & Katja Dörnhöfer & Natascha Oppelt & Rainer Duttmann, 2018. "Spatially Explicit Soil Compaction Risk Assessment of Arable Soils at Regional Scale: The SaSCiA-Model," Sustainability, MDPI, vol. 10(5), pages 1-29, May.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:5:p:1618-:d:147246
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    1. Nendel, C. & Berg, M. & Kersebaum, K.C. & Mirschel, W. & Specka, X. & Wegehenkel, M. & Wenkel, K.O. & Wieland, R., 2011. "The MONICA model: Testing predictability for crop growth, soil moisture and nitrogen dynamics," Ecological Modelling, Elsevier, vol. 222(9), pages 1614-1625.
    2. Jacobs, Anna & Auburger, Sebastian & Bahrs, Enno & Brauer-Siebrecht, Wiebke & Christen, Olaf & Götze, Philipp & Koch, Heinz-Josef & Mußhoff, Oliver & Rücknagel, Jan & Märländer, Bernward, 2017. "Replacing silage maize for biogas production by sugar beet – A system analysis with ecological and economical approaches," Agricultural Systems, Elsevier, vol. 157(C), pages 270-278.
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    Cited by:

    1. Thorsten Ruf & Mario Gilcher & Thomas Udelhoven & Christoph Emmerling, 2021. "Implications of Bioenergy Cropping for Soil: Remote Sensing Identification of Silage Maize Cultivation and Risk Assessment Concerning Soil Erosion and Compaction," Land, MDPI, vol. 10(2), pages 1-16, January.
    2. Monika Vilkiene & Ieva Mockeviciene & Grazina Kadziene & Danute Karcauskiene & Regina Repsiene & Ona Auskalniene, 2023. "Bacterial Communities: Interaction to Abiotic Conditions under Effect of Anthropogenic Pressure," Sustainability, MDPI, vol. 15(14), pages 1-15, July.
    3. Sandra Ledermüller & Marco Lorenz & Joachim Brunotte & Norbert Fröba, 2018. "A Multi-Data Approach for Spatial Risk Assessment of Topsoil Compaction on Arable Sites," Sustainability, MDPI, vol. 10(8), pages 1-22, August.
    4. Michael Kuhwald & Wolfgang B. Hamer & Joachim Brunotte & Rainer Duttmann, 2020. "Soil Penetration Resistance after One-Time Inversion Tillage: A Spatio-Temporal Analysis at the Field Scale," Land, MDPI, vol. 9(12), pages 1-21, December.
    5. Nandor Csikos & Malte Schwanebeck & Michael Kuhwald & Peter Szilassi & Rainer Duttmann, 2019. "Density of Biogas Power Plants as An Indicator of Bioenergy Generated Transformation of Agricultural Landscapes," Sustainability, MDPI, vol. 11(9), pages 1-23, April.

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