IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i5p1618-d147246.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/5/1618/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/10/5/1618/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hampf, Anna C. & Carauta, Marcelo & Latynskiy, Evgeny & Libera, Affonso A.D. & Monteiro, Leonardo & Sentelhas, Paulo & Troost, Christian & Berger, Thomas & Nendel, Claas, 2018. "The biophysical and socio-economic dimension of yield gaps in the southern Amazon – A bio-economic modelling approach," Agricultural Systems, Elsevier, vol. 165(C), pages 1-13.
    2. Carauta, Marcelo & Troost, Christian & Guzman-Bustamante, Ivan & Hampf, Anna & Libera, Affonso & Meurer, Katharina & Bönecke, Eric & Franko, Uwe & Ribeiro Rodrigues, Renato de Aragão & Berger, Thomas, 2021. "Climate-related land use policies in Brazil: How much has been achieved with economic incentives in agriculture?," Land Use Policy, Elsevier, vol. 109(C).
    3. Carauta, Marcelo & Parussis, Julia & Hampf, Anna & Libera, Affonso & Berger, Thomas, 2021. "No more double cropping in Mato Grosso, Brazil? Evaluating the potential impact of climate change on the profitability of farm systems," Agricultural Systems, Elsevier, vol. 190(C).
    4. De Menna, Fabio & Malagnino, Remo Alessio & Vittuari, Matteo & Segrè, Andrea & Molari, Giovanni & Deligios, Paola A. & Solinas, Stefania & Ledda, Luigi, 2018. "Optimization of agricultural biogas supply chains using artichoke byproducts in existing plants," Agricultural Systems, Elsevier, vol. 165(C), pages 137-146.
    5. Tadiello, Tommaso & Gabbrielli, Mara & Botta, Marco & Acutis, Marco & Bechini, Luca & Ragaglini, Giorgio & Fiorini, Andrea & Tabaglio, Vincenzo & Perego, Alessia, 2023. "A new module to simulate surface crop residue decomposition: Description and sensitivity analysis," Ecological Modelling, Elsevier, vol. 480(C).
    6. Galmarini, S. & Solazzo, E. & Ferrise, R. & Srivastava, A. Kumar & Ahmed, M. & Asseng, S. & Cannon, A.J. & Dentener, F. & De Sanctis, G. & Gaiser, T. & Gao, Y. & Gayler, S. & Gutierrez, J.M. & Hoogenb, 2024. "Assessing the impact on crop modelling of multi- and uni-variate climate model bias adjustments," Agricultural Systems, Elsevier, vol. 215(C).
    7. Martin Schmidt & Claas Nendel & Roger Funk & Matthew G. E. Mitchell & Gunnar Lischeid, 2019. "Modeling Yields Response to Shading in the Field-to-Forest Transition Zones in Heterogeneous Landscapes," Agriculture, MDPI, vol. 9(1), pages 1-15, January.
    8. 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.
    9. Tenreiro, Tomás R. & García-Vila, Margarita & Gómez, José A. & Jimenez-Berni, José A. & Fereres, Elías, 2020. "Water modelling approaches and opportunities to simulate spatial water variations at crop field level," Agricultural Water Management, Elsevier, vol. 240(C).
    10. Robert Bedoić & Goran Smoljanić & Tomislav Pukšec & Lidija Čuček & Davor Ljubas & Neven Duić, 2021. "Geospatial Analysis and Environmental Impact Assessment of a Holistic and Interdisciplinary Approach to the Biogas Sector," Energies, MDPI, vol. 14(17), pages 1-20, August.
    11. Pasquel, Daniel & Cammarano, Davide & Roux, Sébastien & Castrignanò, Annamaria & Tisseyre, Bruno & Rinaldi, Michele & Troccoli, Antonio & Taylor, James A., 2023. "Downscaling the APSIM crop model for simulation at the within-field scale," Agricultural Systems, Elsevier, vol. 212(C).
    12. Jin, Xiuliang & Li, Zhenhai & Feng, Haikuan & Ren, Zhibin & Li, Shaokun, 2020. "Estimation of maize yield by assimilating biomass and canopy cover derived from hyperspectral data into the AquaCrop model," Agricultural Water Management, Elsevier, vol. 227(C).
    13. Yin, Xiaogang & Kersebaum, Kurt Christian & Kollas, Chris & Manevski, Kiril & Baby, Sanmohan & Beaudoin, Nicolas & Öztürk, Isik & Gaiser, Thomas & Wu, Lianhai & Hoffmann, Munir & Charfeddine, Monia & , 2017. "Performance of process-based models for simulation of grain N in crop rotations across Europe," Agricultural Systems, Elsevier, vol. 154(C), pages 63-77.
    14. Hampf, Anna C. & Stella, Tommaso & Berg-Mohnicke, Michael & Kawohl, Tobias & Kilian, Markus & Nendel, Claas, 2020. "Future yields of double-cropping systems in the Southern Amazon, Brazil, under climate change and technological development," Agricultural Systems, Elsevier, vol. 177(C).
    15. Carauta, M. & Guzman-Bustamante, I. & Meurer, K. & Hampf, A. & Troost, C. & Rodrigues, R. & Berger, T., 2018. "Assessing the full distribution of greenhouse gas emissions from crop, livestock and commercial forestry plantations in Brazil's Southern Amazon," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277118, International Association of Agricultural Economists.
    16. Xenia Specka & Claas Nendel & Ralf Wieland, 2019. "Temporal Sensitivity Analysis of the MONICA Model: Application of Two Global Approaches to Analyze the Dynamics of Parameter Sensitivity," Agriculture, MDPI, vol. 9(2), pages 1-29, February.
    17. Joseph MacPherson & Carsten Paul & Katharina Helming, 2020. "Linking Ecosystem Services and the SDGs to Farm-Level Assessment Tools and Models," Sustainability, MDPI, vol. 12(16), pages 1-19, August.
    18. Yuexia Sun & Shuai Zhang & Fulu Tao & Rashad Aboelenein & Alia Amer, 2022. "Improving Winter Wheat Yield Forecasting Based on Multi-Source Data and Machine Learning," Agriculture, MDPI, vol. 12(5), pages 1-16, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:10:y:2018:i:5:p:1618-:d:147246. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.