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Monthly RUSLE soil erosion risk of Swiss grasslands

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  • Simon Schmidt
  • Christine Alewell
  • Katrin Meusburger

Abstract

This study presents the first mapping of soil erosion risk modelling based on the Revised Universal Soil Loss Equation (RUSLE) at a sub-annual (monthly) temporal resolution and national scale (100 m spatial resolution). The monthly maps show highest water erosion rates on Swiss grasslands in August (1.25 t ha–1 month–1). In summer, the mean monthly soil loss by water erosion is 48 times higher than the mean soil loss in winter. Considering the annual average fraction of green vegetation cover of 54%, the predicted soil erosion rate for the Swiss national grassland area would add up to a total eroded soil mass of 5.26 Mt yr–1. The RUSLE application with an intact 100% vegetation cover would largely reduce the soil loss to an average annual rate of 0.14 t ha–1 year–1. These findings clearly highlight the importance to consider and maintain the current status of the vegetation cover for soil erosion prediction and soil conservation, respectively.

Suggested Citation

  • Simon Schmidt & Christine Alewell & Katrin Meusburger, 2019. "Monthly RUSLE soil erosion risk of Swiss grasslands," Journal of Maps, Taylor & Francis Journals, vol. 15(2), pages 247-256, July.
    • Handle: RePEc:taf:tjomxx:v:15:y:2019:i:2:p:247-256
    DOI: 10.1080/17445647.2019.1585980
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    File URL: http://hdl.handle.net/10.1080/17445647.2019.1585980
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    Cited by:

    1. Joly, Frédéric & Benoit, Marc & Martin, Raphael & Dumont, Bertrand, 2021. "Biological operability, a new concept based on ergonomics to assess the pertinence of ecosystem services optimization practices," Ecosystem Services, Elsevier, vol. 50(C).
    2. Ramakrishnan Sangeetha & Neelakanda Pillai Kanniperumal Ambujam, 2021. "The overshadow of the human evolvement process in the dynamics of soil drift of an agricultural watershed in Nilgiri Hills, India," Soil and Water Research, Czech Academy of Agricultural Sciences, vol. 16(2), pages 103-111.
    3. Jiří Šandera & Přemysl Štych, 2020. "Selecting Relevant Biological Variables Derived from Sentinel-2 Data for Mapping Changes from Grassland to Arable Land Using Random Forest Classifier," Land, MDPI, vol. 9(11), pages 1-20, October.
    4. Johannes Schmidt & Nik Usmar & Leon Westphal & Max Werner & Stephan Roller & Reinhard Rademacher & Peter Kühn & Lukas Werther & Aline Kottmann, 2023. "Erosion Modelling Indicates a Decrease in Erosion Susceptibility of Historic Ridge and Furrow Fields near Albershausen, Southern Germany," Land, MDPI, vol. 12(3), pages 1-11, February.
    5. Yamaura, Yuichi & Yamada, Yusuke & Matsuura, Toshiya & Tamai, Koji & Taki, Hisatomo & Sato, Tamotsu & Hashimoto, Shoji & Murakami, Wataru & Toda, Kenichiro & Saito, Hitoshi & Nanko, Kazuki & Ito, Erik, 2021. "Modeling impacts of broad-scale plantation forestry on ecosystem services in the past 60Â years and for the future," Ecosystem Services, Elsevier, vol. 49(C).

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