Preprints
https://doi.org/10.5194/egusphere-2024-4087
https://doi.org/10.5194/egusphere-2024-4087
29 Jan 2025
 | 29 Jan 2025
Status: this preprint is open for discussion and under review for Biogeosciences (BG).

Grassland yield estimations – potentials and limitations of remote sensing, process-based modelling and field measurements

Sophie Reinermann, Carolin Boos, Andrea Kaim, Anne Schucknecht, Sarah Asam, Ursula Gessner, Sylvia H. Annuth, Thomas M. Schmitt, Thomas Koellner, and Ralf Kiese

Abstract. Grasslands make up the majority of agricultural land and provide fodder for livestock. Information on grassland yield is very limited as the fodder is directly used at the farms. Data on grassland yields would be needed, however, to inform politics and stakeholders on grassland ecosystem services and inter-annual variations. Grassland yield patterns are often varying on small scales in Germany and estimations are further complicated by missing information on grassland management. Here, we present three different approaches to estimate annual grassland yield for a study region in southern Germany. We apply (i) a model derived from field samples, satellite data and mowing information (RS), (ii) the biogeochemical process-based model LandscapeDNDC (LDNDC) and (iii) a rule-set approach based on field measurements and spatial information on grassland productivity (RVA) to derive grassland yields per parcel for the Ammer catchment area in 2019. All three approaches reach plausible results of annual yields of around 4–9 t/ha and show overlapping as well as diverging spatial patterns. For example, direct comparisons show that higher yields were derived with LDNDC compared to RS and RVA, in particular related to the first cut and for grasslands mown only one or two times per year. The mowing frequency was found to be the most important influencing factor for grassland yields of all three approaches. There were no significant differences found in the effect of abiotic influencing factors, such as climate or elevation, on grassland yields derived from the different approaches. The potentials and limitations of the three approaches are analysed and discussed in depth, such as the level of detail of required input data, or the capability of regional and inter-annual yield estimations. For the first time, three different approaches to estimate grassland yields were compared in depth resulting in new insights in their potentials and limitations. Grassland productivity maps provide the basis for long-term analyses of climate and management impacts and comprehensive studies of the functions of grassland ecosystems.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Share
Sophie Reinermann, Carolin Boos, Andrea Kaim, Anne Schucknecht, Sarah Asam, Ursula Gessner, Sylvia H. Annuth, Thomas M. Schmitt, Thomas Koellner, and Ralf Kiese

Status: open (until 12 Mar 2025)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Sophie Reinermann, Carolin Boos, Andrea Kaim, Anne Schucknecht, Sarah Asam, Ursula Gessner, Sylvia H. Annuth, Thomas M. Schmitt, Thomas Koellner, and Ralf Kiese
Sophie Reinermann, Carolin Boos, Andrea Kaim, Anne Schucknecht, Sarah Asam, Ursula Gessner, Sylvia H. Annuth, Thomas M. Schmitt, Thomas Koellner, and Ralf Kiese

Viewed

Total article views: 84 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
66 14 4 84 1 1
  • HTML: 66
  • PDF: 14
  • XML: 4
  • Total: 84
  • BibTeX: 1
  • EndNote: 1
Views and downloads (calculated since 29 Jan 2025)
Cumulative views and downloads (calculated since 29 Jan 2025)

Viewed (geographical distribution)

Total article views: 62 (including HTML, PDF, and XML) Thereof 62 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 06 Feb 2025
Download
Short summary
Grasslands shape the landscape in many parts of the world and serve as the main source of fodder for livestock. There is a lack of comprehensive data on grassland yield, though highly valuable for authorities and research. By applying three approaches to estimate grassland yields, namely a satellite data model, a biogeochemical model and a field measurements approach, we provide annual grassland yield maps for the Ammer region in 2019 and highlight potentials and limitations of the approaches.
Share