Impact of spatial soil and climate input data aggregation on regional yield simulations

Abstract

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by

Keywords

model variability; spatial variability; temporal variability; crop specific aggregation effects

Published in

PLoS ONE
2016, volume: 11, number: 4, article number: e0151782
Publisher: Public Library of Science

SLU Authors

• Coucheney, Elsa

  • Department of Soil and Environment, Swedish University of Agricultural Sciences
    

• Eckersten, Henrik

  • Department of Crop Production Ecology, Swedish University of Agricultural Sciences
    

• Lewan, Elisabet

  • Department of Soil and Environment, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Agricultural Science

Publication identifier

• DOI: https://doi.org/10.1371/journal.pone.0151782

Permanent link to this page (URI)

https://res.slu.se/id/publ/78399