Impact of coupled input data source-resolution and aggregation on contributions of high-yielding traits to simulated wheat yield.

ABSTRACT: High-yielding traits can potentially improve yield performance under climate change. However, data for these traits are limited to specific field sites. Despite this limitation, field-scale calibrated crop models for high-yielding traits are being applied over large scales using gridded weather and soil datasets. This study investigates the implications of this practice. The SIMPLACE modeling platform was applied using field, 1 km, 25 km, and 50 km input data resolution and sources, with 1881 combinations of three traits [radiation use efficiency (RUE), light extinction coefficient (K), and fruiting efficiency (FE)] for the period 2001-2010 across Germany. Simulations at the grid level were aggregated to the administrative units, enabling the quantification of the aggregation effect. The s

SUBMITTER: Rezaei EE 

PROVIDER: S-EPMC11455967 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature