This dataset contains simulated crop yields for wheat and maize under heat stress, drought stress, and unstressed and irrigated conditions across Germany (2012–2023), generated using the process-based ecosystem model LandscapeDNDC.

The data were produced through a two-step calibration procedure optimizing key growth parameters for both crops, and include district-level yield estimates. The dataset enables assessment of the relative contributions of heat and drought stress to crop yield variability and supports climate impact studies for Central European agriculture. All data are provided in standardized CSV and NetCDF formats with full metadata documentation. The dataset is freely available and intended for reuse in agricultural modeling, climate risk assessment, and related research applications.

GS suffixes: DE_default_ stands for standard stress routine - all stresses enabled

DE_nodrought_ means drought stress is not restricting plant growth

DE_noheat_.. means heat stress is not restricting plant growth

DE_nostress_.. means that neither heat nor droughtstress are restricting plant growth

DE_irri005_ means that theta for irrigation was set to 0.05 -> ~ half mitigation scenario

DE_irri015_ means that theta for irrigation was set to 0.15 -> full drought mitigation scenario

Xheatmultisite stands for calibration parameters from the multisite calibration

suffix parameter setup _best 5th best parameter set for wheat, "6th" best for maize (actually 5th best of the "old" version) _c1 1st best parameter set of both wheat and maize _c2 2nd best parameter set of both wheat and maize _c3 3rd best parameter set of both wheat and maize _c4 4th best parameter set of both wheat and maize _c5 5th best parameter set of both wheat and maize _wlogging site_list_Germany_Landkreis_Nstie_fixed_50_nrep0.csv links the data to districts.