Sensitivities of crop models to extreme weather conditions during flowering period demonstrated for maize and winter wheat in Austria

TLDR

This study extends a European model inter‑comparison by addressing uncertainties in crop models used to assess climate‑change impacts on agriculture. The authors compared seven widely used crop models to evaluate their sensitivity to heat and drought stress during the two‑week period following flowering in winter wheat and maize. Simulations were run at two Austrian sites over 2003–2004 with contrasting agro‑climatic conditions, varying soil management (ploughing vs minimum tillage), and applying defined temperature and precipitation perturbations to assess grain yield and soil moisture during the critical post‑flowering window. While most models produced similar yield trends across scenarios, they differed markedly in the magnitude of yield reductions under short‑term heat or drought, and they responded differently to tillage practices that altered soil water storage.

Abstract

SUMMARY The objective of the present study was to compare the performance of seven different, widely applied crop models in predicting heat and drought stress effects. The study was part of a recent suite of model inter-comparisons initiated at European level and constitutes a component that has been lacking in the analysis of sources of uncertainties in crop models used to study the impacts of climate change. There was a specific focus on the sensitivity of models for winter wheat and maize to extreme weather conditions (heat and drought) during the short but critical period of 2 weeks after the start of flowering. Two locations in Austria, representing different agro-climatic zones and soil conditions, were included in the simulations over 2 years, 2003 and 2004, exhibiting contrasting weather conditions. In addition, soil management was modified at both sites by following either ploughing or minimum tillage. Since no comprehensive field experimental data sets were available, a relative comparison of simulated grain yields and soil moisture contents under defined weather scenarios with modified temperatures and precipitation was performed for a 2-week period after flowering. The results may help to reduce the uncertainty of simulated crop yields to extreme weather conditions through better understanding of the models’ behaviour. Although the crop models considered (DSSAT, EPIC, WOFOST, AQUACROP, FASSET, HERMES and CROPSYST) mostly showed similar trends in simulated grain yields for the different weather scenarios, it was obvious that heat and drought stress caused by changes in temperature and/or precipitation for a short period of 2 weeks resulted in different grain yields simulated by different models. The present study also revealed that the models responded differently to changes in soil tillage practices, which affected soil water storage capacity.