Climate impacts on long-term silage maize yield in Germany

Abstract

In this study, we examine the impacts of climate change on variations in the long-term mean silage maize yield using a statistical crop model at the county level in Germany. The explanatory variables, which consider sub-seasonal effects, are soil moisture anomalies for June and August and precipitation and temperature for July. Climate projections from five regional climate models (RCMs) are used to simulate soil moisture with the mesoscale Hydrologic Model and force the statistical crop model. The results indicate an average yield reduction of −120 to −1050 (kilogram/hectare)/annum (kg ha −1 a −1 ) for the period 2021–2050 compared to the baseline period 1971–2000. The multi-model yield decreases between −370 and −3910 kg ha −1 a −1 until the end of the century (2070–2099). The maximum projected mean loss is less than 10% in magnitude of average yields in Germany in 1999–2015. The crop model shows a strong ability to project long-term mean yield changes but is not designed to capture inter-annual variations. Based on the RCM outcomes, July temperature and August soil moisture anomalies are the main factors for the projected yield anomalies. Furthermore, effects such as adaptation and CO 2 fertilization are not included in our model. Accounting for these might lead to a slight overall increase in the future silage maize yield of Germany.

Machine-learning methods to assess the effects of a non-linear damage spectrum taking into account soil moisture on winter wheat yields in Germany

“…For example, a global study based on processbased models for maize and wheat found that for most countries water stress is a major source of the observed yield variations (Frieler et al, 2017). It has also been shown that it is necessary to account for multiple adverse environmental conditions such as frost, heat, drought, and excessive soil moisture during sensitive growth phases (Trnka et al, 2014;Albers et al, 2017;Schauberger et al, 2017;Mäkinen et al, 2018;Peichl et al, 2018Peichl et al, , 2019. Furthermore, these effects are often mutually amplifying, which potentially increases the impact (Ben-Ari et al, 2018;Lu et al, 2018;Toreti et al, 2019;Zscheischler et al, 2018Zscheischler et al, , 2020.…”

“…In previous studies we have tried to approximate this nonlinear and complex damage spectrum by considering the subseasonal effects of hydro-meteorological variables such as temperature and soil moisture, applying however an econometric linear model neglecting sub-seasonal interaction of the features. This approach was very well able to project long-term mean yield changes but not the inter-annual variations caused by extreme conditions (Peichl et al, 2019). This study applies a statistical framework that takes into account a range of potentially harmful extreme environmental conditions.…”

Application of the governance disruptions framework to German agricultural soil policy

“…With respect to soils and agriculture, it is increasingly obvious that climate change will lead to more and longer drought periods in Central Europe (Samaniego et al, 2018), making adaptive changes to soil management necessary, e.g. shifts in crop rotations (Peichl et al, 2019) and increased reliance on irrigation (Riediger et al, 2016). Different climate adaptation options differ in their effects on soil functions (Hamidov et al, 2018).…”

Different drought types and the spatial variability in their hazard, impact, and propagation characteristics

“…Losses in agriculture are mostly attributed to low soil water availability and heat (see also e.g. Peichl et al, 2019), whereas the increased cost in irrigation relate to low (sub-)surface water levels and the consequent need to use alternative water sources. Impacts on forestry relate to tree growth and vitality and were associated with low soil moisture and groundwater levels in the impact reports, depending on the kind and age of the tree (e.g.…”