• Energy Research

Climate change is expected to severely affect cropping systems and food production in many parts of the world unless local adaptation can ameliorate these impacts. Ensembles of crop simulation models can be useful tools for assessing if proposed adaptation options are capable of achieving target yields, whilst also quantifying the share of uncertainty in the simulated crop impact resulting from the crop models themselves. Although some studies have analysed the influence of ensemble size on model outcomes, the effect of ensemble composition has not yet been properly appraised. Moreover, results and derived recommendations typically rely on averaged ensemble simulation results without accounting sufficiently for the spread of model outcomes. Therefore, we developed an Ensemble Outcome Agreement (EOA) index, which analyses the effect of changes in composition and size of a multi-model ensemble (MME) to evaluate the level of agreement between MME outcomes with respect to a given hypothesis (e.g. that adaptation measures result in positive crop responses). We analysed the recommendations of a previous study performed with an ensemble of 17 crop models and testing 54 adaptation options for rainfed winter wheat (Triticum aestivum L.) at Lleida (NE Spain) under perturbed conditions of temperature, precipitation and atmospheric CO2 concentration. Our results confirmed that most adaptations recommended in the previous study have a positive effect. However, we also showed that some options did not remain recommendable in specific conditions if different ensembles were considered. Using EOA, we were able to identify the adaptation options for which there is high confidence in their effectiveness at enhancing yields, even under severe climate perturbations. These include substituting spring wheat for winter wheat combined with earlier sowing dates and standard or longer duration cultivars, or introducing supplementary irrigation, the latter increasing EOA values in all cases. There is low confidence in recovering yields to baseline levels, although this target could be attained for some adaptation options under moderate climate perturbations. Recommendations derived from such robust results may provide crucial information for stakeholders seeking to implement adaptation measures.

The article outlines the relationship between meteorological variables and the parts of an agroecosystem which might be significantly influenced by climate change in the Czech Republic. It describes the most often applied scenarios under which projections of changes in meteorological variables up to the year 2050 and their impacts on winter wheat and spring barley yields can be made. It outlines the probable impacts of drought as the most significant hydrometeorological extreme in field production. Finally, case-studies are presented of predicted changes in occurrence of European Corn Borer (Ostrinia nubilalis) and predicted changes location and area of zones suitable for the production of different crops.

This study explored the utility of the impact response surface (IRS) approach for investigating model ensemble crop yield responses under a large range of changes in climate. IRSs of spring and winter wheat Triticum aestivum yields were constructed from a 26-member ensemble of process-based crop simulation models for sites in Finland, Germany and Spain across a latitudinal transect. The sensitivity of modelled yield to systematic increments of changes in temperature (-2 to +9°C) and precipitation (-50 to +50%) was tested by modifying values of baseline (1981 to 2010) daily weather, with CO2 concentration fixed at 360 ppm. The IRS approach offers an effective method of portraying model behaviour under changing climate as well as advantages for analysing, comparing and presenting results from multi-model ensemble simulations. Though individual model behaviour occasionally departed markedly from the average, ensemble median responses across sites and crop varieties indicated that yields decline with higher temperatures and decreased precipitation and increase with higher precipitation. Across the uncertainty ranges defined for the IRSs, yields were more sensitive to temperature than precipitation changes at the Finnish site while sensitivities were mixed at the German and Spanish sites. Precipitation effects diminished under higher temperature changes. While the bivariate and multi-model characteristics of the analysis impose some limits to interpretation, the IRS approach nonetheless provides additional insights into sensitivities to inter-model and inter-annual variability. Taken together, these sensitivities may help to pinpoint processes such as heat stress, vernalisation or drought effects requiring refinement in future model development.

The paper evaluates fifty-year series of meteorological data measured at the experimental field station of Žabčice training farm belonging to Mendel University in Brno. The evaluated temperature and precipitation data from 1961 to 2010 were divided into the normal period of 1961–1990 and the subsequent period of twenty years from 1991 to 2010. In addition to the monthly data, different parts of the year were assessed and compared. The findings of this local study carried out in the warmest and also the driest locality in the Czech Republic imply a change in the development of climate. Ten of the twelve months show higher average temperatures in the last two decades and similarly, a change in the rainfall distribution during the year has been observed. The decline in rainfall can be seen in spring period while the increase is evident in summer time. The highest difference in monthly temperatures of the two evaluated time periods was recorded in July (1.4 °C) and in August (1.7 °C). In accordance with the scenarios of climate change, lower rainfall totals were recorded in spring months (April to June), which, along with the temperature increase, negatively affects the agroclimatic conditions of the plant growth and development at the time of the intensive biomass production.

The close relationship between the onset and severity of agricultural and hydrological drought is considered selfevident, yet relatively few studies have addressed the effects of applying agricultural drought adaptation to hydrological drought characteristics. The present study applies a model cascade capable of simultaneously considering the interactions between agricultural and hydrological droughts. The study area covers all river basins in the Czech Republic and includes the periods of 1956-2015 (baseline) and 2021-2080 (future). The model cascade was shown to explain 91% of the variability in the seasonal and annual accumulated runoff and allows for the analysis of increasing/maintaining/decreasing available water capacity (AWC) across the 133 defined basins with a total area of c. 78,000 km2. The study reports that the probability and extent of agricultural drought increased over the entire period with higher AWC scenario showing slower pace of such increase especially from April to June. The trends in the extent or severity of hydrological droughts were of low magnitude. The future climate has been projected through the use of ensembles of five global (CMIP5) and five regional (EURO-CORDEX) climate models. The results showed a significant increase in the duration of agricultural drought stress and in the area affected throughout the year, particularly in July-September. The hydrological drought response showed a marked difference between areas with a negative and positive climatic water balance, i.e., areas where long-term reference evapotranspiration exceeds long-term precipitation (negative climatic water balance) and where it does not (positive climatic water balance). The overall results indicate that increasing soil AWC would decrease the frequency and likely also impact of future agricultural droughts, especially during spring. This result would be especially true if the wetter winters predicted by some of the models materialized. Hydrological droughts at the country level are estimated to become more pronounced with increasing AWC, particularly in catchments with a negative climatic water balance.

Europe is, after Asia, the second largest producer of wheat in the world, and provides the largest share of barley. Wheat (and to a similar extent, barley) production in Europe increased by more than 6-fold during the 20th century. During the first half of the 20th century, this was driven by expanding the harvested area. This was followed, from the mid-20th century, by a massive increase in productivity that in many regions has stalled since 2000. However, it remains unclear what role climatic factors have played in these changes. Understanding the net impact of climatic trends over the past century would also aid in our understanding of the potential impact of future climate changes and in assessments of the potential for adaptation across Europe. In this study, we compiled information from several sources on winter wheat and spring barley yields and climatological data from 12 countries/regions covering the period from 1901-2012. The studied area includes the majority of climatic regions in which wheat and barley are grown (from central Italy to Finland). We hypothesized that changes in climatic conditions have led to measurable shifts in climate-yield relationships over the past 112 yr, and that presently grown wheat and barley show a more pronounced response to adverse weather conditions compared to crops from the early 20th century. The results confirm that climate-yield relationships have changed significantly over the period studied, and that in some regions, different predictors have had a greater effect on yields in recent times (between 1991 and 2012) than in previous decades. It is likely that changes in the climate-yield relationship at the local level might be more pronounced than those across the relatively large regions used in this study, as the latter represents aggregations of yields from various agroclimatic and pedoclimatic conditions that may show opposing trends.

Adaptation of crops to climate change has to be addressed locally due to the variability of soil, climate and the specific socio-economic settings influencing farm management decisions. Adaptation of rainfed cropping systems in the Mediterranean is especially challenging due to the projected decline in precipitation in the coming decades, which will increase the risk of droughts. Methods that can help explore uncertainties in climate projections and crop modelling, such as impact response surfaces (IRSs) and ensemble modelling, can then be valuable for identifying effective adaptations. Here, an ensemble of 17 crop models was used to simulate a total of 54 adaptation options for rainfed winter wheat (Triticum aestivum) at Lleida (NE Spain). To support the ensemble building, an ex post quality check of model simulations based on several criteria was performed. Those criteria were based on the “According to Our Current Knowledge” (AOCK) concept, which has been formalized here. Adaptations were based on changes in cultivars and management regarding phenology, vernalization, sowing date and irrigation. The effects of adaptation options under changed precipitation (P), temperature (T), [CO2] and soil type were analysed by constructing response surfaces, which we termed, in accordance with their specific purpose, adaptation response surfaces (ARSs). These were created to assess the effect of adaptations through a range of plausible P, T and [CO2] perturbations. The results indicated that impacts of altered climate were predominantly negative. No single adaptation was capable of overcoming the detrimental effect of the complex interactions imposed by the P, T and [CO2] perturbations except for supplementary irrigation (sI), which reduced the potential impacts under most of the perturbations. Yet, a combination of adaptations for dealing with climate change demonstrated that effective adaptation is possible at Lleida. Combinations based on a cultivar without vernalization requirements showed good and wide adaptation potential. Few combined adaptation options performed well under rainfed conditions. However, a single sI was sufficient to develop a high adaptation potential, including options mainly based on spring wheat, current cycle duration and early sowing date. Depending on local environment (e.g. soil type), many of these adaptations can maintain current yield levels under moderate changes in T and P, and some also under strong changes. We conclude that ARSs can offer a useful tool for supporting planning of field level adaptation under conditions of high uncertainty.