ALBERT

Description: SUMMARYThe present study is focused on the potential occurrence of the Colorado potato beetle (Leptinotarsa decemlineata, Say 1824), an important potato pest, and the European corn borer (Ostrinia nubilalis, Hübner 1796), the most important maize pest, during climate change. Estimates of the current potential distribution of both pest species as well as their distribution in the expected climate conditions are based on the CLIMEX model. The study covers central Europe, including Austria, the Czech Republic, Hungary, and parts of Germany, Poland, Romania, Slovakia, Switzerland, Ukraine, Slovenia, the northern parts of Serbia, parts of Croatia and northern Italy. The validated model of the pests’ geographical distribution was applied within the domain of the regional climate model (RCM) ALADIN, at a resolution of 10 km. The weather series that was the input for the CLIMEX model was prepared by a weather generator (WG) which was calibrated with the RCM-simulated weather series (for the period of 1961–90). To generate a weather series for two future time periods (2021–50 and 2071–2100), the WG parameters were modified according to 12 climate change scenarios produced by the pattern scaling method. The standardized scenarios derived from three global climate models (HadCM, NCAR-PCM and ECHAM) were scaled by low, middle and high values of global temperature change estimated by the Model for the Assessment of Greenhouse-gas Induced Climate Change (MAGICC) model (assuming three combinations of climatic sensitivity and emission scenarios). The results of present study suggest the likely widening of the pests’ habitats and an increase in the number of generations per year. According to the HadCM-high scenario, the area of arable land affected by a third generation per season of Colorado potato beetle in 2050 is c. 45% higher, and by a second generation of the European corn borer is nearly 61% higher, compared to present levels.

Description: SUMMARYThe objective of the present paper was to study the impact of climate change on grain yield, water balance, crop water productivity (CWP) and water requirements for the summer-sown maize in Faisalabad, Pakistan. Climate-change scenarios (Special Report on Emission Scenarios (SRES) A1B, A2 and B1) were derived from the general circulation model ECHAM 5 and the crop model CERES-Maize was used to simulate impacts of the applied climate scenarios. Calibration and validation of the crop models were carried out for the summer-sown maize in 2007 and for the spring-sown maize in 2008. Three predefined reduced irrigation scenarios were compared to traditional irrigation practices for the summer-sown maize. Under the current conditions, scenario S1 (one irrigation event skipped at the vegetative stage) showed a higher simulated yield than scenario S2 (one irrigation event skipped at the grain-filling stage) due to higher water drainage and nitrogen (N) leaching rates in scenario S2. Scenario S3 (irrigation events skipped at both crop establishment and the grain-filling stage) showed significantly higher grain yield because it had the lowest drainage and N leaching rates. In this irrigation scenario, 60 mm of water were saved compared to the other two scenarios, and much more water was saved compared to the traditional local regime.In the predicted climatic scenarios and with reduced irrigation, the simulated maize yields and crop water productivities were affected differently. For the period from 2036 to 2065, a more significant yield decrease was shown in all emission and irrigation scenarios. A yield decrease was simulated by both, including and not including the direct effect of elevated atmospheric CO2 concentrations on photosynthesis. However, the simulated direct effect of elevated CO2 was to produce higher yield and CWP in all scenarios. The highest grain yields and crop water productivities were achieved in the reduced irrigation scenario S3 for all emission scenarios and climatic periods for the same reason as under the current conditions (N leaching). However, the yield differences between the climate scenarios were mainly due to the shortening of the simulated growing period. This was caused by increased temperatures compared to current conditions. A shortened growing cycle reduced the potential time for biomass accumulation and in the present case it was not balanced by the CO2 fertilizing effect (without a potential change in maize cultivars).By simulating optimum yields (where automatic irrigation is determined by the model to receive optimum yield), under the current conditions it was found that 285 mm of irrigation would ensure the highest grain yield and CWP (30 mm more than under irrigation scenario S3). In this case, actual evapotranspiration reached 373 mm and less deep drainage and N leaching occurred. In the future climate scenarios, optimum yields and irrigation demands diminished depending on the emission scenario, but CWP increased slightly.The present simulation study shows a clear decreasing yield trend for autumn maize under a warm climate for each type of (unchanged) irrigation management due to the shortening of the growing period. However, in the current climate, as well as in the future climate scenarios, maize yield levels could be improved by optimized (and reduced) irrigation compared to traditional irrigation due to reduced N leaching. Even in the scenario with the highest warming trend (A1B emission scenario for the period 2036–65), the current yield levels could be kept or even improved.

Description: SUMMARYOne of the main problems in estimating the effects of climate change on crops is the identification of those factors limiting crop growth in a selected environment. Previous studies have indicated that considering simple trends of either precipitation or temperature for the coming decades is insufficient for estimating the climate impact on yield in the future. One reason for this insufficiency is that changes in weather extremes or seasonal weather patterns may have marked impacts.The present study focuses on identifying agroclimatic parameters that can identify the effects of climate change and variability on winter wheat yield change in the Pannonian lowland. The impacts of soil type under past and future climates as well as the effect of different CO2 concentrations on yield formation are also considered. The Vojvodina region was chosen for this case study because it is a representative part of the Pannonian lowland.Projections of the future climate were taken from the HadCM3, ECHAM5 and NCAR-PCM climate models with the SRES-A2 scenario for greenhouse gas (GHG) emissions for the 2040 and 2080 integration periods. To calibrate and validate the Met&Roll weather generator, four-variable weather data series (for six main climatic stations in the Vojvodina region) were analysed. The grain yield of winter wheat was calculated using the SIRIUS wheat model for three different CO2 concentrations (330, 550 and 1050 ppm) dependent on the integration period. To estimate the effects of climatic parameters on crop yield, the correlation coefficient between crop yield and agroclimatic indices was calculated using the AGRICLIM software. The present study shows that for all soil types, the following indices are the most important for winter wheat yields in this region: (i) the number of days with water and temperature stress, (ii) the accumulated precipitation, (iii) the actual evapotranspiration (ETa) and (iv) the water deficit during the growing season. The high positive correlations between yield and the ETa, accumulated precipitation and the ratio between the ETa and reference evapotranspiration (ETr) for the April–June period indicate that water is and will remain a major limiting factor for growing winter wheat in this region. Indices referring to negative impact on yield are (i) the number of days with a water deficit for the April–June period and (ii) the number of days with maximum temperature above 25 °C (summer days) and the number of days with maximum temperature above 30 °C (tropical days) in May and June. These indices can be seen as indicators of extreme weather events such as drought and heat waves.

Description: A probabilistic crop forecast based on ensembles of crop model output estimates, presented here, offers an ensemble of possible realizations and probabilistic forecasts of green water components, crop yield and green water footprints (WFs) on seasonal scales for selected summer crops. The present paper presents results of an ongoing study related to the application of ensemble forecasting concepts in crop production. Seasonal forecasting of crop water use indicators (evapotranspiration (ET), water productivity, green WF) and yield of rainfed summer crops (maize, spring barley and sunflower), was performed using the AquaCrop model and ensemble weather forecast, provided by The European Centre for Medium-range Weather Forecast. The ensemble of estimates obtained was tested with observation-based simulations to assess the ability of seasonal weather forecasts to ensure that accuracy of the simulation results was the same as for those obtained using observed weather data. Best results are obtained for ensemble forecast for yield, ET, water productivity and green WF for sunflower in Novi Sad (Serbia) and maize in Groß-Enzersdorf (Austria) – average root mean square error (2006–2014) was

Description: SUMMARYThe goal of the present study was to assess the impact of selected soil protection measures on soil erosion and retention of rainwater in a 1·14 km2 watershed used for agriculture in the north-east of Austria. Watershed conditions under conventional tillage (CT), no-till (NT) and under grassland use were simulated using the Water Erosion Prediction Project (WEPP) soil erosion model. The period 1961–90 was used as a reference and results were compared to future Intergovernmental Panel on Climate Change (IPCC) scenarios A1B and A2 (2040–60).The simulations for the NT and grassland options suggested runoff would decrease by 38 and 75%, respectively, under the current climatic conditions. The simulation results suggest that, under future climate scenarios, the effectiveness of the selected soil conservation measures with respect to runoff will be similar, or decreased by 16–53%.The actual average net soil losses in the watershed varied from 2·57 t/ha/yr for conventional soil management systems to 0.01 t/ha/yr for grassland. This corresponds to a maximum average annual loss of about 0·2 mm, which is considered to be the average annual soil formation rate and therefore an acceptable soil loss. The current soil/land use does not exceed this limit, with most of the erosion occurring during spring time. Under future climate scenarios, the simulations suggested that CT would either decrease soil erosion by up to 55% or increase it by up to 56%. Under these conditions, the acceptable limits will partly be exceeded. The simulations of NT suggested this would reduce annual soil loss rates (compared to CT) to 0·2 and 1·4 t/ha, i.e. about the same or slightly higher than for NT under actual conditions. The simulation of conversion to grassland suggested soil erosion was almost completely prevented.The selected soil conservation methods maintain their protective effect on soil resources, independent of the climate scenario. Therefore, with small adaptations, they can also be recommended as sustainable soil/land management systems under future climatic conditions.However, based on the available climate scenarios, climate-induced changes in the frequency and intensity of heavy rainstorms were only considered in a limited way in the present work. As the general future trend indicates a strong increase of rainstorms with high intensity during summer months, the results of the present study may be too optimistic.

Description: SUMMARYThe present study investigates regional climate change impacts on agricultural crop production in Central and Eastern Europe, including local case studies with different focuses in Austria, the Czech Republic and Slovakia. The area studied experiences a continental European climate and is characterized by strong climatic gradients, which may foster regional differences or trends in the impacts of climate change on agriculture. To study the regional aspects and variabilities of climate change impacts on agriculture, the effect of climate change on selected future agroclimatic conditions, crop yield and variability (including the effect of higher ambient CO2 concentrations) and the most important yield limiting factors, such as water availability, nitrogen balance and the infestation risks posed by selected pests were studied. In general, the results predicted significant agroclimatic changes over the entire area during the 21st century, affecting agricultural crop production through various pathways. Simulated crop yield trends confirmed past regional studies but also revealed that yield-limiting factors may change from region to region. For example, pest pressures, as demonstrated by examining two pests, are likely to increase due to warmer conditions. In general, higher potentials for cereal yield increase are seen for wetter and cooler regions (i.e. uplands) than for the drier and warmer lowlands, where yield potentials will be increasingly limited by decreasing crop water availability and heat under most scenarios. In addition, yield variability will increase during the coming decades, but this may decrease towards the end of the 21st century. The present study contributes to the interpretation of previously conducted climate change impact and adaptation studies for agriculture and may prove useful in proposing future research in this field.

Description: SUMMARYThe main objective of the present crop simulation study was to determine the impact of climate change on the winter wheat production of a dry area situated in north-east Austria (Marchfeld region) based on the CERES-Wheat crop-growth simulation model associated with global circulation models (GCMs). The effects of some of the feasible regional- and farm-based adaptation measures (management options) on crop yield and water and nitrogen (N) balance under the climate scenarios were simulated. Climate scenarios were defined based on the ECHAM5, HadCM3 and NCAR PCM GCM simulations for future conditions (2021–50) as described in the Special Report on Emission Scenarios A1B (Nakicenovic & Swart 2000). The potential development, yield, water demand and soil N leaching were estimated for winter wheat and all of the defined climates (including rising CO2 levels) and management scenarios (soil cultivation, windbreaks and irrigation).The results showed that a warming of 2°C in the air temperature would shorten the crop-growing period by up to 20 days and would decrease the potential winter wheat yield on nearly all of the soil types in the region. Particularly, high-yield reductions were projected for light-textured soils such as Parachernozems. A change from ploughing to minimum tillage within the future scenario would lead to an increase of up to 8% of the mean yield of winter wheat. This effect mainly resulted from improved water supply to the crop, associated with higher soil water storage capacity and decrease of unproductive water losses. Hedgerows, which reduce the wind speed, were predicted to have particularly positive effects on medium and moderately fine-textured soils such as Chernozems and Fluvisols. With both management changes, regional mean-yield level can be expected to be +4% in comparison with no management changes in the future conditions. Compared with the baseline period, water demand for the potential yield of winter wheat would require 6–37 mm more water per crop season (area-weighted average). The highest water demand would be on medium-textured soils, which make up the largest amount of area in the study region. Additionally, the effects of snow accumulation near hedgerows would further increase the yield, but would also lead to higher N leaching rates. However, specific management options, such as minimum tillage and hedgerows, could contribute towards reducing the increasing water demand.

Description: A probabilistic crop forecast based on ensembles of crop model output (CMO) estimates offers a myriad of possible realizations and probabilistic forecasts of green water components (precipitation and evapotranspiration), crop yields and green water footprints (GWFs) on monthly or seasonal scales. The present paper presents part of the results of an ongoing study related to the application of ensemble forecasting concepts for agricultural production. The methodology used to produce the ensemble CMO using the ensemble seasonal weather forecasts as the crop model input meteorological data without the perturbation of initial soil or crop conditions is presented and tested for accuracy, as are its results. The selected case study is for winter wheat growth in Austria and Serbia during the 2006–2014 period modelled with the SIRIUS crop model. The historical seasonal forecasts for a 6-month period (1 March-31 August) were collected for the period 2006–2014 and were assimilated from the European Centre for Medium-range Weather Forecast and the Meteorological Archival and Retrieval System. The seasonal ensemble forecasting results obtained for winter wheat phenology dynamics, yield and GWF showed a narrow range of estimates. These results indicate that the use of seasonal weather forecasting in agriculture and its applications for probabilistic crop forecasting can optimize field operations (e.g., soil cultivation, plant protection, fertilizing, irrigation) and takes advantage of the predictions of crop development and yield a few weeks or months in advance.