Abstract: Models are increasingly used to estimate greenhouse gas emissions at site to regional and national scales and are outlined as the most advanced methodology for national emission reporting in the framework of UNFCCC. Process-based models incorporate the major processes of the carbon and nitrogen cycle and are thus thought to be widely applicable at various spatial and temporal scales. The definition of the spatial scale is determined by the objectives. GHG emission reporting requests spatially and temporally aggregated information whereas for the assessment of mitigation options on hot spots and hot moments of emissions a high spatial simulation resolution is required. In addition, other input data also determine the simulation scale. Low resolution simulations needs less effort in computation and data management, but important details could be lost during the process of data aggregation associated with high uncertainties of the simulation results. This study presents the aggregation effects of climate input data on the simulations of soil N2O emissions and nitrate leaching by comparing different biogeochemistry models. Using process-based models (DailyDayCent, LandscapeDNDC, Stics, Mode, Coup, Epic), we simulated a 30-year cropping system for two crops (winter wheat and maize monocultures) under water- and nutrient-limited conditions based on a 1 km resolution climate dataset. We aggregated the climate data to resolutions of 10, 25, 50, and 100 km and repeated the simulations on these spatial scales. We calculated the N2O emissions as well as the nitrate leaching on all scales. Results will be presented and discussed.

Abstract: Global warming and frequent extreme weather conditions affect crop yields worldwide. Drought and high temperatures are among stresses that often act simultaneously. Therefore the aim of the studies was to analyze effect of combined drought and heat stresses on growth and function of spring wheat. The experiment was conducted in a growth chamber conditions. Spring wheat cv Łagwa was planted in soil columns of 10cm in diameter and 45cm high filled with Orthic Luvisol developed from loess and grown up  to the end of flowering.  The treatments were: (C) control with optimum growth soil water potential 160 hPa (pF 2.2), 250 µmol m-2s-1 PAR, 22/18 °C day / night temperatures and  60% air relative humidity throughout growing period; (D) drought stress with soil water potential 250 kPa (pF 3.4) at flowering; (HT) high temperature stress with air temperature 34/24°C and optimum soil water potential ; (DHT) drought  (as above) and high temperature (34/24°C day / night) stresses at flowering. During the experiment photosynthesis rate, transpiration and stomatal conductance were  measured using the gas exchange system GFS-3000 and DualPAM 100 (Walz, Germany). Drought stress reduced photosynthesis rate by  11%, high temperature by 19% and both stresses by 79% as compared to control  (100%). However, drought stress decreased transpiration rate similarly as combined drought and high temperature stresses (by 60-63%). Transpiration rate under high temperature stress compared to control slightly increased.

Abstract: Increasing temperatures, changed precipitation patterns and more frequent extreme events may lead to an increase in crop failure and to a substantial decrease of crop yields. The assessment of climate change impacts on agricultural sector has a particular interest to stakeholders and policy makers, in order to identify specific agricultural sectors and agro-climatic zones that could be more vulnerable to changes in climatic conditions and to develop the most appropriate policies to cope with these threats. For these reasons, the evaluation of climate change impacts for key crops in different agro-climatic zones was made exploring climate uncertainty and focusing on short period monitoring, which is particularly useful for food security and risk management. The analysis was made using the DSSAT-CSM (Decision Support System for Agrotechnology Transfer – Cropping System Model) software, version 4.5. Crop models implemented into DSSAT-CSM were used, for each selected crop, to evaluate climate change impacts on crop production. Multiple combinations of soils and climate conditions, crop management and varieties were considered for different agro-climatic zones. The climate impact was assessed using future climate projections, statistically and/or dynamically downscaled, for the specific areas. Direct and indirect effects of different CO2 concentrations, projected for the future periods, were separately explored to estimate their effects on crops. Finally, several adaptation strategies were evaluated with the aim to reduce the negative impact of climate change on crop production. The results of the study, analysed at local and regional scale, will be discussed.