Large scale extreme risk assessment using copulas: an application to drought events under climate change for Austria

Droughts pose a significant challenge to farmers, insurers as well as governments around the world and the situation is expected to worsen in the future due to climate change. We present a large scale drought risk assessment approach that can be used for current and future risk management purposes. Our suggested methodology is a combination of a large scale agricultural computational modelling -, extreme value-, as well as copula approach to upscale local crop yield risks to the national scale. We show that combining regional probabilistic estimates will significantly underestimate losses if the dependencies between regions during drought events are not taken explicitly into account. Among the many ways to use these results it is shown how it enables the assessment of current and future costs of subsidized drought insurance in Austria

Increasing crop production in Russia and Ukraine—regional and global impacts from intensification and recultivation

Russia and Ukraine are countries with relatively large untapped agricultural potentials, both in terms of abandoned agricultural land and substantial yield gaps. Here we present a comprehensive assessment of Russian and Ukrainian crop production potentials and we analyze possible impacts of their future utilization, on a regional as well as global scale. To this end, the total amount of available abandoned land and potential yields in Russia and Ukraine are estimated and explicitly implemented in an economic agricultural sector model. We find that cereal (barley, corn, and wheat) production in Russia and Ukraine could increase by up to 64% in 2030 to 267 million tons, compared to a baseline scenario. Oilseeds (rapeseed, soybean, and sunflower) production could increase by 84% to 50 million tons, respectively. In comparison to the baseline, common net exports of Ukraine and Russia could increase by up to 86.3 million tons of cereals and 18.9 million tons of oilseeds in 2030, representing 4% and 3.6% of the global production of these crops, respectively. Furthermore, we find that production potentials due to intensification are ten times larger than potentials due to recultivation of abandoned land. Consequently, we also find stronger impacts from intensification at the global scale. A utilization of crop production potentials in Russia and Ukraine could globally save up to 21 million hectares of cropland and reduce average global crop prices by more than 3%

To burn or retain crop residues on croplands? An integrated analysis of crop residue management in China

Crop residue burning influences human health and global climate change. In China—the world's largest crop residue producer—farmers burn almost one quarter of their crop residues in the field after harvest, despite the government providing financial incentives such as subsidies to retain crop residues. This study combined economic analyses with simulations of soil carbon accumulation and carbon emission reduction associated with different residue management practices to determine the minimum level of incentives needed for Chinese farmers to shift from burning to retaining crop residues for generating carbon benefits. Simulation results showed that (Ahmed et al., 2015) the density of topsoil organic carbon in China's croplands would have increased from about 21.8 t ha−1 in 2000 to 23.9 t ha−1 in 2010, and soil organic carbon sequestration would have reached 24.4 Tg C yr−1 if farmers had shifted from burning to retaining crop residues on croplands during this period; and (Auffhammer and Gong, 2015) retaining crop residues would have avoided about 149.9 Tg of CO2 emission per year. Economic analyses showed that (Ahmed et al., 2015) existing subsidies in all regions of China, except Northeast China, only accounted for 18–82% of the incentives required for farmers to shift from burning to crop residue retention; (Auffhammer and Gong, 2015) Northeast China required the lowest incentive (287 CNY ha−1), while eastern China required the highest (837 CNY ha−1); and (Balkovič et al., 2014) the prevailing market prices (1.4–60.2 CNY tCO2e−1) in China's seven pilot carbon markets seem to be below the required incentives (39.6–189.1 CNY tCO2e−1). Our study suggests that the Chinese government should increase subsidies or seek innovative incentive schemes to encourage farmers to change their crop residue management practices for global climate change mitigation and health benefits

The land use change impact of biofuels consumed in the EU: Quantification of area and greenhouse gas impacts

Biofuels are promoted as an option to reduce climate emissions from the transport sector. As most biofuels are currently produced from land based crops, there is a concern that the increased consumption of biofuels requires agricultural expansion at a global scale, leading to additional carbon emissions. This effect is called Indirect Land Use Change, or ILUC. The EU Renewable Energy Directive (2009/28/EC) directed the European Commission to develop a methodology to account for the ILUC effect. The current study serves to provide new insights to the European Commission and other stakeholders about these indirect carbon and land impacts from biofuels consumed in the EU, with more details on production processes and representation of individual feedstocks than was done before. ILUC cannot be observed or measured in reality, because it is entangled with a large number of other changes in agricultural markets at both global and local levels. The effect can only be estimated through the use of models. The current study is part of a continuous effort to improve the understanding and representation of ILUC

Consistent negative response of US crops to high temperatures in observations and crop models

High temperatures are detrimental to crop yields and could lead to global warming-driven reductions in agricultural productivity. To assess future threats, the majority of studies used process-based crop models, but their ability to represent effects of high temperature has been questioned. Here we show that an ensemble of nine crop models reproduces the observed average temperature responses of US maize, soybean and wheat yields. Each day >30 °C diminishes maize and soybean yields by up to 6% under rainfed conditions. Declines observed in irrigated areas, or simulated assuming full irrigation, are weak. This supports the hypothesis that water stress induced by high temperatures causes the decline. For wheat a negative response to high temperature is neither observed nor simulated under historical conditions, since critical temperatures are rarely exceeded during the growing season. In the future, yields are modelled to decline for all three crops at temperatures >30 °C. Elevated CO 2 can only weakly reduce these yield losses, in contrast to irrigation

Uncertainties in global crop model frameworks: effects of cultivar distribution, crop management and soil handling on crop yield estimates

Global gridded crop models (GGCMs) combine field-scale agronomic models or sets of plant growth algorithms with gridded spatial input data to estimate spatially explicit crop yields 40 and agricultural externalities at the global scale. Differences in GGCM outputs arise from the use of different bio-physical models, setups, and input data. While algorithms have been in the focus of recent GGCM comparisons, this study investigates differences in maize and wheat yield estimates from five GGCMs based on the public domain field-scale model Environmental Policy Integrated Climate (EPIC) that participate in the AgMIP Global Gridded Crop Model 45 Intercomparison (GGCMI) project. Albeit using the same crop model, the GGCMs differ in model version, input data, management assumptions, parameterization, geographic distribution of cultivars, and selection of subroutines e.g. for the estimation of potential evapotranspiration or soil erosion. The analyses reveal long-term trends and inter-annual yield variability in the EPIC-based GGCMs to be highly sensitive to soil parameterization and crop management. Absolute yield levels as well depend not only on nutrient supply but 50 also on the parameterization and distribution of crop cultivars. All GGCMs show an intermediate performance in reproducing reported absolute yield levels or inter-annual dynamics. Our findings suggest that studies focusing on the evaluation of differences in bio-physical routines may require further harmonization of input data and management assumptions in order to eliminate background noise resulting from differences in model setups. For agricultural impact assessments, employing a GGCM ensemble with its widely varying assumptions 55 in setups appears the best solution for bracketing such uncertainties as long as comprehensive global datasets taking into account regional differences in crop management, cultivar distributions and coefficients for parameterizing agro-environmental processes are lacking. Finally, we recommend improvements in the documentation of setups and input data of GGCMs in order to allow for sound interpretability, comparability and reproducibility of published results

Integrated Multi-scale Modeling Framework for Assessment of Land-use Related Challenges under Global Change

Land is the cornerstone of many of the sustainability challenges the world is facing. About 800 million people are still undernourished today, mostly in rural areas. Agriculture will need to expand production by 60% by 2050 to satisfy future food demand but is anticipated to be the sector most directly hit by climate change. At the same time, agriculture, forestry, and land-use change are responsible for 25% of global anthropogenic greenhouse gas (GHG) emissions and these sectors are also key to achieving climate stabilization, as they can provide negative emissions through afforestation and bioenergy production with carbon capture and storage. Advanced system analysis tools are required to capture the multiple dimensions of these challenges: the global partial equilibrium model of agricultural and forest sectors, Global Biosphere Management Model, developed at IIASA, represents the state of the art in model linking across sectors, disciplines, and spatial scales. This model integrates information from a 1x1 km grid where the land characteristics and climate are defined, up to 30 regional aggregates where the international trade is represented. Spatially explicit production activities are defined through Leontief production functions representing the input-output relationships of a large set of production systems/technologies. Crops, grass, livestock, and forest systems are parameterized through biophysical models which capture overall production and environmental impacts such as carbon and nitrogen balances, water use, or GHG emissions. The model can also be used for market foresight, integrated assessment of climate change impacts and adaptation, or for assessment of mitigation options by providing to energy system models, such as Model for Energy Supply Strategy Alternatives and their General Environmental Impact (MESSAGE) at IIASA, economic information on abatement potential through emissions reduction, carbon sequestration and bioenergy production. More specific applications of the model have also been applied at global, regional and even national level, and validated by numerous publications

The Value of Global Earth Observations

Humankind has never been so populous, technically equipped, and economically and culturally integrated as it is today. In the twenty-first century, societies are confronted with a multitude of challenges in their efforts to manage the Earth system