Rötter, R. P., & Semenov, M. A. (2014). Development of methods for the probabilistic assessment of climate change impacts on crop production (Vol. 3).
Abstract: Various attempts have been made to determine the relative importance of uncertainties in climate change impact assessments stemming from climate projections and crop models, respectively, and to analyse yield outputs probabilistically. For example, in the ENSEMBLES project, probabilistic climate projections (Harris et al. 2010) have been applied in conjunction with impact response surfaces (IRS), constructed by using impact models, to estimate the future likelihood (risk) of exceeding critical thresholds of crop yield impact (see, Fronzek et al., 2011, for an explanation of the method). In this task, we aimed to further develop and operationalize these methods and testing them in different case study regions in Europe. The method combines results of a sensitivity analysis of (one or more) impact model(s) with probabilistic projections of future temperature and precipitation (Fronzek et al., 2011). Such an overlay is one way of portraying probabilistic estimates of future impacts. By further accounting for the uncertainties in crop and biophysical parameters (using perturbed parameter approaches), the outcome represents an ensemble of impact risk estimates, encapsulating both climate and crop model uncertainties. No Label
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Hutchings, N., Weindl, I., Topp, C. F. E., Snow, V. O., Rotz, A., Raynal, H., et al. (2017). Does collaborative farm-scale modelling address current challenges and future opportunities (Vol. 10).
Abstract: Resources required increasing, resources available decreasing Farm-scale modellers will need to make strategic decisions Single-owner models May continue with additional resources Risk of ‘succession’ problem Community modelling is an alternative Need to continue building a community of farm modellers
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Eory et al. (2016). Economic assessment of greenhouse gas mitigation on livestock farms (Vol. 8).
Abstract: Conference presentation PDF
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Palatnik, R. (2015). Economic Impacts of Water Scarcity under Diverse Water Salinities (Vol. 5).
Abstract: Exploitation of alternative water sources is expected to grow in the decades to come in water-stressed countries with fast population growth, especially in regions where a further decline of natural freshwater availability is expected due to climate change. Increasing utilization of non-freshwater usually leads to salinity build-up in fields and water sources as well as accumulation of various pollutants – both having a considerable impact on the suitability of non-freshwater for irrigation due to constraints associated with crop salinity tolerance and food safety regulations.We developed a linked CGE – farm-level model of a water economy with representation for multiple water types characterized by different qualities. We employ the model to assess the impact of water shortage on the Israeli economy, where a steadily growing water scarcity is leading to an increasing utilization of alternative water sources. We simulate water shortage scenarios based on the Long Term National Master Plan for The Water Economy developed by the Israeli Water Authority (IWA).The linked CGE – farm-level model provides a mechanism for estimating the Constant Elasticity of Substitution (CES) rates between different irrigation water types used in agriculture. This mechanism accounts for the effects of salinity on yields and takes into consideration food safety regulations for irrigating crops with treated wastewater. We demonstrate that, in contrast to previous studies, CES rates between different water types are not identical and generally lower than previously assumed – differences that can be attributed to the constraints associated with crop salinity tolerance and food safety regulations.Our results reveal that water shortage can lead to a significant decline of Israel’s GDP, where a considerable part of the decline is attributed to the decrease in agricultural outputs. The magnitude of the impact depends on the underlying assumptions regarding future desalination capacity. To further study the effect of desalination, we run simulations under various desalination levels and examine its impact on the GDP. We also examine the extent to which the impact of water shortage is sensitive to CES rates between different irrigation water types. No Label
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Özkan, á¹¢., Bonesmo, H., Østerås, O., & Harstad, O. M. (2014). Effect of Increased Somatic Cell Count and Replacement Rate on Greenhouse Gas Emissions in Norwegian Dairy Herds (Vol. 3).
Abstract: Dairy sector contributes around 4% of global greenhouse gas (GHG) emissions, of which 2/3 and 1/3 are attributed to milk and meat production, respectively. The main GHGs released from dairy farms are methane, nitrous oxide and carbon dioxide. The increased trend in emissions has stimulated research evaluating alternative mitigation options. Much of the work to date has focused on animal breeding, dietary factors and rumen manipulation. There have been little studies assessing the impact of secondary factors such as animal health on emissions at farm level. Production losses associated with udder health are significant. Somatic cell count (SCC) is an indicator on udder health. In Norway, around 45, 60 and 70% of cows in a dairy herd at first, second and third lactation are expected to have SCC of 50,000 cells/ml and above. Another indirect factor is replacement rate. Increasing the replacement rate due to health disorders, infertility and reduced milk yield is likely to increase the total farm emissions if the milking heifer replacements are kept in the herd.In this study, the impact of elevated SCC (200,000 cells/ml and above) and replacement rate on farm GHG emissions was evaluated. HolosNor, a farm scale model adapting IPCC methodology was used to estimate net farm GHG emissions. Preliminary results indicate an increasing trend in emissions (per kg milk and meat) as the SCC increases. Results suggest that animal health should be considered as an indirect mitigation strategy; however, further studies are required to enable comparisons of different farming systems. No Label
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