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Zavalloni, M.; Marconi, V.; Viaggi, D.; Raggi, M. |
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Climate change adaptation: a farm level model to assess investment decisions in water storage |
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2014 |
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One of the potential measures suggested to cope with the changes induced by Climate Change (CC) is the construction of rainwater harvesting reservoirs (Bozzola and Swanson, n.d.). The literature has focused mostly on the water allocation management but it overlooks at the structure of the investment decision. We analyse the investment decision in water storage facilities, for different farming specialization and under different climatic scenarios to assess the option value of the investment. We take an interdisciplinary approach integrating climate, agronomic and economic models. CC effects are assessed by a downscale of the A1B scenario of the IPCC (Tomozeiu et al., 2010). The resulting estimated temperatures and rainfall levels are then introduced in an agronomic model, which determines the irrigation water quantity and timing for a number of crops. Finally all these elements are included in a farm level economics model, DHYMORA (Viaggi et al., 2010). The model is applied to typical farm specializations in eastern Emilia-Romagna, including both annual and perennial crops. |
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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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MA @ admin @ |
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5060 |
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Dass, P.; Müller, C.; Brovkin, V.; Cramer, W. |
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Can bioenergy cropping compensate high carbon emissions from large-scale deforestation of high latitudes |
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Journal Article |
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2013 |
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Earth System Dynamics |
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Earth System Dynamics |
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4 |
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2 |
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409-424 |
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land-use change; global vegetation model; soil carbon; climate-change; surface albedo; cover changes; snow cover; remind-r; forest; productivity |
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Numerous studies have concluded that deforestation of the high latitudes result in a global cooling. This is mainly because of the increased albedo of deforested land which dominates over other biogeophysical and biogeochemical mechanisms in the energy balance. This dominance, however, may be due to an underestimation of the biogeochemical response, as carbon emissions are typically at or below the lower end of estimates. Here, we use the dynamic global vegetation model LPJmL for a better estimate of the carbon cycle under such large-scale deforestation. These studies are purely theoretical in order to understand the role of vegetation in the energy balance and the earth system. They must not be mistaken as possible mitigation options, because of the devastating effects on pristine ecosystems. For realistic assumptions of land suitability, the total emissions computed in this study are higher than that of previous studies assessing the effects of boreal deforestation. The warming due to biogeochemical effects ranges from 0.12 to 0.32 degrees C, depending on the climate sensitivity. Using LPJmL to assess the mitigation potential of bioenergy plantations in the suitable areas of the deforested region, we find that the global biophysical bioenergy potential is 68.1 +/- 5.6 EJ yr(-1) of primary energy at the end of the 21st century in the most plausible scenario. The avoided combustion of fossil fuels over the time frame of this experiment would lead to further cooling. However, since the carbon debt caused by the cumulative emissions is not repaid by the end of the 21st century, the global temperatures would increase by 0.04 to 0.11 degrees C. The carbon dynamics in the high latitudes especially with respect to permafrost dynamics and long-term carbon losses, require additional attention in the role for the Earth’s carbon and energy budget. |
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2190-4987 |
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CropM |
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MA @ admin @ |
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4486 |
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Eza, U.; Shtiliyanova, A.; Borras, D.; Bellocchi, G.; Carrère, P.; Martin, R. |
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An open platform to assess vulnerabilities to climate change: An application to agricultural systems |
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Journal Article |
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2015 |
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Ecological Informatics |
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Ecological Informatics |
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30 |
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389-396 |
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climate change; grasslands; modeling platform; vulnerability assessment; pasture simulation-model; software component; solar-radiation; crop production; change impacts; adaptation; indicator; makers |
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Numerous climate futures are now available from global climate models. Translation of climate data such as precipitation and temperatures into ecologically meaningful outputs for managers and planners is the next frontier. We describe a model-based open platform to assess vulnerabilities of agricultural systems to climate change on pixel-wise data. The platform includes a simulation modeling engine and is suited to work with NetCDF format of input and output files. In a case study covering a region (Auvergne) in the Massif Central of France, the platform is configured to characterize climate (occurrence of arid conditions in historical and projected climate records), soils and human management, and is then used to assess the vulnerability to climate change of grassland productivity (downscaled to a fine scale). We demonstrate how using climate time series, and process-based simulations vulnerabilities can be defined at fine spatial scales relevant to farmers and land managers, and can be incorporated into management frameworks. (C) 2015 Elsevier B.V. All rights reserved. |
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1574-9541 |
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CropM LiveM, ft_macsur |
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MA @ admin @ |
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4708 |
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Haas, E. |
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Responses of soil N2O emissions and nitrate leaching on climate input data aggregation: a biogeochemistry model ensemble study |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-20 |
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Numerical simulation models are increasingly used to estimate greenhouse gas (GHG) emissions at site to regional scales and are outlined as the most advanced methodology (Tier 3) for national emission inventory in the framework of UNFCCC reporting.Low resolution simulations needs less effort in computation and data management, but details could be lost during data aggregation associated with high uncertainties of the simulation results. This aggregation effect and its uncertainty will be propagated with the simulations. This paper aims to study the aggregation effects of climate and soil input data on soil N2O emissions and nitrate leaching by comparing different biogeochemistry models. We simulated two 30-year cropping systems (winter wheat and maize monocultures) under nutrient-limited conditions. Input data (climate and soil) was based on a 1 km resolution aggregated on resolutions of 10, 25, 50, and 100. In the first step, the soil data was kept homogenous using representative soil properties while climate data was used on all different scales. In the second step, the climate data was kept homogeneous while soil initial data was used on all different scales. Finally in the third step we have used spatially explicit climate and soil data on all different scales. We analyzed the N2O emissions per unit of crop yield as well as the nitrate leaching on the annual average as well as on daily resolution to study pulsing events for all scenarios and on all scales. The study presents an analysis of the influence of data aggregation.The study gives an indication on adequate spatial aggregation schemes in dependence on the scope of regionalization studies addressing the quantification of losses of reactive nitrogen from managed arable systems. No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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MA @ admin @ |
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2135 |
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Author |
Bojar, W. |
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Methods to limit risks in agriculture in the era of climate change |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-8 |
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Nowadays, you can forecast that in twenty-first century a probability of drought risk occurrence, a one of the threatening a type of risk in agriculture, will reach a level between 66 and 90 per cent [IPCC 2001].The beginning of the twenty-first century is a time to seek new methods of risk management in agriculture. This is confirmed by the reports and surveys carried out in many research centres, as well as commissioned by public authorities [Xu et al. 2008]. Currently, you can observe the growing importance of the issue of risk in agriculture due to the worsening climate change, changes in the Common Agricultural Policy, the progressive liberalization of food trade on a global scale (less market intervention, increased price volatility and fluctuations in food supply and demand) and associated with those phenomena increase market risk [Jerzak 2008]. Demographic boom, growth in epidemics and diseases or changes in models of consumer behaviour as a result of today’s food trends healthy diet have an impact on food security. It is of interest to large research teams in Europe, just as the above risk factors affect the imbalance of global supply and demand for food in the long term. The Stern [Stern 2006] and report the Foundation for the Development of Polish Agriculture – FDPA) [Report FDPA 2008] and the communications of the European Commission show that in agriculture a lack of system solutions for the management of various risks and set of management instruments it is inadequate to the current situation of the sector.Analyzing historical data, one can conclude that in Poland more often we have to deal with losses caused by deficiency of precipitation than the excess [Mizak et al. 2013]. Droughts in Poland are most common when during the growing season flows very warm and dry air. In 2008, the area of arable land, determined in accordance with the applicable System Monitoring Agricultural Drought criterion of a 20 percent reduction in crop yields covered more than 8.1 million hectares, which accounted for 54% of arable land in Poland [Mizak et al. 2011]. Appropriate agricultural policy and trade policy should ensure sufficient food for the rapidly growing global population under mentioned above extreme natural events circumstances.Research centers in many EU countries and beyond should create appropriate models, tools and techniques in order to solve signaled above specific problems at farms, regions, countries and groups of countries in order to reduce the risks associated with food production [Bojar et al. 2012]. Such models were created as part of the research carried out in the Kujawy & Pomorze region where their results show the possibility of predicting the effects of climate change in the long term [Bojar et al., 2013, Zarski et al. 2014, Bojar at al., 2013].In particular, the series established the likelihood of a lack of rain in the forecast for the years 2030 and 2050 at a certain level and so the series 7, 8, 9 and 10 decades without rain likely to occur by 2030 amounts to 0.302, 0.109, 0.032 and 0.009, while for the year 2050 decades for a series of 7, 8, 9 and 10 respectively 0,543, 0,222, 0,070 and 0,019. It follows that, for a series of seven and eight decades without rain probability of such unfavorable phenomena is highest. Then established the relationship that the lack of rainfall will decrease yields of cereals in total, winter wheat, spring barley and potatoes. It results in the decline in land productivity in the years 2030 and 2050 will amount to cereals in total, winter wheat, spring barley and potatoes in the range of the maximum and minimum respectively 2.51 t/ha -3.67 t/ha, 3.10 t/ha- 4.10 t/ha, 1.63 t/ha – 3.33 t/ha and 15.30 t/ha- 21.00 t/ha [Bojar et al. 2013].The above-described conditions of risk of conducting agricultural activities indicate the need to develop methods of mitigating their negative effects.Mitigation of production and business risks in agriculture can be reached as follows:- advancement models for defining dependencies between yields and whether in long-term to forecasts negative effects in farming productivity and profitability and this way minimize production and business risks,- advancement of system of crop insurance,- improvement of the infrastructure of small retention and simulation of the impact of various forms of cooperation of agricultural producers to increase the efficiency of their operations (joint purchasing of inputs, selling of agricultural products and/or use of machinery [Bojar 2008], work specialization versus production specialization [Bojar W., Drelichowski L., 1994.], common trainings, advertisements [Bojar, Kinder 2008, etc.]. Own preliminary research findings confirmed that approximately one third of the respondents jointly purchases and sales their products and forms of farmer cooperation with a joint market activities (transaction) in the Kujavian & Pomeranian region.For more detail and more precise explanation of dependency between yield and rainfalls some efforts will be focused on mathematical models describing agriculture and climate change problems that can be encountered in risk and safety analysis. We need to describe the uncertainties from incomplete knowledge, imperfect models or measurement errors.Because yields of crops depend strongly on rainfall there will be considered different models of rainfall. You will attempt of the generalization of model mixture the gamma distribution and a single point at zero distribution. This approach will be a continuation of the work that has been sent to print. To extend this application it could be performed calculations for the empirical data coming from the Kujavian & Pomeranian region for different crops.This work was co-financed by NCBiR, Contract no. FACCE JPI/04/2012 – P100 PARTNER No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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MA @ admin @ |
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2123 |
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