Pasqui, M., Quaresima, S., Tomozeiu, R., Dono, G., Doro, L., Cortignani, R., et al. (2014). A comprehensive climate characterization of the Oristano (Sardinia) regional pilot case study. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: In order to assess probability distributions of critical response variables in a full crop modelling system, a complete climate characterization has been implemented to identify principal variability components in the Oristano (Sardinia) regional pilot study area with a particular emphasis on current vs near future climate.
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Lellei-Kovács, E., Barcza, Z., Hidy, D., Horváth, F., Ittzés, D., Ittzés, P., et al. (2014). Application of Biome-BGC MuSo in managed grassland ecosystems in the Euro-Mediteranean region. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Simulation of the biogeochemical cycles of extensively and intensively managed grasslands and croplands are of particular interest due to the strong connection between ecosystem production, animal husbandry and food security. In the frame of MACSUR LiveM activities, we conducted a series of „blind tests” (i.e. uncalibrated model simulations with previously optimized model) on differently managed grasslands within Europe and Israel. We used the latest version of Biome-BGC MuSo model, the modified version of the widely used biogeochemical Biome-BGC model. Biome-BGC MuSo contains structural improvements, development of management modules, and the extension of the model to simulate herbaceouos ecosystem carbon and water cycles more faithfully. The studied ecosystems were meadows and pastures located in a variety of climate zones from the Atlantic sector to Central Europe, including Mediterranean sites. Managements were intensive and extensive grazing or mowing with or without different kind of fertilizers. Under similar options we simulated ecosystem variables, e.g. Gross Primary Production (GPP) and Net Ecosystem Exchange (NEE). Our experiences show that different sites have different sensitivity to the parameters (maximum root depth, soil parameters, etc.), but overall the model provided realistic fluxes. Experiences gained during the blind tests led us to further improve the model. Biome-BGC MuSo is available as a standalone model in personal computers, but also through virtual laboratory environment and Biome-BGC Projects database (http://ecos.okologia.mta.hu/bbgcdb) developed within the BioVeL project (http://www.biovel.eu). Scientific workflow management, web service and desktop grid technology can support model optimization in the so-called „calibrated runs” within MACSUR.
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Roggero, P. P., Seddaiu, G., Ledda, L., Doro, L., Deligios, P., Nguyen, T. P. L., et al. (2014). Combining modeling and stakeholder involvement to build community adaptive responses to climate change in a Mediterranean agricultural district. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The case study area (54,000 ha) is located at Oristano, Italy. The main cropping systems are based on forages (silage maize, Italian ryegrass and alfalfa under irrigation, winter cereals and grasslands under rainfed conditions), rainfed cereals (durum wheat, barley), vegetables (e.g. artichokes), rice, citrus, olives and vineyards. Some 36,000 ha are served by irrigation. The area includes the dairy cows cooperative system of Arborea (30,000 cows, 5500 ha, nitrate vulnerable zone). The rainfed dairy sheep includes 372,000 sheep and a number of small milk processing plants. The research aims to support adaptive responses to climate change through the combination of modeling approaches and stakeholder engagement. Present (2000-2010) and future (2020-2030) climatic scenarios were developed by combining global climate models with Regional Atmospheric Modelling Systems to produce calibrated time series of daily temperature and precipitation for the case study. The EPIC model was calibrated to simulate the impact of climate scenarios on the main cropping systems. The impact of THIndex on milk yield, milk quality and mortality was also simulated for dairy cows. A territorial farm-type Discrete Stochastic Programming model was implemented to simulate choices for thirteen farming typologies as influenced by crop yields and water consumptions. Participatory activities, including field experiments, interviews, focus groups and interactive workshops, involved farmers and other stakeholders in the most critical phases of the research. The assessment of uncertainties and opportunities were proposed as a basis for discussion with policy makers to identify priorities for agro-climatic measures in 2014-2020.
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Bellocchi, G., Ma, S., Köchy, M., & Braunmiller, K. (2013). Datasets classification and criteria for data requirements (Vol. 2).
Abstract: This deliverable focuses on the collation, screening, and consolidation of data for selected grassland sites in Europe and peri-Mediterranean regions. No Label
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Sieber, S., Amjath-Babu, T. S., McIntosh, B. S., Tscherning, K., Müller, K., Helming, K., et al. (2013). Evaluating the characteristics of a non-standardised Model Requirements Analysis (MRA) for the development of policy impact assessment tools. Env. Model. Softw., 49, 53–63.
Abstract: The aim of this paper is to provide a critical analysis of the strengths and weaknesses of a non-standardised Model Requirements Analysis (MRA) used for the purpose of developing the Sustainability Impact Assessment Tool (SIAT). By ‘non-standardised’ we mean not strictly following a published MRA method. The underlying question we are interested in addressing is how non-standardised methods, often employed in research driven projects, compare to defined methods with more standardised structure, with regards their ability to capture model requirements effectively, and with regards their overall usability. Through describing and critically assessing the specific features of the non-standardised MRA employed, the ambition of this paper is to provide insights useful for impact assessment tool (IAT) development. Specifically, the paper will (i) characterise kinds of user requirements relevant to the functionality and design of IATs; (ii) highlight the strengths and weaknesses of non-standardised MRA for user requirements capture, analysis and reflection in the context of IAT; (iii) critically reflect on the process and outcomes of having used a non-standardised MRA in comparison with other more standardised approaches. To accomplish these aims, we first review methods available for IAT development before describing the SIAT development process, including the MRA employed. Major strengths and weaknesses of the MRA method are then discussed in terms of user identification and characterisation, organisational characterisation and embedding, and ability to capture design options for ensuring usability and usefulness. A detailed assessment on the structural differences of MRA with two advanced approaches (Integrated DSS design and goal directed design) and their role in performance of the MRA tool is used to critique the approach employed. The results show that MRA is able to bring thematic integration, establish system performance and technical thresholds as well as detailing quality and transparency guidelines. Nevertheless the discussion points out to a number of deficiencies in application – (i) a need to more effectively characterise potential users, and; (ii) a need to better foster communication among the distinguished roles in the development process. If addressed these deficiencies, SIAT non-standardised MRA could have brought out better outcomes in terms of tool usability and usefulness, and improved embedding of the tool into conditions of targeted end-users. (C) 2013 Elsevier Ltd. All rights reserved.
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