Abstract: 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.

Abstract: Policy making aims to align agricultural production with multifunctional services such as environmental conservation, rural development, and economic competitiveness. Policies counteract or reinforce external driving forces such as climate change, global economic developments, demography, consumption patterns. They considerably affect decision making of farmers. Because of the interaction and non-linear feedback loops with socio-economic and geophysical processes of the land use systems, policies are difficult to design, and their impacts are difficult to anticipate. The policy making community articulates an emerging demand for science based evidence in support of the policy process. Ex-ante impact assessment of policy making provides the legal basis to fuel scientific evidence into the policy process. For researchers, impact assessment is a means to structure the analysis of human-environment interactions. For policy makers, impact assessment is a means to better target policy decisions towards sustainable development. The integration of both requires a mutual understanding of the respective objectives and operational restrictions within the scientific and policy-making domains. This paper provides insight into the process of policy impact assessment and how research based methods and tools can best feed into it. Three aspects are outlined: the co-design of the assessment between policy makers and researchers; the integration of quantitative analysis with participatory valuation methods; and the robustness and transparency of the analytical methods.

Abstract: Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2 ], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(-1) per °C. Doubling [CO2 ] from 360 to 720 μmol mol(-1) increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2 ] among models. Model responses to temperature and [CO2 ] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.