Individuazione delle aree agricole e delle colture a forte rischio per variazioni climatiche

Considerable effort has been expended in studies on a large-scale and general circulation modeling to assess climatic risk. However, downscaling to the local level to assess climate risk for agricultural areas and crops has proven difficult. In addition, there have been few attempts to account for inter-annual climate variability. To overcome these deficiencies, a project to incorporate year-to-year climate variability with land evaluation was conducted. Land evaluation provides qualitative information about land, such as its cropping potential or land vulnerability risk, based on bio-physical and socio-economic characteristics. In general, land qualities derived from measurements of dynamic variables (e.g. climate data) are converted to static variables (means) for the purposes of land evaluation. This study presents an application of land evaluation for estimating the climate risk for agriculture at local scales. Observed and future climate variability data were combined with geographic and soil information from Sardinia and Emilia-Romagna, Italy, using a Land Capability for Agriculture (LCA) classification system, which classifies agricultural land into a range of quality and potential productivity. The climatic variability LCA classification was based on maximum soil moisture deficit and heat accumulation. A climatic risk index was developed analyzing the inter-annual variability of maximum soil moisture deficit for the period 1961-2000 and the results were compared with climatic risk index values calculated for the period 2005-2099 from two different emission scenarios. Potential effects of future climate change on wheat and tomato productivity were also determined using a crop simulation model. The results showed that LCA classification is sensitive to weather variability and that the determination of actual and future climatic risk for agriculture requires climatic variability to be included into land evaluation models. In addition, the analysis showed that future temperature and rainfall regimes could cause an increase in climatic risk greatly affecting potential productivity of crops.