Clime change represents an important issue for the scientific community regardless of the specific field of study due to the environmental effects and impacts on the economy (especially agriculture) and human communities. The environmental impacts include the loss of biodiversity (species and ecosystems), while agricultural impacts include the exposure to heat, changes of the precipitation regime, and dispersion of diseases and pests. The assessment of particular scenarios related to changes of temperature and precipitations plays a central role among clime change studies, including predicted impacts on the ecosystems. This study addresses the exposure to clime change in the Romanian part of the Tisza river basin, using a novel approach based on the Geographical Information Systems modeling in conjunction with factor analysis to pinpoint the most affected counties based on clime data reflecting the current situation and 2100 predictions by generalizing the micro-scale situation at the county level. The results suggest that the actual precipitations explain 85% of the clime variability, the counties most affected by predicted clime change (Arad and Timiş) are situated in the western part of the region, and the economic sector most affected by predicted clime changes is agriculture, provided the predominance of agricultural areas in the most affected counties. While consistent with other studies, the results benefit upon the strength of the statistical tools, and could be used by the local authorities from the territorial units at risk to elaborate strategies resulting into the mitigation of effects and diminishing the agricultural loss. The methodological limitations of the study are first of all due to the fact that it relies on predictions, which in their turn assume the climatic response to increased greenhouse gases of the National Center for Atmospheric Research climate model, CCM3, at T42 and T170 resolutions, and due to the over-generalizing effects of GIS modeling.

clime change; agricultural impact; exposure; GIS; factor analysis; Tisza

Presentation: oral