Drought events can cause severe damages to agriculture and in particular to rainfed agriculture. The problems can be more evident in semi-arid regions of the Mediterranean. It is of great importance to assess the impacts of drought on the yield at an early stage, in order to be able to take measures on time for mitigating the anticipated losses, supporting the farmers, and enhancing food security. The aim of the paper is to formulate a simple methodology for estimating the impacts of drought on rainfed agriculture, and especially on wheat yield, prior to the harvest. The Reconnaissance Drought Index (RDI) is used as the main independent variable in linear regression models for the assessment of drought effects on wheat yield. To test the proposed methodology, data from two rural areas of Greece are used and the wheat yield is simulated using the AquaCrop model. Multiple regression models with variables that include RDI and the minimum temperature for winter months are tested and evaluated through a cross-validation process. The performance of the models is assessed by various criteria. Indicatively, the correlation coefficients at each study area reach 0.87 and 0.91 for predictions 1 month before harvest, 0.84 and 0.82 for 2 months and 0.67 and 0.77 for 3 months before harvest. The results show that the RDI, for reference periods that represent the critical development stages of the crop, is highly correlated with the wheat yield. A satisfactory prediction of the drought impacts on wheat yield 2 to 3 months before the harvest can be achieved. The proposed methodology can be useful to the authorities, stakeholders and insurance services for facing drought events and mitigating losses in rainfed agriculture.
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