Feasibility study of the Prediction of Annual Drought Based on Drought Conditions in the Spring Season

The drought defined as the lack of precipitation from its average along a period of time is one the most important subjects in meteorology and its prediction can play an effective rule in the field of water resources management. Therefore, both different modelling strategies and different affective variables on drought characteristics are applied for drought prediction. Considering the effect of spring rainfalls on annual drought conditions, the feasibility of the estimation of annual drought based on spring rainfall is investigated in thisstudy. However, Arazkooseh station located in Golestan province, Iran with 45 years recorded daily data were selected as case study. After calculation of drought severity factor based on standardized precipitation index (SPI), for 1, 3, and 12 months’ time scales, the correlation matrix was created. The results indicated highest correlation values between annual drought and drought in spring season. In order to find more accurate results, monthly drought indices for spring season were added to an M5 model. The results showed the predictability of annual drought using spring rainfalls as its correlation coefficient was 0.89 and the root mean square error was 0.57.