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Drought is one of the main natural hazards affecting the economy and the environment of large areas. Droughts cause crop losses, urban water supply shortages, social alarm, degradation and desertification. In this study, the spatial characteristics of annual and seasonal drought were evaluated based on climate data from 16 synoptic stations during the period of 1980-2010 in south of Iran. To estimate the drought severity used modified Reconnaissance Drought Index (RDI) and to prepare maps, ArcGis10.2 software was used. Results showed in annual drought, percent of areas with normal condition, severe dry and extreme dry condition have had significant increasing trend (0.95 level). In winter drought, the percentage of areas with severe dry and extreme dry condition have had significant increasing trend (0.95 level). In spring drought, percent of areas with moderate dry has had significant increasing trend (0.95 level), in summer drought, percent of areas with moderate dry has had increasing trend (insignificant) and in autumn drought, percent of areas with severe dry has had significant increasing trend (0.95 level). Other classes of drought in different time scales had not significant trend. Result showed that the percentage of area with dry condition is increasing, this can be effective on the agricultural activities, agricultural productions, water resource management and other activities.

Confronting drought and reducing its impacts requires modeling and forecasting of this phenomenon. In this research, the ability of different time series models (the ARIMA models with different structures) were evaluated to model and predict seasonal drought based on the RDI drought index in the south of Iran. For this purpose, the climatic data of 16 synoptic stations from 1980 to 2010 were used. Evaluation of time series models was based on trial and error. Results showed drought classes varied between ‘very wet’ to ‘severely dry’. The more occurrence frequency of ‘severely dry’ class compared to other drought classes represent the necessity of drought assessment and the importance of managing the effects of this phenomenon in the study area. Results showed that the highest severity of drought occurred at Abadeh, Shiraz, Fasa, Sirjan, Kerman, Shahre Babak and Saravan stations. According to selecting the best model fitted to the computed three-month RDI time series, results indicated that the MA model based on the Innovations method resulted in maximum cases with the best performance (37.5% of cases). The AR model based on the Yule–Walker method resulted in minimum cases with the best performance (6.3% of cases) in seasonal drought forecasting.