انصاری

Drought is a natural creeping event that starts due to lower moisture compared to normal condition. This phenomenon impacts all aspects of human activities. However there is neither any detailed definition nor a general and proper index for drought monitoring. In this study, fuzzy logic has been applied to deal with inherent uncertainties of the real world data. We presented a fuzzy model to evaluate and analysis the drought. Using the Fuzzy logic for drought monitoring of Mashhad synoptic station showed its higher capability and efficiency compared to Boolean logic. We combined two membership functions related to SPI (Standardized precipitation index) and SEI (a presumable standardized index for evapotranspiration), to provide a new index (SEPI: Standardized Evapotrans-Precipitation Index). The results showed that fuzzy model which employed 81 rules with minimum of 2 and maximum of 4 rules is the most accurate approach. The new index (SEPI) not only covers all advantages of SPI, but also can be calculated using different time scales of available data. Moreover, it considers temperature effects on drought occurrence and severity too. Monitored drought using SPI and SEPI indices demonstrated high correlation (more than 90%) between these two indices across all time scales. Drought monitored by SEPI for Mashhad synoptic station, at 1 to 3 monthly scales showed high drought frequency but low duration. Increasing time scales resulted in low frequency but higher duration. Employing SEPI also showed that high intensity and frequency of drought occurred in years 2000 and 2001 across all time scales. The longest drought duration, by 3 years across all time scales, occurred between 1995 to 1998.