An Investigation and assessment of meteorological drought in Lake Urmia Basin using drought indices and probabilistic methods

Drought is one of the most important weather-induced phenomena which may have severe impacts on different areas such as agriculture, economy, energy production, and society. A number of drought indices have been introduced and used in various countries to date. In the current study, four meteorological drought indices including Percent of Normal Precipitation Index (PNPI), Standard Index of Annual Precipitation (SIAP), Rainfall Anomaly Index (RAI), and Standardized Precipitation Index (SPI) are compared and evaluated for monitoring droughts in Lake Urmia Basin in Iran. The comparison of indices was carried out based on drought classes that were monitored in the study area using 40 years of data (1966-2005). Two well-known probability approaches including Runs theory and Markov chain model, were used to estimate the probability of wet and dry periods. The frequency matrix is formed and the transition probability matrix of wet- dry spells is created accordingly based on maximum likelihood method. The equilibrium probability is calculated based on succeed power on probability matrix. The results demonstrated that among the drought indices, PNPI is not an appropriate index in annual estimates and SPI and RAI are better than other indices and their results are nearer to reality. The results indicated the equilibrium probability of very dry, dry, normal, wet and very wet periods is obtained 0.23, 0.27, 0.23, 0.17 and 0.1, respectively.