چکیده:
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.
خلاصه ماشینی:
"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.
1. Drought indices The results of drought monitoring in Lake Urmia Basin using Percentage of Normal Precipitation Index (PNPI) are given in Table 4 and the time series of PNPI values are given in Figure 2.
The results of Standardized index annual precipitation (SIAP) show that in the Lake Urmia basin 16 droughts periods (40%) have occurred with various severities in 1966-2005.
The results of drought monitoring in Lake Urmia Basin using Rainfall Anomaly Index (RAI) are given in Table 6 and the time series of RAI values are given in Figure 4.
Time series of RAI values in Lake Urmia basin The results from the Standard Precipitation Index (SPI) show that there were 19 dry periods with different severities in Lake Urmia basin for 1966-2005.
Probabilistic methods In this study to investigate the occurrence and persistence probability of droughts in Lake Urmia basin, The annual rainfall situation was determined using Runs theory from 1966-2005 (Table 7).
The severity of dry and wet periods in the Lake Urmia basin using Runs theory Year Annual (View the image of this page) Table 8.
5. Conclusions This study focused on the application of four known drought indices (PNPI, SIAP, RAI ans SPI) for drought detection and monitoring in Lake Urmia Basin in Iran for 40 years (1966-2005)."