Drought indices are among the most important tools used by planners to monitor and manage water scarcity. The Standardized Precipitation Index (SPI) is one of the most widely used indices due to its simplicity and its ability to facilitate comparisons between regions with different climatic conditions. The World Meteorological Organization (WMO) has adopted the SPI as a key tool for monitoring meteorological drought. It measures the deviation of accumulated precipitation over a specified period from its long-term average, expressed in terms of standard deviations. The SPI is based on transforming accumulated precipitation into cumulative probabilities using an appropriate probability distribution, then converting these probabilities into the standard normal distribution, which has a mean of zero and a variance of one. Positive SPI values indicate wetter-than-normal conditions, whereas negative values indicate drier-than-normal conditions. The accuracy of the index depends on selecting an appropriate probability distribution, as an unsuitable distribution may overestimate or underestimate drought severity. Therefore, several distributions are typically tested, including Gamma, Logistic, Weibull, and Lognormal. Their suitability is evaluated using goodness-of-fit tests, such as the Kolmogorov–Smirnov and Anderson–Darling tests. In the study under consideration, the SPI was calculated at a 12-month timescale for five meteorological stations in the Middle Euphrates region: Hillah, Karbala, Najaf, Diwaniyah, and Samawah. The analysis was based on the reference period from 1991 to 2021 and was conducted using the R programming environment. The results revealed that the most suitable probability distribution varied from one station to another. The Logistic distribution was selected for Hillah, the Lognormal distribution for Karbala and Samawah, the Gamma distribution for Najaf, and the Weibull distribution for Diwaniyah. This variation demonstrates that applying a single probability distribution to all stations may produce inaccurate results. SPI values are classified into several categories: mild drought, ranging from 0 to −0.99; moderate drought, from −1 to −1.49; severe drought, from −1.5 to −1.99; and extreme drought, at −2 or below. To characterize individual drought events, Run Theory was employed. Drought duration is defined as the period during which SPI values remain below the specified threshold, drought severity is calculated as the sum of the SPI values during that period, and drought intensity is determined by dividing severity by the number of months in the event. The results for the historical period (1991–2021) revealed the following numbers of drought months based on the SPI: 76 months in Hillah, 64 in Diwaniyah, 63 in Karbala, 56 in Najaf, and 44 in Samawah. Najaf experienced the longest continuous drought, lasting approximately 43 months, and recorded the lowest SPI value of approximately −2.81 in 1999. In Karbala, an SPI value close to −2 was recorded in 1997. The longest drought episodes identified using the SPI occurred in Hillah between 2007 and 2009 and in Diwaniyah between 2007 and 2010, with durations of approximately two to two and a half years. When the SPI was applied to projected climate series for the period 2021–2060, the results indicated that Najaf and Samawah are expected to experience the longest drought durations, whereas Karbala is projected to experience the shortest. The projected drought episodes identified using the SPI generally range from approximately one to two years. Examples include Karbala during 2037–2038, Najaf during 2049–2051, and Samawah during 2041–2043, with the latter extending beyond two years. Under the high-emission scenario, Hillah recorded the highest SPI-based drought intensity, reaching approximately −2.2 in 2026. Despite its usefulness, the SPI has certain limitations that must be acknowledged. Since it relies exclusively on precipitation, it does not account for the effects of rising temperatures and increased evaporation. Therefore, it is often complemented by the Standardized Precipitation Evapotranspiration Index (SPEI), which incorporates the water balance by considering precipitation and potential evapotranspiration. The same study demonstrated that some of the most severe future drought episodes, such as the projected drought in Diwaniyah between 2050 and 2052, were more clearly identified by the SPEI than by the SPI. Consequently, SPI results should be interpreted as indicators of meteorological drought conditions rather than as definitive predictions of actual future conditions on the ground. In conclusion, the SPI represents a simple and effective tool for identifying, classifying, and comparing drought conditions across meteorological stations and different time periods. However, its full value is realized when it is interpreted alongside other drought indices and translated into practical water-management decisions, including strengthening water storage capacity and improving irrigation efficiency. Presented by: Asst. Lecturer Zahraa Hussain Mohammed Source: Zahraa Hussain Mohammed Aziz (2024). Projections of Climate Changes in Hydrological Regime of the Middle Mesopotamian Plain. Supervisor: Asst. Prof. Dr. Imad Habeeb Obead.