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How can I calculate standard precipitation index (SPI)?

The Standardized Precipitation Index (SPI), developed by T.B. McKee, N.J. Doesken, and J. Kleist and in 1993, is based only on precipitation. One unique feature is that the SPI can be used to monitor conditions on a variety of time scales. This temporal flexibility allows the SPI to be useful in both short-term agricultural and long-term hydrological applications. The SPI is the most popular drought index (Karabulut, 2015) and is a widely recognized index for characterizing meteorological droughts (Hayes et al., 1999; Deo, 2011). McKee et al. (1993,1995) defined SPI suitable for different timescales (1, 3, 6, 12, 24 and 48 months), and the output values ranged from -2.0 to 2.0. Positive SPI values indicate precipitation higher than the median and negative values indicate precipitation lower than the median of long term precipitation records. The SPI values can be interpreted as the number of standard deviations by which the observed anomaly deviates from the long-term mean.

The Standardized Precipitation Index (SPI) is a widely used index to characterize meteorological drought on a range of timescales. On short timescales, the SPI is closely related to soil moisture, while at longer timescales, the SPI can be related to groundwater and reservoir storage. Standard precipitation index formula is very simple but due to precipitation data follow gamma distribution, you should to use gamma distribution. Gamma distribution is difficult but you can use MDM, RDIT, or DMAP for calculating standard precipitation index (SPI), these softwares is very simple and user-friendly.

In 2009, WMO recommended SPI as the main meteorological drought index that countries should use to monitor and follow drought conditions (Hayes, 2011). By identifying SPI as an index for broad use, WMO provided direction for countries trying to establish a level of drought early warning. There are some limitations in related to SPI: As a measure of water supply only, the SPI does not account for evapotranspiration, and this limits its ability to capture the effect of increased temperatures (associated with climate change) on moisture demand and availability.

The SPI is sensitive to the quantity and reliability of the data used to fit the distribution; 30-50 years recommended The SPI Does not consider the intensity of precipitation and its potential impacts on runoff, streamflow, and water availability within the system of interest. SPI can be calculated on as little as 20 years' worth of data, but ideally the time series should have a minimum of 30 years of data, even when missing data are accounted for. An advantage in using SPI is that only rainfall data are needed for its computation. SPI can also be compared across regions of different climatic zones.

Name: Jaffar Mirzadeh