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Monthly rainfall data from June to October for 39 years were used to compute Standardized Precipitation Index (SPI) values based on two parameter gamma distribution for a low rainfall and a high rainfall districts of Andhra Pradesh state, India. Comparison of SPI with actual rainfall and rainfall deviation from the mean indicated that SPI values under-estimate the intensity of dryness/wetness when the rainfall is very low/very high, respectively. As a result, the SPI in the worst drought years of 2002 and 2006 in the low rainfall district indicated only moderate dryness instead of extreme dryness. SPI values of the high rainfall district showed slightly better stretching in both positive and negative directions, compared to that of the low rainfall district. Further, the SPI values of longer time scales (2, 3 and 4 months) showed an extended range compared to that of 1 month, but the sensitivity in drought years has not improved significantly.Normality tests were conducted based on Shapiro-Wilk statistic, p-values and absolute value of the median to ascertain whether non-normality of SPI is a possible reason. Although the results confirmed normal distribution, the scatter plot indicated deviation of the cumulative probability distribution of SPI from normal probability in the lower and upper ranges.Therefore, it is suggested that SPI as a stand alone indicator needs to be interpreted with caution to assess the intensity of drought. Further investigations should include sensitivity of SPI to the estimated shape and scale at lower and upper bounds of the gamma distribution and use of other distributions, such as Pearson III, to standardize the computational procedures, before using SPI as a substitute to the rainfall deviations from normal, for drought intensity assessment.

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Drought is an important global hazard, challenging the sustainable agriculture and food security of nations. Measuring agricultural drought vulnerability is a prerequisite for targeting interventions to improve and sustain the agricultural performance of both irrigated and rain-fed agriculture. In this study, crop-generic agricultural drought vulnerability status is empirically measured through a composite index approach. The study area is Haryana state, India, a prime agriculture state of the country, characterised with low rainfall, high irrigation support and stable cropping pattern. By analysing the multiyear rainfall and crop condition data of kharif crop season (June-October) derived from satellite data and soil water holding capacity and groundwater quality, nine contributing indicators were generated for 120 blocks (sub-district administrative units). Composite indices for exposure, sensitivity and adaptive capacity components were generated after assigning variance-based weightages to the respective input indicators. Agricultural Drought Vulnerability Index (ADVI) was developed through a linear combination of the three component indices. ADVI-based vulnerability categorisation revealed that 51 blocks are with vulnerable to very highly vulnerable status. These blocks are located in the southern and western parts of the state, where groundwater quality is saline and water holding capacity of soils is less. The ADVI map has effectively captured the spatial pattern of agricultural drought vulnerability in the state. Districts with large number of vulnerable blocks showed considerably larger variability of de-trended crop yields. Correlation analysis reveals that crop condition variability, groundwater quality and soil factors are closely associated with ADVI. The vulnerability index is useful to prioritise the blocks for implementation of long-term drought management plans. There is scope for improving the methodology by adding/fine-tuning the indicators and by optimising the weights.

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Grid (1°latitude × 1°longitude) level daily rainfall data over India from June to September for the years 1951-2007, generated by the India Meteorological Department, were analysed to build monthly time series of Standardized Precipitation Index (SPI). Analysis of SPI was done to study the spatial and temporal patterns of drought occurrence in the country. Geographic spread of SPI-derived Area under Dryness (AUD) in different years revealed the uniqueness of the 2002 drought, with widespread dryness in July. Mann-Kendall trend analysis and moving average based trends performed on the AUD indicated an increasing trend in July. The area under moderate drought frequency has increased in the most recent decade. Ranking of years based on Drought Persistency Score (DPS) indicated that 1987 was the most severe drought year in the country. The results of the study have revealed various aspects of drought climatology in India. A similar analysis with the SPI of finer spatial resolution and relating it to crop production would be useful in quantifying the impact of drought in economic terms.

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