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Extreme hydrological events such as droughts can cause substantial damage to society and ecosystem. Droughts can be characterized by severity, duration, spatial extent and frequency of occurrences. In this study gridded (0.5 latitude 0.5 longitude) daily precipitation data for the year 1971-2005 from Western Rajasthan meteorological subdivision of India are used to develop monthly time series of Standardized Precipitation Index (SPI). The drought conditions are identified based on SPI percentile value of 20% or below for each grid point in the study domain. The spatial identification of drought is based on spatial contiguity of SPI values aggregated at a time scale of six months (SPI 6) at each pixel. Drought severity is assessed from spatial mean SPI value of drought cluster identified at successive monthly time scale. It is found that drought severity and spatial extent is negatively correlated with each other. The drought severity is best described by generalized extreme value distribution and spatial extent using log normal distribution. The joint distribution of drought severity and spatial extent are modeled using bivariate Plackett and Archimedean class of Frank copulas. Standard goodness-of-fit test suggests that Plackett copula as a more suitable model. The copula based joint distribution of drought severity and spatial extent is employed to derive conditional return period, which in turn is used to derive drought severity-area-frequency (SAF) curves. The results of the study can be useful in water resources planning in drought affected areas and for deciding drought management policies.