Evaluation of time scale of meteorological, hydrological and agricultural drought indices

The present study was carried out to characterize drought in the Marathwada region of Maharashtra, which experiences recurring droughts, through meteorological, hydrological and agricultural drought indices, namely the Standardized Precipitation Index (SPI), Streamflow Drought Index (SDI) and Vegetation Condition Index (VCI), respectively. Standardized Precipitation Index (SPI) and Streamflow Drought Index (SDI) were computed at 1, 3, 6, 9 and 12-month time scales using in situ precipitation and streamflow data, respectively, for 35 years (1980-2014). The VCI was computed using MODIS satellite data at 500 m resolution for 1, 3 and 5-month time scales for 15 years (2000-2014). The time scales of drought indices were evaluated using historical drought years and foodgrain production. The drought area observed by SPI, SDI and VCI at different time scales was correlated with foodgrain production during kharif season for 15 years (2000-2014). The correlation analysis indicated a significant correlation between foodgrain production and 3-month SPI (r = - 0.724) and 5-month VCI (r = - 0.811), respectively, however, a low correlation was observed between multiscale SDI and foodgrain production. 3-month SPI and 5-month VCI were found to be more appropriate time scales to observe meteorological and agricultural droughts, respectively, in the region; while none of the SDI's time scales could capture hydrological drought. The analysis also revealed that the magnitude of meteorological (observed by 3-month SPI) and agricultural (observed by 5-month VCI) droughts mimic the quantum of loss in foodgrain production very closely. However, the severity and the areal extent of droughts observed by these indices were varied both spatially and temporally. Thus, the present study concluded that a single indicator (i.e., meteorological, hydrological or agricultural) is not sufficient to capture the actual drought situation, thereby suggesting the use of multiple indicators-based approaches for realistic drought characterization and monitoring.