Regional agricultural drought characterization using remote sensing based observations from geostationary satellites

Abstract

Agricultural drought has been a prime concern in an agrarian country like India. The dependencies on the vagaries of the south west monsoon and the erratic climatic conditions have made the country more vulnerable to increased frequency of drought in the recent years. The untimely onset and uneven distribution of south-west mon soon rainfall lead to agricultural drought causing reduction in food-grain production with high vulnerability over semi-arid tract (SAT) of India. In addition to current system of implementation, there is a need of advanced monitoring and assessment of agricultural drought at regional scale regarding its onset, progression and impact on crops to minimize the damage. The present study aimed to develop a pathway of three-stage (early, mid, late) regional agricultural drought characterization including early warning using biophysical, meteorological and hydrological parameters derived from a suite of Indian geostationary satellites. The study used time-series data for a period of five years (2009-2013) to develop three indicators applicable for early, mid and late-season drought characterization. Finally, a seasonal agricultural drought assessment (SADA) approach has been developed from the combination of all the three drought indicators based on weighted ranges of four drought severity classes defined for all the three classes of indicators. An early warning indicator (EWI) has been developed from satellite-based reference evapotranspiration (ET0) and rain fall for early-season drought characterization corresponding to early vegetative stage crops during June to July. A water scalar (Wscalar) has been developed from short wave infrared (SWIR) and near infrared (NIR) band combinations, to characterize mid-season agricultural drought corresponding to peak vegetative stage correspond ing to August September. A Combined Deficit Index (CDI) has been developed from deficit of tri-monthly sum antecedent rainfall and deficit in monthly vegetation vigor in terms normalized difference vegetation index (NDVI), with a lag period of one month between the two to characterize the late-season agricultural drought. All the indicators were evaluated and were found to show good correlation with other independent drought indicators such as standardized precipitation index (SPI), land surface temperature (LST), carbon productivity (GPP), rainfall, NDVI, evapotran spiration (ET) and crop yield. The comparison of SADA-based drought-affected area with those from existing operational approach showed a correlation of 0.54 (p<0.01), which demonstrated the applicability of SADA for seasonal agricultural drought char acterization in the study region.