Abstract:
An early warning model had been developed using two variables derived from rainfall data to predict agricultural drought for Jodhpur district of Rajasthan, India. The model explained up to 74.1% of the variation in the pearl millet's yield (i.e., the production per unit area). This model was later modified by including a variable derived from a soil moisture index. In this paper, an approach is described to further improve the model by including a variable derived from the MODerate Imaging Spectroradiometer (MODIS) satellite data. It was found that the 16 day Normalized Difference Vegetation Index (NDVI) derived from the MODIS data acquired during May—June could be a potential variable for further improving the model and drought management.
