Understanding the Drought Situation in a Water-Stressed Region of India

The onset of drought is very crucial from an agricultural as well as water management point of view in a catchment. A meteorological drought results from a lack of rainfall beyond a certain threshold and is translated to a hydrological drought when the water bodies get affected due to lack of flow to them resulting in storage depletion. This further transforms into agricultural drought when it affects agriculture. Being difficult to observe on-ground, the drought is generally represented in terms of different hydro-meteorological proxies such as precipitation, temperature, soil moisture, streamflow. This study explored the translation of meteorological drought to vegetation in a drought-prone state of India. For this, the vegetation condition index (VCI) and the widely used Standardized Precipitation Index (SPI) were estimated at the district scale. The VCI was calculated from the MODIS-derived NDVI in Google Earth Engine platform. The in-situ rainfall data was used for SPI estimation at different time scales (3-month, 6-month, and 12-month).  Further, different weightage functions such as rectangular, gaussian, triangular, and circular weightage functions were applied for their performance in estimating SPI and their correlation to VCI. Analysis of the results reveals strong dependence of VCI on SPI at larger time scales such as 6-month and 12-month time scales for the whole year as well as in monsoon season. Further, the SPI estimated using the rectangular weightage function shows a better correlation to VCI followed by the circular weightage functions. 

Key Words: Drought, Standardized Precipitation Index (SPI), Vegetation Condition Index (VCI), Weightage Function