Publications

Rani, A; Sehgal, VK; Dhakar, R; Abhilash; Das, B; Pragya (2024). Remote sensing based Multivariate Hierarchical Agricultural Drought Index (MHADI) for India. THEORETICAL AND APPLIED CLIMATOLOGY, 155(12), 9885-9909.

Abstract
Agricultural drought has multi-dimensional adverse impacts on food security, livelihood of farmers, and socio-economic conditions in India. An integrated novel index named as 'Multivariate Hierarchical Agricultural Drought Index (MHADI)' was developed for near real-time monitoring of agricultural drought at 1 km grid and 16-day interval during the kharif crop season (Jun-Oct) over India. The input drought indices used for the development of MHADI were Standardized Precipitation Index computed at the time scales of 16 days (SPI-0.5), one-month (SPI-1) and three-months (SPI-3) from CHIRPS rainfall data, Standardized Normalized Difference Vegetation Index (SNDVI) from MODIS NDVI data, Standardized Normalized Difference Water Index (SNDWI) from MODIS surface reflectance data, Standardized Evaporative Stress Ratio (SESR) from MODIS evapotranspiration data, and Standardized Soil Water Deficit Index (SSWDI) from SMAP root-zone soil moisture data. Separate weights were assigned to these drought indices for the early, mid, and late phases of crop season using the Analytical Hierarchical Process (AHP) method. The SSWDI and SESR received higher weightage during the early and mid-crop season, while SNDVI during the late season. The MHADI was able to capture and characterize well the historical spatio-temporal patterns of agricultural drought over India and showed increasingly significant correlation with Standardized Normalized Gross Agricultural Primary Productivity (SNGPP) with the progress of crop season. This new index has the potential for use in the operational agricultural drought monitoring and declaration system of India as it can be generated at high spatial and temporal resolution with lower computational requirements.

DOI:
10.1007/s00704-024-05204-1

ISSN:
0177-798X