SPATIO-TEMPORAL ASSESSMENT OF DRY AND WET SPELLS AND VEGETATION HEALTH IN DELHI, INDIA: AN INTEGRATED APPROACH USING SPI AND MODIS DERIVED NDVI

This study examines the occurrence of dry and wet spells using 0.25° x 0.25° binary gridded 30- year period (1992–2022) of rainfall data to explores the Standardized Precipitation Index (SPI) and its impact on vegetation of this region for the critical cropping months of January and July. These months mark key growth stages for rabi and kharif crops, making them particularly vulnerable to climatic variability. The SPI analysis highlights significant hydro-meteorological extremes, especially in Lodhi Road and Palam areas, where maximum SPI values exhibit pronounced fluctuations. Yearly assessments reveal prolonged dry spells in Lodhi Road and Safdarjung regions, with SPI values frequently dipping below zero during crucial agricultural periods. In January, SPI values range from 0.3 (wet conditions) to -0.8 (severe dryness), reflecting high variability in precipitation. Strong spatial correlations in rainfall patterns are observed, particularly between Lodhi Road areas and Palam areas (0.906), indicating region-wide climatic influences. NDVI trends from 2001 to 2022 reveal an overall increase in vegetation health, with values rising from 0.16 to 0.3, coinciding with predominantly positive SPI values. However, the correlation between SPI and NDVI is weak (-0.0825), suggesting that vegetation health is influenced by additional factors such as urbanization and land-use changes. The Mann-Kendall test and Sen’s Slope test detects no significant trend in SPI but identifies a significant upward trend in NDVI, signaling a long-term shift in vegetation dynamics. These findings underscore the complex interplay between precipitation variability, drought risk, and vegetation resilience in an urban environment. The study highlights the increasing threat of meteorological droughts and their implications for agricultural sustainability, emphasizing the need for adaptive water management and climate-resilient planning to mitigate the risks posed by natural hazards.