Spatiotemporal dynamics of vegetation cover and drought conditions in West Darfur, Sudan: Implications of climate variability and future projections

Abstract

This study explores the spatiotemporal dynamics of vegetation cover in West Darfur, Sudan, a region severely affected by the compounded effects of climate change and socio-environmental crises. Using Moderate Resolution Imaging Spectroradiometer (MODIS) Normalised Difference Vegetation Index (NDVI) data spanning 2000–2023 and the Standardised Precipitation-Evapotranspiration Index (SPEI), we assessed vegetation dynamics in relation to drought conditions. Data processing and analysis were conducted using Google Earth Engine (GEE), QGIS, and R-Software. An Autoregressive Integrated Moving Average (ARIMA) model was utilised to forecast future climate scenarios, thereby enhancing the predictive understanding of precipitation trends. The results revealed vegetation loss during the drought periods of 2005 and 2010, with decreases of 646.23 km² (2.83%) and 275.21 km² (1.21%), respectively. In contrast, substantial vegetation recovery was observed in 2015 (0.54%, 122.25 km²), 2020 (7.87%, 1794.70 km²), and 2023 (8.78%, 2001 km²), aligning with increased annual precipitation and reduced drought intensity. Historical SPEI analysis underscores prolonged drought events between 1980 and 2010, followed by a notable reduction in drought frequency and severity in subsequent years. Precipitation projections suggest a continuing trend of increasing precipitation, likely fostering further vegetation regeneration in the study area. This study underscores the intricate interplay between vegetation cover, precipitation variability, and drought conditions in West Darfur, highlighting both the region's vulnerability to climate-induced stressors and its potential for ecological recovery under favourable climatic conditions. The findings contribute to informed policymaking aimed at mitigating climate impacts and promoting sustainable land-use practices in vulnerable arid and semi-arid regions.