The Rio Grande/ R & iacute;o Bravo basin, home to over ten million people, is under increasing stress due to changing land use, agricultural practices, and hydroclimatic variability. This study examines vegetation dynamics in the region using MODIS (Moderate Resolution Imaging Spectroradiometer) Earth Observations, analyzing temporal changes over a 21-year period (2000-2020). As shifts in vegetation are often driven by natural hydroclimatic variablity, these changes have significant implications for the broader desert ecosystem, including native species. We examine how climatic factors-particularly precipitation and temperature-influence vegetation patterns using Normalized Difference Vegetation Index (NDVI), supported by leaf area index (LAI) and fraction of photosynthetically active radiation (FPAR). We utilize gridded datasets from both ground-based and satellite sources to assess spatiotemporal vegetation trends. We apply the Mann Kendall test with a pre-whitening approach to minimize the impact of serial correlation in the data. Our findings show a greening pattern in southern areas (notably in Mexico), and widespread browning across much of the United States (US) portion of the basin, with New Mexico (US) showing significant browning linked to declining precipitation. Seasonally, vegetation responds most strongly to rainfall frequency and intensity during the primary growing seasons (April-September), with weaker and more spatially variable responses during cooler or drier months. Vegetation browning is particularly prominent in natural herbaceous areas and shrublands. Along the Rio Grande, a narrow corridor of tree cover remains near the river and adjacent streams. Beyond this corridor lies an arid zone, that supports only drought-tolerant vegetation and cacti. As precipitation patterns continue to shift, native vegetation may be increasingly disrupted. To support the long-term sustainability of native ecosystems, vegetation management strategies in the Rio Grande basin must adapt to these changing environmental conditions.Graphical AbstractThis study investigates the influence of meteorological factors-specifically precipitation and temperature-on vegetation dynamics within the Rio Grande Basin. We employ gridded datasets derived from both ground-based observations and satellite estimates to analyze spatiotemporal variations in vegetation. A non-parametric Mann Kendall trend analysis is conducted at the grid scale to identify long-term vegetation trends. The study area map illustrates the Rio Grande Basin, highlighting delineated watersheds, sub-watersheds, and dominant land cover types. Panel (a) includes an inset showing the Rio Grande Basin overlaid on administrative boundaries with an elevation backdrop. Areas experiencing significant vegetation browning are emphasized, along with the spatial distribution of land cover based on the Land Cover Classification System (LCCS2). Findings reveal that browning is predominantly concentrated in natural herbaceous areas and shrublands.