The Loess Plateau (LP), Earth's largest loess deposit, has experienced significant vegetation recovery since 2000 despite water scarcity. Using 2001-2022 satellite-derived normalized difference vegetation index (NDVI) and solar-induced chlorophyll fluorescence (SIF) data, we analyze vegetation structural (greenness) and functional (photosynthesis) responses, addressing critical knowledge gaps in cover expansion-functional enhancement relationships during ecological restoration. Sustained warming and increased moisture have consistently enhanced both the NDVI and SIF across the LP, with water availability remaining the key limiting factor for vegetation structure and function. Notably, the relative trend of SIF (RTSIF: 3.92% yr(-1)) significantly exceeded that of the NDVI (RTNDVI: 1.63% yr(-1)), producing a mean divergence (Delta RTSIF-NDVI) of 2.38% yr(-1) (p < 0.01) across the LP. This divergence indicates faster functional enhancement relative to structural expansion during vegetation recovery, with grasslands exhibiting the most pronounced difference in Delta RTSIF-NDVI compared to forests and shrublands. Hydrothermal conditions regulated vegetation structural-functional divergence, with regions experiencing stronger water stress exhibiting significantly greater Delta RTSIF-NDVI values. These findings demonstrate substantial hydrological constraint alleviation since 2001. Increased precipitation enhanced light use efficiency, accelerating photosynthetic function-especially in grasslands due to their rapid precipitation response. In contrast, forests maintained higher structure-function synchrony (lower values of Delta RTSIF-NDVI) through conservative strategies. Our findings indicate that grasslands may evolve as carbon sink hotspots via photosynthetic overcompensation, whereas forests remain reliant on sustaining current vegetation and are constrained by deep soil water deficits. This contrast highlights the value of Delta RTSIF-NDVI as a physiologically based indicator for quantifying restoration quality and predicting carbon sequestration potential across the LP.