Unravelling the hidden drivers of crop sensitivity to precipitation in the arid and semi-arid regions of Northwest China

Understanding how vegetation responds to precipitation variability is critical for sustaining crop productivity and ecosystem resilience in arid and semi-arid regions. This study examines the sensitivity of maize and wheat to precipitation across the Loess Plateau, with a focus on aridity gradients, soil texture, and the effects of atmospheric CO₂. We employed remote sensing data in combination with dynamic linear models to capture temporal and spatial variability in vegetation sensitivity from 2001 to 2023. Results show that maize exhibits a sharp unimodal sensitivity peak near an aridity index of 0.4, with maximum normalized difference vegetation index (NDVI) responses reaching 0.85 m⁻¹ H₂O, reflecting strong responsiveness to moderate moisture availability. In contrast, wheat displays a broader, less intense peak shifted toward higher aridity (∼0.7), with maximum responses of ∼0.55 m⁻¹ H₂O, indicating greater adaptation to drier conditions. Soil texture further modulates these responses, with sandy soils amplifying the sensitivity of leaf area index (LAI) due to their lower water retention capacity. Elevated atmospheric CO₂ increased water-use efficiency and enhanced LAI sensitivity (∼0.15 for maize) under moderate aridity, though this effect weakened under higher aridity levels. Temporal analyses revealed declining trends in both NDVI and precipitation, with a sharper decline in wheat (NDVI: –0.401; precipitation: –0.17), underscoring its greater vulnerability to water stress. These findings highlight the combined influence of climate drivers, soil properties, and physiological responses in shaping crop sensitivity to precipitation, providing critical insights for adaptive management strategies that aim to ensure agricultural resilience under future climate change.