Water-carbon coupling shapes the stability of terrestrial carbon sinks, yet the magnitude, direction, and timing of interactions between surface runoff (Q) and gross primary productivity (GPP) can differ among hydroclimatic regimes and shift over time. This study evaluates Q and GPP coupling in the Minjiang River Basin, a monsoon-influenced mountain-to-basin transition with strong topographic mediation. Using the China Natural Runoff Dataset version 1.0, gap-filled MODIS GPP, CRU meteorology, and MODIS vegetation indices, patterns from micro subbasins to the full basin were quantified with Mann-Kendall trend tests, spatial Pearson correlations, five-year moving correlations, and random forest attribution. Q and GPP show pronounced spatial heterogeneity, with higher Q in the middle and lower basin and increasing GPP from north to south, while basin-scale trends are modest and largely not significant. Spatial coupling forms a persistent north-negative and south-positive dipole. Decoupling is strongest and most extensive from 2001 to 2010, whereas from 2007 to 2018 it shows weaker negative correlations and expanding positive coupling. Moving window analyses indicate strengthening coupling in most subbasins and sign reversals in some. Attribution identifies precipitation as the dominant driver of Q across subbasins, while GPP is jointly regulated by temperature and vegetation structure, with the relative influence shifting from climate toward structure between periods as NDVI and LAI increase in importance. Atmospheric moisture and vegetation also gain influence on Q in the later period. These findings provide transferable diagnostics for identifying where and when water and carbon coupling is likely to weaken or strengthen in mountain plain transitions and highlight vegetation structural levers for carbon-relevant water management.
Lu et al. (Thu,) studied this question.