Quantifying the influence of vegetation dynamics on carbon uptake and its climatic drivers is critical for regional carbon-cycle assessments, yet most land surface modeling studies still parameterize static vegetation. This limitation is particularly relevant in South Asia, where widespread vegetation greening has altered ecosystem productivity. This study focuses on the spatiotemporal variability of gross primary productivity (GPP), evapotranspiration (ET), and the resulting ecosystem water-use efficiency (WUE = GPP/ET) to understand the long-term trends and drivers across South Asia. Simulations are performed over South Asia for 1985–2023 using the Indian Land Data Assimilation System (ILDAS) with a dynamic vegetation scheme and hybrid meteorological forcing involving local IMD (India Meteorological Department) precipitation while maintaining transboundary consistency. Results reveal significant regional variations with high GPP ( >2500 g.C/m 2 /year) and WUE (> 2 g.C/kg H 2 O/year) over the lower Himalayan and northeastern regions, and low values over arid north-western region. Seasonal variability peaks during the monsoon for GPP (σ = 95.44 g C/m²) and ET (σ = 39.60 mm), whereas WUE varies the most in the pre-monsoon (σ = 12.48 g C/m²/mm), reflecting vegetation adaptation under water-limited conditions. Non-parametric elasticity analysis indicates temperature (ε = –21.78) and pressure (ε = 76.30) as dominant climatic drivers of WUE, while soil moisture and leaf area index (LAI) are the primary internal drivers. Trend analysis reveals significant increases (p < 0.05) in GPP and WUE across large parts of South Asia, particularly in northern and central agro-ecological zones, consistent with vegetation greening within existing forest cover. Model evaluation shows stronger agreement for GPP with FluxSat (median R = 0.70; KGE = 0.43) than with MODIS, and robust ET performance against MODIS (median R = 0.81; KGE = 0.44) over vegetated regions. In the absence of direct observations, cross-validation of modeled WUE with MODIS-derived WUE indicates moderate agreement (median R = 0.36) but low KGE (0.21), reflecting uncertainties in ratio-based diagnostics. Overall, the spatial coherence of errors supports the utility of the current ILDAS framework with dynamic vegetation scheme for assessing long-term carbon–water interactions across South Asia. • Dynamic vegetation scheme improves representation of ecosystem carbon uptake in Indian Land Data Assimilation System. • Forests in the lower Himalayas and Northeast India show the highest productivity and WUE across the region. • GPP and WUE show significantly (p < 0.05) increasing trend across South Asia due to widespread vegetation greening. • WUE is found more sensitive to temperature, pressure, soil moisture and leaf area index.
Chakraborty et al. (Thu,) studied this question.