Randomized trial quantifies drought risk in a subtropical monsoon basin, indicating critical climate impact on water management.
Reliable quantification of compound-drought risk under coupled climate change and land-use dynamics remains a critical challenge. This study employed the Ganjiang River Basin (80,948 km2) as a representative subtropical monsoon catchment, integrating the SWAT hydrological model, CMIP6 multi-model ensembles, the PLUS land-use simulation model, C-vine Copula joint probability analysis, Budyko elasticity attribution, and XGBoost–SHAP decomposition to assess multi-dimensional drought evolution under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios (2030–2070). The calibrated SWAT model exhibited robust performance (R2 = 0.92/0.90; NSE = 0.92/0.89), while the PLUS model (accuracy = 93.6%) projected progressive forest decline (15–19%) with concomitant cropland expansion under escalating emissions. Drought characteristics extracted via run theory from SPEI, SRI, and SSMI revealed a shift toward high-frequency, short-duration events under SSP1-2.6 and pronounced nonlinear amplification under SSP5-8.5. C-vine Copula analysis demonstrated a fundamental transition from Gaussian to Gumbel dependency structures under SSP5-8.5, with three-dimensional AND probability escalating from 0.44 to 0.70 (+59%). Budyko elasticity attribution identified climatic forcing as the dominant driver of runoff variability (94.7–108.9%), while land-use contributions exhibited scenario-dependent sign reversal: forest conservation under SSP1-2.6 suppressed runoff (−8.9%) through enhanced evapotranspiration, whereas forest degradation under SSP5-8.5 amplified runoff (+2.1%) via diminished water retention. XGBoost–SHAP independently corroborated these findings (climate: 95–97%). These results underscore the dominance of climatic forcing in governing drought variability, highlight forest conservation as a cost-effective nature-based mitigation strategy, and emphasize the necessity of multi-index monitoring frameworks for compound-drought risk management.
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