Compound drought and heatwave events (CDHWs) pose severe threats to cropland productivity. Yet, climatic zone-specific responses of cropland gross primary productivity (GPP) and solar-induced chlorophyll fluorescence (SIF) to CDHWs remain unclear. This study utilized the machine learning framework coupled with SHAP analysis to reveal the spatiotemporal heterogeneity of CDHWs in China and quantify their relationships with GPP and SIF across different climatic zones. Results showed that moderate, severe, and extreme CDHWs increased significantly in frequency at rates of 0.263, 0.283, and 0.068 events per decade ( p < 0.05), respectively, with corresponding increases in duration of 0.158, 0.159, and 0.147 days per decade from 1981 to 2024. Spatially, severe and extreme CDHWs were concentrated in the arid and semi-arid regions of Northwest China, northern North China, and Southwest China. In terms of cropland productivity responses, relative to normal conditions, GPP is 2.42% higher under heatwave-only conditions, while it is 9.37% lower under drought-only conditions. Interestingly, CDHW conditions correspond to the largest GPP reduction of 14.05%. SHAP analysis further identified RHum as the most negative contributor to GPP under CDHW conditions. For SIF, it exhibited larger response magnitudes to extreme events, declining by 15.14% under drought-only conditions, rising by 55.99% under heatwave-only conditions, and remaining elevated by 42.25% under CDHWs. Climatic zone-specific analysis demonstrated that LRad, temperature (Temp), and RHum were the three core predictors of GPP in the model. Notably, Prec exerted the weakest contribution, ranging from 0.076 to 0.105. However, LRad was the important predictor for SIF across all climatic zones, with minimal regional variability. Additionally, RHum contributed nearly as much as Temp to GPP in the BWk zone. This study elucidates the nonlinear relationships between CDHWs and cropland productivity and their climate zone-dependent mechanisms over China, providing critical scientific support for the development of national climate change adaptation strategies and the construction of climate-resilient agricultural systems.
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Yi et al. (2026) studied this question.
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