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Observational modeling reveals compound drought and landscape factors drive 1-km food-provision shortfalls, highlighting the necessity of multidimensional hydroclimatic monitoring.
Seasonal water deficits can constrain food provision in humid-subtropical agricultural regions, but their spatial patterns are difficult to diagnose when grain statistics are reported by administrative units and drought is represented by a single index. We developed a mass-constrained and interpretable framework to diagnose county-statistics-constrained relative food-provision shortfall (FPL) at 1-km resolution in the Heng–Shao drought corridor, China. County grain production from 2013 to 2024 was allocated using target-year cropland area and a target-year-excluded, cropland-conditioned Landsat Enhanced Vegetation Index (EVI) reference, while FPL was defined relative to a target-year-excluded county-level Theil–Sen statistical reference. Compound drought signals were represented by vapour-pressure-deficit anomaly (D vpd ), soil-moisture anomaly (D soil ), and climatic-water-deficit anomaly (D cwd ); their associations with FPL were evaluated using spatially blocked Categorical Boosting (CatBoost), cross-fitted SHapley Additive exPlanations (SHAP) and TreeSHAP. FPL was strongly right-skewed and spatially localised, with an uncapped mean of 0.036 and a skewness of 4.047. CatBoost achieved pooled out-of-fold coefficients of determination (R 2 ) of 0.329–0.340 across 10–20 km spatial blocks, and adding the joint hydroclimatic predictor set comprising Dvpd, Dsoil and Dcwd increased R 2 by 0.166 beyond the background predictors. Cropland-landscape and hydroclimatic variables formed the two largest SHAP-attributed predictor groups, accounting for 34.67% and 33.72% of total attribution, respectively. The three hydroclimatic indicators also exhibited differentiated nonlinear responses and recurrent joint-attribution structures. These findings show that retaining complementary hydroclimatic dimensions alongside cropland-landscape context provides a spatially explicit diagnostic basis for characterising within-county relative food-provision shortfall.
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Wei et al. (2026) studied this question.
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