Agricultural stability is increasingly constrained by the frequent, intense, and spatially clustered extreme weather and climate events observed in recent years. Climate change introduces unprecedented uncertainties into regional and global food-production systems. This study aims to explore the spatial evolution of China’s grain-production patterns and assess the associated risks of climatic disasters using county-level administrative units as the fundamental analytical scale. Methodologically, spatial-overlay analysis was employed to characterize the evolution of grain production between 2010 and 2020. We focused on major grain-producing regions, including 800 key grain-producing counties and nine traditional commodity-grain bases. Following spatial diagnostics, we investigated major climate-induced disasters, selecting Northeast China—a region pivotal to national food security—as a representative case study for analyzing long-term agricultural disaster trends. Subsequently, the risks of floods, droughts, and heatwaves were assessed at the county level based on the IPCC risk framework (Risk = Hazard × Exposure × Vulnerability). High-resolution gridded datasets were constructed to extract hazard data for these three extreme events under current, 1.5°C, and 2.0°C warming scenarios. To enhance accuracy, we employed a raster-based statistical method integrated with a spatial mask of cropland distribution, ensuring that hazard assessments were precisely aligned with modern agricultural production spaces. Exposure was quantified using the sown area of major grain crops derived from the 30m-resolution MGL dataset, applying a weighting rule (2.0 for double-cropping systems, 1.0 for single-cropping) to account for cropping intensity. Vulnerability was modeled using nighttime light intensity and irrigation coverage as proxies for socioeconomic resilience and adaptive capacity. The results indicate that: (1) Between 2010 and 2020, China’s grain production continued its pronounced northward shift and westward expansion, accompanied by marked spatial polarization. Simultaneous increases were observed in the numbers of both high-output (>1 million tons) and low-output (<0.1 million tons) counties, and the coefficient of variation in per capita grain output increased by 27.77 percentage points, exacerbating regional inequality. (2) Significant internal differentiation intensified within core production areas. Although the collective contribution of the 715 analyzed key grain-producing counties rose, 302 of them (42.24%) experienced output declines, with an average magnitude of 14.42%. Furthermore, production capacity diminished in several traditional commodity-grain bases, including the Taihu Plain and the Pearl River Delta. (3) A distinct spatial overlap exists between extreme-event risk hotspots and core grain-production areas. Specifically, flood risk exhibits a northward expansion trend, eventually reaching the Northeast China Plain; drought risk remains a foundational constraint, with nearly 20% of total grain production exposed to high-risk conditions; and heatwave risk is highly concentrated in core zones. This spatial convergence results in major grain-producing counties facing significantly higher current risk levels and future risk increments compared to the national average. (4) The threat of future warming to grain production exhibits a non-linear accelerating trend. The threat from heatwaves demonstrates the most alarming trajectory: under a 2.0°C warming scenario, the share of counties facing high heatwave risk (risk index > 20 000) is projected to increase more than fourfold from the current level (from 2.12% to 8.74%), exposing over one-fifth (21.18%) of national grain production to severe heat stress. Crucially, the increase in the proportion of threatened grain production resulting from the additional 0.5°C of warming (from 1.5°C to 2.0°C) is far greater than that observed in the previous warming stage. This highlights the critical urgency of limiting global warming to lower levels. We recommend that policymakers integrate localized realities and future climate risks to optimize grain-production layouts and strengthen disaster-response infrastructure.

Urban-rural integration is the ineviatable trend in the development of urban-rural relations. Counties serve as crucial vehicles for achieving this integration of new urbanization and comprehensive rural revitalization. To reveal the spatial patterns and formation mechanisms of urban-rural synergy across Chinese counties, this study employs spatial analysis and multinomial logistic regression models using 2020 cross-sectional data from 2, 355 counties. We first explore the spatial distribution of urban-rural development and synergy typologies at the national scale, then conduct focused comparative analyses of pattern differentiation in the Yangtze River Basin and Yellow River Basin, while systematically identifying key factors influencing the probability of different synergy types.The research has four major findings. Firstly, nationally, urban-rural development exhibits a pattern of "lower levels in northeastern and southwestern regions, with localized higher levels in southeastern and northwestern areas." Within the major basins, development intensity along the Yangtze River increases downstream, while the Yellow River Basin shows higher development in its northern reaches and estuary zone but lower levels in the southern regions. Secondly, high-level synergy counties (40.3%) align spatially with major urban agglomerations; low-level synergy clusters (48.3%) concentrate in former contiguous poverty-stricken areas; urban-lagging imbalance counties (5.5%) are frequently adjacent to high-synergy counties; rural-lagging imbalance counties (5.9%) show no significant spatial clustering. Thirdly, synergy differentiation is mechanistically driven by the "population-land-industry" analysis framework: terrain constraints exacerbate imbalance whereas transportation advantages mitigate dysfunction risks; industrial upgrading suppresses low-level synergy but has limited effect on improving rural-lagging imbalance; inefficient government investment and structural contradictions in human capital hinder development. Finally, promotion pathways require spatially tailored strategies: enhancing innovation radiation in high-synergy zones; promoting eco-industrialization in low-synergy regions; facilitating industrial transfer absorption or removing institutional barriers in imbalance areas. Basin-specific priorities include: addressing low-level synergy in poverty-stricken upstream areas, the mountainous southern Jiangxi region, and the agricultural areas of northern Anhui farmer within the Yangtze Basin; strengthening the Lanzhou-Xining, Guanzhong, and Central Plains urban agglomerations to resolve the prevalent low-level synergy and rural-lagging imbalance throughout the Yellow River Basin.