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The Northeast region of China and Huang Huai Hai (3H) region are vital maize production bases in northern China that are crucial for national food security. The absence of phenological data hinders a detailed assessment of the alignment between maize development stages and climatic resources. This study combines the authors’ maize phenology data with climate suitability modeling to evaluate maize’s climate suitability at different developmental stages in both regions. This study shows that during the maize growth cycle, the average temperature, precipitation, sunshine, and comprehensive climate suitability were 0.77, 0.49, 0.87, and 0.65, respectively, in the Northeast. In contrast, the average temperature, precipitation, sunshine, and comprehensive climate suitability in the 3H region were 0.98, 0.53, 0.73, and 0.70, respectively. Precipitation is a major factor influencing maize growth, with temperature and sunshine impacting growth differently across regions. Temperature significantly affects maize in the Northeast, while sunshine plays a greater role in the 3H region. The Northeast is suitable for drought-resistant maize varieties, and implementing a late harvest policy in Liaoning could enhance maize yield. The 3H region generally has favorable climatic conditions. Apart from certain parts of Henan needing drought-resistant varieties, areas with ample growing seasons can adopt long-duration varieties to maximize thermal resource utilization. Our results have important implications for optimizing maize planting strategies and enhancing regional resilience, aiming to assess meteorological factors’ impact on maize growth in key production areas.

The Rolling Hilly Region of Northeast China (RHRNEC) is a critical grain production area in China, and soil erosion is a major problem in this region. To determine spatial and temporal changes in rainfall erosivity (RE) in the RHRNEC and generate information useful for soil and water conservation, agricultural management, and ecological protection efforts, a RE index consisting of nine erosivity indices based on normal and extreme precipitation was established. The normal RE index (NREI) comprised annual RE (ARE), wet season RE (WRE), dry season RE (DRE), typical wet-month RE (TWRE), and typical dry-month RE (TDRE), and the extreme RE index set (EREI) comprised maximum one-day RE (RE × 1 day), maximum five consecutive days RE (RE × 5 day), storm RE (RE50), and maximum continuous RE (CRE). ARE, WRE, and TWRE decreased at relative rates of 2.5%, 2.9%, and 4.1%, respectively. By comparison, DRE increased at a non-significant relative rate of 6.3%, and all extreme RE indices decreased at a non-significant rate relative to 1981–2015 mean values. The future trends for all RE indices were predicted to be opposite to historical trends. The future trends and historical trends of all indices exhibited opposite patterns. RE gradually increased from north to south, and WRE, DRE, and all extreme RE indices were significantly negatively correlated with longitude, latitude, and altitude (p < 0.05). ARE, WRE, and TWRE showed increasing trends in the north and south and decreasing trends in the center. The findings are useful for soil and water conservation, especially for agricultural management and ecological protection.

Drought and floods affect the growth and yield of maize, affecting food security. Therefore, it is crucial to assess maize’s drought and waterlogging status in various growth stages. We used phenological and daily meteorological data and spatial analysis to identify the drought and waterlogging conditions of spring maize in Northeast China in eight growth stages. We calculated the crop water surplus/deficit index and used the national standard for maize drought and waterlogging. The results indicate a significant decreasing trend of effective precipitation in Northeast China. The maize’s water requirements changed during the growing period. The ranking of the daily water requirements of maize from high to low in the different growth stages was the flowering stage to the silking stage (6.9 mm/d), the tasseling stage to the flowering stage (6.1 mm/d), the jointing stage to the tasseling stage (4.9 mm/d), the seven-leaf stage to the jointing stage (3.4 mm/d), the silking stage to the harvesting stage (2.0 mm/d), the emergence stage to the three-leaf stage (1.4 mm/d), the three-leaf stage to the seven-leaf stage (1.3 mm/d), and the sowing stage to the emergence stage (1.2 mm/d). Drought occurred primarily in the early growth and development stage, and the most severe drought conditions were observed in the sowing to emergence stages and the emergence to the three-leaf stages in most areas in Northeast China. Waterlogging occurred predominantly in the flowering to the silking stages and the silking to the maturity stages in southeast Liaoning and parts of Jilin. Inner Mongolia had the lowest soil moisture conditions and was unsuitable for maize growth, followed by Heilongjiang, Jilin, and Liaoning. The dominant meteorological factors affecting the drought and waterlogging status of maize in different growth stages were precipitation and wind speed, followed by the minimum temperature, relative humidity, sunshine hours, and maximum temperature. The average temperature did not influence the drought and waterlogging status. The results provide a basis for selecting drought-resistant varieties and preventing waterlogging.

Detailed traits are required for early warning and prediction of crop-related meteorological hazards. Currently, data sets describing maize phenological traits in Northeast China are few and incomplete, resulting in poor spatial interpolation results that do not accurately reflect the spatial distributions and temporal development patterns of maize phenology in the region. In this study, a maize-phenology data set is produced containing nine phenological stages and phenological stage maps based on three sets of in situ maize-phenology data from three different sources. First, the relationship between each phenological stage and date of the previous stage, longitude, latitude, and altitude, is uncovered using a multiple stepwise regression method. Then, the spatial variation of each phenological stage using ArcGIS is explored. Finally, a maize phenological stage data set and a phenological stage atlas are established for the average state of 2010–2020 in Northeast China. The data set was validated using phenological data from agricultural weather stations run by the China Meteorological Administration. The validated data set can be used for various purposes, including real-time warning and prediction of maize-related meteorological hazards.