Spring frost is an extreme temperature event that poses a significant threat to winter wheat production and consequently jeopardizes food security. In the context of climate change, the accelerated phenology of winter wheat due to global warming advances the frost-sensitive stage, thereby escalating the risk of spring frost damage. Present techniques for monitoring and assessing frost damage heavily rely on meteorological data, controlled field experiments and crop model simulations, which cannot accurately depict the actual disaster situation for winter wheat. In this study, we propose a novel method that utilizes remote sensing index and statistical data to ascertain the spatial distribution of spring frost damage to winter wheat and evaluate the extent of damage. This method was employed to monitor and assess the spring frost damage event that occurred in Shandong province from 3 to 7 April 2018. The result shows that beginning on 3 April, the daily minimum temperature in western Shandong Province dropped significantly (decreased by 17.93 °C), accompanied by precipitation. The daily minimum temperature reached the lowest on 7 April (−1.48 °C). The growth of winter wheat began to be inhibited on 3 April 2018, and this process persisted until 13 April. Subsequently, the impact of spring frost damage on winter wheat ceased and growth gradually resumed. The affected area of winter wheat spanned 545,000 mu with an accuracy rate of 89.72%. Severely afflicted areas are mainly located in the cities of Jining, Zaozhuang, Dezhou, Heze, Liaocheng, Jinan and Tai’an in western Shandong province, and the yield reduction rates were 5.27~12.02%. Our monitoring results were consistent with the distribution of county-level winter wheat yield in 2018 in Shandong province, the daily minimum temperature distribution during spring frost and severely afflicted areas reported by the news. This method proves effective in delineating the spatial distribution of agricultural disasters and monitoring the extent of disaster damage. Furthermore, it can provide reliable information of disaster area and geospatial location for the agricultural department, thereby aiding in disaster damage assessment and post-disaster replanting.

Integrated foliar spraying has been proposed as an effective measure to mitigate the increasingly severe impacts of hot–dry–windy (HDW) events on winter wheat yield under ongoing climate change, and its physiological effectiveness has been mechanistically validated. However, there are still few quantitative assessments of the application of this technology at the regional scale. First, hourly meteorological data from the ERA5-Land reanalysis (1981–2020) were matched to the centroids of 599 counties within China’s major winter wheat-producing regions, allowing precise alignment with county-level yield data. Subsequently, spatial and temporal trends of sub-daily HDW events were analyzed. These HDW events were classified according to daily duration into three categories: short-duration (HDW_sd1, 1 h d⁻¹), moderate-duration (HDW_sd2, 2–3 h d⁻¹), and prolonged-duration (HDW_sd3, 4–8 h d⁻¹). Finally, a difference-in-differences (DiD) approach combined with panel matching methods was employed to quantitatively assess the effectiveness of integrated foliar spraying technology—comprising plant growth regulators, essential nutrients, fungicides, and insecticides—on wheat yield improvements under varying irrigation conditions. The results indicate that HDW is a major compound event threatening high-yield and stable-yield regions within the main winter wheat production areas of China, and in the study area, the annual average number of HDW days ranges from 3 to 13 days, increasing by 1–4 days dec⁻¹. While HDW events continue to intensify, the integrated foliar spraying technology effectively mitigates yield losses due to HDW stress. Specifically, yield increases of up to 18–20% were observed in counties with sufficient irrigation infrastructure since the large-scale implementation began in 2012, particularly in regions exposed to more than 2 days of HDW stresses annually. However, the effectiveness of integrated foliar spraying was notably compromised in areas lacking adequate irrigation infrastructure, highlighting the necessity of reliable irrigation conditions. In these poorly irrigated areas, yield improvements remained limited and inconsistent, typically fluctuating around negligible levels. These findings underscore that robust irrigation infrastructure is pivotal to unlock the yield benefits of integrated foliar spraying technology, while also highlighting its transformative potential in advancing climate-smart agriculture globally—particularly in regions grappling with intensifying compound stress events driven by climate change, where this innovation could foster resilient and adaptive food systems to counter escalating environmental extremes.

In this study, we have investigated changes in precipitation extremes and the population’s exposure to these extremes during 2091–2099 in China’s Beijing–Tianjin–Hebei (JJJ) region relative to the historical period of 1991–1999. First, the regional climate model RegCM4, with a hydrostatic dynamic core, was run for east Asia, including China, at a 12 km resolution for 1990–1999 and 2090–2099. This model is forced by global climate model (GCM) MPI-ESM1.2-HR under the middle shared socioeconomic pathways (SSP245). The first year was used as a model spinup. Then, the 12 km results were used to force RegCM4 with a non-hydrostatic dynamic core (RegcM4-NH) at a 3 km convection-permitting scale over the JJJ region during the historical and future periods. Future precipitation extremes were predicted to increase over the whole of China and its four subregions, while decreases were predicted over the JJJ region. This may partly be caused by lower increases in specific humidity over the JJJ region. The percentage contributions of the three components of total population exposure, i.e., changes in exposure due to changes in the population, precipitation extremes and the joint impact of the population and extremes, were then analyzed. Changes in the population and wet extremes were closely related to changes in the total exposure over the JJJ region. The population is the dominant factor that most impacts the total exposure to dry extremes. Finally, changes in future population exposure to precipitation extremes per degree of warming were quantified for the JJJ region.

Given the increasing crop yield losses, water scarcity, and fertilizer application in Northeast China, a systematic assessment is increasingly necessary to investigate the potential of crop redistribution to enhance grain production while alleviating environmental pressures. Here we quantify the potential of crop redistribution in Northeast China through a multi-objective optimization approach. First, we construct a dataset that contains four objectives including crop yield, yield losses, water deficit, and nitrogen fertilizer application based on their annual data in 273 counties over two decades (2001–2020). Second, we optimize the county-level distribution of rice, maize and soybean using the developed dataset and evaluate the benefits on each objective. Finally, we design a crop redistribution scheme and analyze its impact on the cropping structure in Northeast China based on the optimal solution. Results show significant potential of crop redistribution, with crop production increases by 1.70% (2.41 × 10⁶ tons), production losses decrease by 2.69% (1.84 × 10⁵ tons), water deficit decreases by 6.78% (3.88 × 10⁸ m³) and N fertilizer application decreases by 10.87% (5.41 × 10⁷ kg) when all the objectives are optimized simultaneously. The crop redistribution scheme is summarized as follows: compared with the baseline crop structure, rice area increases by 69.58%, maize reduces by 12.8%, and soybean reduces by 54.79% in Northeast China. Specifically, rice area increases in northwestern Heilongjiang, eastern Jilin, most counties in Liaoning, and reduces elsewhere. Maize area reduces in most of the counties, except for several counties in southwestern Heilongjiang, northern Jilin, and northern parts of the Four Eastern Leagues. Soybean area reduces in northern part of Heilongjiang and Four Eastern Leagues and increases in western Jilin and most counties in Liaoning. Although crop redistribution scheme was generated, the model remains limited in terms of crop types, spatial resolution, and the range of factors influencing crop distribution. Future work will address these limitations to enhance the reliability and applicability of the crop redistribution model.