Climate change has a distinct impact on agriculture in China, particularly in the northeast, a key agriculture area sensitive to extreme hydroclimate events. Using monthly climate and agriculture data, the influence of drought on maize and soybean yields—two of the main crops in the region—in northeast China since 1961 to 2017 were investigated. The results showed that the temperature in the growing season increased by 1.0 °C from the period 1998–2017 to the period 1961–1980, while the annual precipitation decreased slightly. However, precipitation trends varied throughout the growing season (May–September), increasing slightly in May and June, but decreasing in July, August and September, associated with the weakening of the East Asian summer monsoon. Consequently, the annual and growing season drought frequency increased by 15%, and 25%, respectively, in the period 1998–2017 relative to the period 1961–1980. The highest drought frequency (55%) was observed in September. At the same time, the drought intensity during the growing season increased by 7.8%. The increasing frequency and intensity of drought had negative influences on the two crops. During moderate drought years in the period 1961–2017, 3.2% and 10.4% of the provincial maize and soybean yields were lost, respectively. However, during more severe drought years, losses doubled for soybean (21.8%), but increased more than four-fold for maize (14.0%). Moreover, in comparison to the period 1961–1980, a higher proportion of the yields were lost in the period 1998–2017, particularly for maize, which increased by 15% (increase for soybean was 2.4%). This change largely depends on increasing droughts in August and September, when both crops are in their filling stages. The impact of drought on maize and soybean production was different during different growth stages, where a strong relationship was noted between drought and yield loss of soybean in its filling stage. Given the sensitivity of maize and soybean yields in northeast China to drought, and the observed production trends, climate change will likely have significant negative impacts on productivity in the future.

China is the main producer and consumer of rice in the world, and rice is a major staple food grain for more than half of the world's population. Reduced rice yields caused by climate factors not only affect the food security of China, but also has global repercussions. Thus, it is vital to assess the potential impact of climate warming on rice production. Using daily temperature and phenology records of double-cropping rice from agro-meteorological stations in southern China, the influence of increased temperatures on rice yields during the last several decades was investigated. Associated with an increase in average daily mean temperatures by 0.7 °C during 2009-2018 relative to 1961-1970, Killing Degree Days (KDD), an indicator for damaging high temperature, for early and late rice increased by 110% and 88.6% respectively. However, the negative influence of KDDs on yields was mainly evident for early rice, because high temperatures occurred frequently during the sensitive grain-filling period; early-rice yields showed a decrease of 8% per 1 °C increase in mean growing season air temperature. Late rice yields, on the other hand, were not as negatively influenced by increasing temperatures as early rice, because high temperature usually occurred during the vegetative growth stage, which was not so sensitive to high temperature.

An important component in improving the quality of forests is to study the interference intensity of forest fires, in order to describe the intensity of the forest fire and the vegetation recovery, and to improve the monitoring ability of the dynamic change of the forest. Using a forest fire event in Bilahe, Inner Monglia in 2017 as a case study, this study extracted the burned area based on the BAIS2 index of Sentinel-2 data for 2016–2018. The leaf area index (LAI) and fractional vegetation cover (FVC), which are more suitable for monitoring vegetation dynamic changes of a burned area, were calculated by comparing the biophysical and spectral indices. The results showed that patterns of change of LAI and FVC of various land cover types were similar post-fire. The LAI and FVC of forest and grassland were high during the pre-fire and post-fire years. During the fire year, from the fire month (May) through the next 4 months (September), the order of areas of different fire severity in terms of values of LAI and FVC was: low > moderate > high severity. During the post fire year, LAI and FVC increased rapidly in areas of different fire severity, and the ranking of areas of different fire severity in terms of values LAI and FVC was consistent with the trend observed during the pre-fire year. The results of this study can improve the understanding of the mechanisms involved in post-fire vegetation change. By using quantitative inversion, the health trajectory of the ecosystem can be rapidly determined, and therefore this method can play an irreplaceable role in the realization of sustainable development in the study area. Therefore, it is of great scientific significance to quantitatively retrieve vegetation variables by remote sensing.

Frequent droughts and waterlogging events are a threat to food security. An understanding of the spatial and temporal variations that occur during such events is essential when conducting a regional and/or global drought and waterlogging assessment. The goal of this study is to define a comprehensive index that considers the continuum system of atmosphere, crops, and soil moisture impacts on droughts and waterlogging events, and to analyze the temporal and spatial distribution of such events in the development of maize. The results show that the proposed comprehensive drought and waterlogging index (CDWI) can bring together the advantages of a single drought and waterlogging index and reasonably describe its range. During the study period, the annual trends of the CDWI decreased at different growth stages from 1982 to 2015, whereas the CDWI did not show significant spatial heterogeneity during any particular stage. Increasing trends of CDWI over 0.019/year were found in the northern part of Midwestern Jilin Province from the emergence to tasseling stages. In addition, decreasing trends were observed in the study area from the tasseling to maturation stages. Slight drought and waterlogging events occurred more frequently than moderate and serious drought and waterlogging events.

As the climate warms, the impact of drought on plants has increased. We aimed to construct a comprehensive drought index (CDI), coupling soil-vegetation-atmosphere drought and heat conditions based on multi-source information, and to combine it with static and dynamic drought hazard evaluation models to analyze the spatial and temporal distribution characteristics of agricultural drought disasters and hazards during the growing season (May to September) in Northeast China (NEC). The results demonstrated that the CDI could combine the benefits of meteorology (standardized precipitation evapotranspiration index, SPEI), vegetation (vegetation health index, VHI), and soil (standardized soil moisture condition index, SMCI) indices. This was performed using a relative weighting method based on the remote sensing data of solar-induced chlorophyll fluorescence (SIF) to determine the weights of SPEI, VHI, and SMCI. The CDI for drought monitoring has the advantages of broad spatial range, long time range, and high accuracy, and can effectively reflect agricultural drought; the growing season in NEC showed a trend of becoming drier during 1982–2020. However, the trends of the drought index, the impact range of drought events, and the hazard of agricultural drought all turned around 2000. The drought hazard was highly significant (p < 0.001) and decreased from 2000 to 2020. The frequency of drought disasters was the highest, and the hazard was the greatest in May. The best level of climatic yield anomalies in maize were explained by drought hazard in August (R² = 0.28). In the center and western portions of the study area, farmland and grassland areas were where higher levels of hazard were most commonly seen. The dynamic hazard index is significantly correlated with climatic yield anomalies and can reflect the actual impact of drought on crop yield. The study results serve as a scientific foundation for drought risk assessment and management, agricultural planning, and the formulation of drought adaptation policies, as well as for ensuring food security in China.

The Tibetan plateau is one of the most sensitive areas in China and has been significantly affected by global warming. From 1961 to 2017, the annual air temperature increased by 0.32 °C/decade over the Tibetan Plateau, which is the highest in the whole of China. Furthermore, this is a trend that is projected to continue by 0.30 °C/decade from 2018 to 2050 due to global warming using the Regional Climate Model version 4 (RegCM4). The increased temperature trend in recent decades has been highest in winter, which has been positive for the safe dormancy of winter wheat. In order to investigate agricultural adaptation to climate change in the Tibetan plateau, we used the World Food Studies (WOFOST) cropping systems model and weather data from the regional climate model RegCM4, to simulate winter wheat production in Guide county between 2018 and 2050. The simulated winter wheat potential yields amounted to 6698.3 kg/ha from 2018 to 2050, which showed the wheat yields would increase by 81%, if winter wheat was planted instead of spring wheat in the Tibetan Plateau with the correct amount of irrigation water. These results indicate that there are not only risks to crop yields from climate change, but also potential benefits. Global warming introduced the possibility to plant winter wheat instead of spring wheat over the Tibetan Plateau. These findings are very important for farmers and government agencies dealing with agricultural adaptation in a warmer climate.