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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. [ABSTRACT FROM AUTHOR]

Due to the national nutrition crisis and the adjustment of planting structure, millet has once again become a widely planted cash crop in Northern China. However, as the climate warms in recent years, drought has occurred frequently and repeatedly in Northern China, which has seriously threatened millet production safety in this area. Therefore, it is urgent to clarify the hazard of millet drought disaster and provide reference for the formulation of millet disaster prevention and reduction measures. In this paper, combined with the water demand of millet in each growth period, Standardized Precipitation Requirement Index (SPRI) was selected to identify and quantify the drought disaster of millet. Considering the impact of different degrees of drought in different growth periods, a hazard assessment model is constructed to evaluate the hazard of millet drought disaster in Northern China under the background of climate change. The results show that: (1) SPRI can well characterize the drought of millet in Northern China. (2) In the context of climate change, millet drought in Northern China shows a trend of increasing intensity and decreasing frequency, and it is possible that millet drought will be even more severe in the future. (3) Combined with the hazard assessment model, millet drought in Northern China will still be dominated by middle hazard in the future, but the areas with high hazard will gradually increase, mainly distributed in northeast China, central and western Inner Mongolia and northern Gansu. The research results can be of great practical significance for the adjustment of agricultural production structure in the future, especially for the sustainable development of agriculture and the formulation of measures to prevent and resist agricultural disasters. [Display omitted] • We apply SPRI to identify millet drought by considering actual water demand. • Future changes of millet drought evaluated by CMIP6-GCM models. • Hazard assessment model was presented combined with disaster loss coefficient. • The areas with high hazard of millet drought will gradually increase in future. [ABSTRACT FROM AUTHOR]

Agricultural drought is a major problem facing China's agricultural production. In this study, the cash crop 'peanut' was used as an example to explore vulnerability. Through the atmosphere–plant–soil continuum system, a single index that could represent different types of droughts affecting peanuts was selected and weighted using the CRITIC weighting method to construct a multi-source data fusion drought index (MFDI). Then, Pearson correlation analysis between the comprehensive drought index and relative meteorological yield and the Mann–Kendall trend test for different growth periods of peanuts were used to verify MFDI and analyze the variation over time. A three-dimensional vulnerability assessment method of drought intensity–drought duration–yield reduction rate was established based on the run theory and trend surface analysis. The results show that the constructed multi-source data fusion drought index (MFDI) can more accurately characterize the actual drought conditions of peanuts in Shandong Province. The MFDI results showed that the drought severity in the coastal areas of the study area decreased with the growth and development of peanuts, while the drought became more severe in the western and northern parts during the late growth period of peanuts. The vulnerability surface of the drought intensity–drought duration–yield reduction rate showed that when the drought intensity was < 0.8 and the duration was < 3.5 months, the vulnerability of peanut crops was low, and then with the increase in drought intensity or duration, the vulnerability increased. The impact of drought duration cannot be ignored. In contrast to traditional vulnerability assessment methods, this study established a three-dimensional vulnerability surface, which provides a new approach for agricultural drought vulnerability assessment. The research results are helpful for a deeper understanding of the relationship between drought and crop vulnerability and provide scientific support for local governments in formulating disaster prevention and mitigation policies. [ABSTRACT FROM AUTHOR]

• A quantitative assessment framework for ecosystem drought risk was established. • Nearly 45.4% of ecosystem vegetation in NEC has a moderate or high risk of drought. • Quantitative assessment of vulnerability is the key point to drought risk assessment. • The drought risk patterns driven by climate variability and human activities are different in farmland and natural vegetation. Given the significant increasing trend of droughts in Northeast China (NEC) under climate change, it is of particularly urgency to quantify the drought risk to vegetation in different ecosystems. Based on the theory of risk formation, we developed a quantitative framework for the assessment of ecosystem drought risk that integrates both drought hazard and vulnerability (sensitivity and adaptability). To quantitatively assess the drought risk to different vegetation types in NEC, we used long-term (1982–2015) normalized difference vegetation index (NDVI) data and standardized precipitation evapotranspiration index (SPEI) data. The effects of climate change and non-climatic factors (mainly human activities) on the NDVI dynamics and drought risk were analyzed using the partial least squares regression method to explore key drivers of risk formation. Our findings indicate that almost 45.4% of ecosystem vegetation in NEC is at a moderate or high risk of drought. Our findings indicate that vulnerability is key to NEC drought risk assessment, and adaptability plays an important role in regulating sensitivity. Land cover is the main driving factor for the spatial pattern of drought vulnerability in NEC, and forests have the lowest vulnerability. The impact of climate change on vegetation dynamics in dry years (R2 dry = 0.35) is significantly higher than over the entire study period (R2 all = 0.20). Cropland drought risk is dominated by human activities, whilst woodland and grassland drought risk is controlled by temperature and precipitation variability, respectively. The driving force analysis of vegetation dynamics and drought risk improves our understanding of the mechanisms behind the formation of risk patterns in NEC. Our study provides a basis for land use management and the formulation of drought adaptation options for vegetation types at different growth stages. [ABSTRACT FROM AUTHOR]

Maize is susceptible to drought and low temperatures. In recent years, drought, low temperatures, and their composite events have often occurred during the growth period of maize, causing a huge impact. In this study, maize in the Songliao Plain was used as the research object. Based on the crop water surplus deficit index (CWSDI) and heat index (F(T)), combined with the Theil–Sen median and Mann–Kendall tests (Sen–MK) and empirical orthogonal function (EOF), the temporal trends and spatial patterns of drought and low temperatures in different growth periods of maize were obtained. Copula modelling was used to analyse the joint probability distribution and return period of drought and low temperatures. The results showed that the temporal variation trend of the CWSDI was significantly different at different growth periods of maize, and there were different trends and spatial modal distributions. However, the temporal variation trend of F(T) was similar, showing a downward trend over the entire region. There was no obvious asymmetry or skew‐dependent structure in the distribution of concurrent events of drought and low temperature; however, the joint probability contours of different growth periods were biased to the upper left. The recurrence period of drought and low‐temperature concurrent events was within 2 years, and the recurrence period was basically between 2 and 5 years, with a reduction in drought or low temperatures. [ABSTRACT FROM AUTHOR]

[Display omitted] • Fitting drought intensity and yield loss rate to construct sensitivity curves. • Considering millet planting climatic suitability as a potential exposure index. • A perfect index system suitable for millet drought risk assessment was built. • Distribution and dynamic migration characteristics of millet drought risk were analyzed. Due to the improvement of living standards and the adjustment of dietary structure, the cereal industry shows excellent growth prospects. Clarifying millet drought risk distribution and determining its dynamic evolution characteristics are therefore of great importance for guiding millet production, preventing drought risks, and ensuring food security. In this study, SPRI was used to identify millet drought, and drought intensity-yield loss rate curves were constructed to characterize millet drought sensitivity. The potential exposure of millet was explored by considering millet climatic suitability and farmland proportion. In light of this, a comprehensive assessment of millet drought risk in different growth periods was made using natural disaster risk theory. The results showed that: (1) The sensitivity model for each growth period had passed the F-test of α = 0.05 (R2 were 0.544, 0.408 and 0.347 respectively), reaching a significant level, which proved that the model can be used to assess millet drought sensitivity. (2) More than 70 % of Liaoning Province had a suitable climatic environment for millet production. Combined with the farmland proportion, the area with high potential exposure was distributed in the central region of Liaoning. (3) The millet drought risk in different growth periods showed a characteristic distribution of high in the northwest and low in the southeast. Among them, Chaoyang had the largest high and extremely high drought risk area in the three growth periods, accounting for 92.11 %, 99.34 % and 98.86 % respectively. At the same time, the center-of-gravity model shows that the barycenter of millet drought risk has a trend of spreading from the west of Liaoning to the northeast and southwest. To sum up, the millet drought risk area in Liaoning may increase in the future, measures should be taken to prevent and mitigate millet drought from three aspects: before, during and after the disaster. [ABSTRACT FROM AUTHOR]

Due to global warming, it is necessary to study the influence of extreme climate and concurrent events on crop growth. The study area was the Songliao Plain, where drought events frequently occur. First, the daily meteorological data of 14 meteorological stations from 1981 to 2016 were collected to analyze the temporal and spatial changes in the crop water surplus and deficit index, extreme growing degree-days, and heat stress intensity during different growth stages of maize. Second, the cloud model was used to describe the fuzziness of concurrent events (simultaneous drought and heat), and mutual mapping between qualitative and quantitative data was undertaken. The fuzzy certainty degree of the influence of different degrees of concurrent events on maize was calculated. Third, the copula function was used to describe the randomness of concurrent extreme events and calculate the joint probability distribution and return period. An assessment method was proposed for concurrent events from the perspective of system uncertainty. Finally, we analyzed the relationship between concurrent events and maize yield, which showed different degrees of water deficit and warming trends during each growth period. Crops were most affected by extreme weather during the reproductive growth period (RGP). During the vegetative growth period (VGP), the temperature increase was higher than in other periods, especially in the high-latitude region. The frequency of mild concurrent events was higher during the VGP and RGP. During the vegetative and reproductive period, the average occurrence probability of mild, moderate, and severe concurrent events was 21.9%, 1.7%, and 0.35%, respectively, whereas during the RGP, it was 23.1%, 8.2%, and 0.12%, respectively. The present study provides a meaningful reference for a better understanding of the occurrence laws of drought, heat, and concurrent events during crop growth periods and how to optimize the agricultural management of maize. • Cloud model qualitative and quantitative mapping of drought and heat events. • Copula function was used to describe the randomness of concurrent extreme events. • Vegetative growth periods (VGP) and reproductive growth periods (RGP) were modelled. [ABSTRACT FROM AUTHOR]