Major Grain-producing Areas Research Articles

Unraveling Risk Networks of Cultivated Land Protection: An Exploratory Stakeholder-Oriented Case Study in Xiliuhe Town, Hubei Province, China

The protection of cultivated land plays an important role in ensuring food security, maintaining social stability, and promoting economic development. The protection of cultivated land involves a range of stakeholders (e.g., governments at different levels, farmers, and land-use organizations) and entails intertwined risk factors (e.g., to economic, environmental, social, and political factors). Therefore, it is crucial to identify and assess key stakeholders and associated risks to better align land protection policies. However, previous studies of risk are fragmented, and there has been little research targeting the complex interactions among risk factors in the protection of cultivated land. Taking Xiliuhe Town as an example, this study analyzes complex and intertwined risk factors from a network perspective in an in-depth case study in a major grain-producing area. The results show that: (1) the risk-factor network of cultivated land protection is relatively sparse, with a total of 142 nodes and 253 links; (2) local governments and land flow-out farmers are the core stakeholders, with strong power and connectivity in the network; (3) taking into account key stakeholders and associated risk factors, a framework for mitigating risks is developed, and a network simulation is performed. Using the simulation results, the effectiveness of the risk-mitigation strategies is assessed and validated. These results shed new light on cultivated land protection and sustainable agricultural development in emerging countries.

Trinity assessment method applied to heavy-metal contamination in peri-urban soil–crop systems: A case study in northeast China

Identification and assessment of heavy-metal (HM) contamination in soil–crop systems are prerequisites for treating contamination of cultivated land. Traditional assessment methods focus primarily on total soil HM concentrations, whereas the assessment of HMs that occur in available forms or are accumulated by crops is increasingly considered essential for evaluating land contamination. Until now, there has been a lack of methods to adequately quantify the contamination status of soil–crop agroecosystems. We propose a ‘trinity’ assessment method covering total, available, and accumulated HMs involving a catastrophe-progression method and fusion algorithm. A typical urban–rural transition zone in NE China was selected for demonstration of the method and to identify HM spatial patterns associated with the impact of urbanization using GIS-based bivariate Moran's I analysis. Results indicate a spatial mismatch between total, available, and accumulated HM concentrations. Traditional methods indicate that soil–crop systems generally have less contamination and lower risk levels, whereas contaminated areas defined more holistically by the trinity method have a decreasing urban–rural trend. Furthermore, the bivariate Moran's I analysis indicates that land-use conflicts cause spatial clustering of HM contamination in cultivated lands where urbanization and industrialization have led to HM accumulation. Cluster patterns are significantly associated with the transition from urban to rural areas. These findings suggest that the trinity soil–crop system provides a practical tool for the quantitative assessment of the HM contamination status of peri-urban agriculture in major grain-producing areas, aiding the development of managerial strategies to prevent the occurrence of ecological hazards.

High crop yield losses induced by potential HONO sources — A modelling study in the North China Plain

Nitrous acid (HONO) is a major source of hydroxyl radicals in the troposphere through its photolysis, and can significantly influence ozone (O3) levels, thereby causing considerable crop yield losses. Previous studies have assessed relative crop yield losses by using exposure-response equations with observed or simulated O3, however, the contribution of enhanced O3 due to potential HONO sources to the crop yield losses has never been quantified. In this study, for the first time, we evaluated the crop yield losses caused by potential HONO sources in the North China Plain (NCP), which is one of the major grain-producing areas in China suffering from heavy O3 pollution, by using the Weather Research and Forecasting/Chemistry (WRF-Chem) model during the wheat and maize growing seasons of 2016. HONO simulations were significantly improved after including six potential HONO sources in the WRF-Chem model. The potential HONO sources produced a daily maximum 8-h O3 enhancement of 8.1/8.2 ppb during the wheat/maize growing seasons, respectively, and led to ~11.4%/3.3% relative yield losses for wheat/maize, respectively, corresponding to approximately US$3.78/0.66 billion losses, respectively, in NCP in 2016. The above results suggest that potential HONO sources play a significant role in O3 formation and could induce high crop yield losses globally.

Research on the degree of coupling of the Internet development level and agricultural--Ecological efficiency based on 2009-2018 data from 13 major grain-producing areas in China.

Agricultural informatization and agricultural green development are important components of modern agricultural development, and coordination between the two is an important foundation for achieving sustainable agricultural development. This paper uses data from the 13 major grain producing areas in China from 2009 to 2018 to analyze the coordination of the Internet development level and the agricultural ecological-efficiency, and it further investigates the degree of coupling and coordination between the two. The results of theis study are as follows.(1) The Internet development level of China's 13 main grain production areas has been continuously improving. The average Internet penetration rate increased from 0.25 in 2008 to 0.54 in 2018. (2) The agricultural ecological efficiency of China's main grain production areas has gradually improved. The average value of agricultural ecological efficiency increased from 0.45 in 2009 to 0.79 in 2018. (3) The Internet development level in China's main grain production areas and the continuous improvement of coordination and degree of coupling of the agricultural ecological efficiency show that the interaction between them has led to continuous improvements in the agricultural informatization development and agricultural green development. However, the coordination between the two still has significant room for growth, and there is a certain gap between the different regions.

Agricultural Water Use Efficiency and Rebound Effect: A Study for China.

Agricultural water use accounts for the largest proportion of water withdrawal, so improving agricultural water use efficiency is an important way to alleviate water shortage. However, the expected water saving by the improved agricultural water use efficiency may be offset by the rebound effect, which means the goal of water saving by improving agricultural water use efficiency is not achieved. Based on the definition of the rebound effect of agricultural water use, this paper first uses a fixed model to measure the causal effect of agricultural water use efficiency on agricultural water use to analyze the agricultural water rebound effect, then analyses the heterogeneity and mechanism of the effect of agricultural water use efficiency on agricultural water use with the panel data from 30 provinces or cities in China from 2000 to 2017. The results show that, firstly, the agricultural water use efficiency has a significant negative effect on agricultural water use, but the average agricultural water rebound effect is 88.81%. Secondly, the effect of agricultural water use efficiency on agricultural water use is heterogeneous, in which the improvement of agricultural water use efficiency in humid or major grain-producing areas will have a lower agricultural water rebound effect. Finally, agricultural water use efficiency can affect agricultural water use through planting area and planting structure. An increase in agricultural water use efficiency will expand the planting area to increase water use. However, this will change the planting structure to decrease water use. The implication for agricultural water management is that the irrigation agricultural scale has to be controlled under the condition of available water resource, while improving agricultural water use efficiency.

Approach for optimizing the water-land-food-energy nexus in agroforestry systems under climate change

CONTEXTAgroforestry systems are widely promoted for their economic and environmental benefits. Food, energy, water and land resources in agroforestry systems are inextricably intertwined and expected to be severely impacted by climate change. Socioeconomic development and increasing populations have posed unique challenges for meeting the demand for food, energy, water and land, and the challenge will become more pressing under projected resource shortages and eco-environmental deterioration. Thus, a method of optimizing and sustainably managing the water-land-food-energy nexus in agroforestry systems under climate change must be developed. OBJECTIVEThis paper develops an optimization model framework for the sustainable management of limited water-land-food-energy resources in agroforestry systems under climate change. The aims are to (1) quantify the interactions and feedbacks within water, land, food and energy subsystems; (2) provide trade-offs among water and energy utilization efficiency, economic benefits and environmental protection in agroforestry systems; and (3) generate optimal policy options among water and land resources for different crops and woodlands in different regions under different climate change patterns. METHODSThe model framework is based on multiobjective fractional programming, and compromise programming is used to solve it. Climate change patterns are obtained from atmospheric circulation models and representative concentration pathways. The above aims are investigated through an actual nexus management problem in northeast China. Spatiotemporal meteorological and report-based databases, life cycle assessments, Pearson correlation analyses, data envelopment analyses and analytic hierarchy processes are integrated to realize practical application. RESULTS AND CONCLUSIONSThe results show that climate variation will change the water and land allocation patterns and these changes will be more pronounced for major grain-producing areas. The optimized water allocation decreased (especially for rice, e.g., the optimal average value of the irrigation quota of rice was 4226 m3/ha, while the corresponding actual irrigation requirement of rice was [4200–7200] m3/ha) to improve the water use efficiency, and surface water allocation accounted for two-thirds. Maize had the largest planting area, although planting soybean generated the most greenhouse gases (greenhouse gas emissions from field activities for rice, maize, and soybean were 43.46%, 84.06% and 91.16%, respectively); However, these gases can be absorbed by forests. The model improved the harmonious degree of the resource-economy-environment system from 0.24 to 0.56 after optimization. SIGNIFICANCESIntegrated models contribute to the sustainable management of water, food, energy and land resources and can consider the complex dynamics under climate change. It can be used as a general model and extended to other agroforestry systems that show inefficient agricultural production.

First report of Heterodera filipjevi on winter wheat from Hebei Province in North China.

First report of Heterodera filipjevi on winter wheat from Hebei Province in North China.

Dilemma and solution of land scarcity, agro-production, and environmental risk for typical grain-producing areas in rapid urbanizing process in China.

How to satisfy food production sustainably in the rapid urbanizing process is a vital problem for major grain-producing areas. Taking two national grain-producing regions in China, Shandong and Dongting Lake Region as examples, this study uses step-by-step prediction and a double-objective linear programming model to analyze the dilemma of land scarcity, food demand, and environmental load. It is found that food demand by 2030 will induce partial regional cropland deficiency and heterogeneous agro-environmental risk among cities. The double-objective linear programming model finds possible solutions in different scenarios: on the premise of keeping the current cropland area unchanged, the upper threshold of crop yield by 2030 will be 2539.06 × 104 t in Dongting and 7175.13 × 104 t in Shandong, respectively. On the condition of guaranteeing food self-sufficiency and minimizing the environmental load, the lower threshold of arable land area should be 99.47 × 104 ha in Dongting and 436.85 × 104 ha in Shandong. Pollutant reduction will be realized by reallocation of agro-production task and optimized practices. The food carbon impact can be reduced by up to 1.27 kg CO2 eq/kg. This study contributes to feasible pathways towards adequate agro-production, lessened land scarcity, and minimal environmental risk for rapid urbanizing cities in a sustainable way.

Assessing the Sensitivity of Main Crop Yields to Climate Change Impacts in China

Quantitatively assessing the spatial divergence of the sensitivity of crop yield to climate change is of great significance for reducing the climate change risk to food production. We use socio-economic and climatic data from 1981 to 2015 to examine how climate variability led to variation in yield, as simulated by an economy–climate model (C-D-C). The sensitivity of crop yield to the impact of climate change refers to the change in yield caused by changing climatic factors under the condition of constant non-climatic factors. An ‘output elasticity of comprehensive climate factor (CCF)’ approach determines the sensitivity, using the yields per hectare for grain, rice, wheat and maize in China’s main grain-producing areas as a case study. The results show that the CCF has a negative trend at a rate of −0.84/(10a) in the North region, while a positive trend of 0.79/(10a) is observed for the South region. Climate change promotes the ensemble increase in yields, and the contribution of agricultural labor force and total mechanical power to yields are greater, indicating that the yield in major grain-producing areas mainly depends on labor resources and the level of mechanization. However, the sensitivities to climate change of different crop yields to climate change present obvious regional differences: the sensitivity to climate change of the yield per hectare for maize in the North region was stronger than that in the South region. Therefore, the increase in the yield per hectare for maize in the North region due to the positive impacts of climate change was greater than that in the South region. In contrast, the sensitivity to climate change of the yield per hectare for rice in the South region was stronger than that in the North region. Furthermore, the sensitivity to climate change of maize per hectare yield was stronger than that of rice and wheat in the North region, and that of rice was the highest of the three crop yields in the South region. Finally, the economy–climate sensitivity zones of different crops were determined by the output elasticity of the CCF to help adapt to climate change and prevent food production risks.

Soil-Quality Assessment during the Dry Season in the Mun River Basin Thailand

The Mun River Basin is one of Thailand’s major grain-producing areas, but the production is insufficient, and most of the cultivated lands are rain-fed and always unused in the dry season. All this makes it necessary to determine the status of soil nutrients and soil quality in the dry season to improve soil conditions, which will be useful for cultivation in the farming period. The aim of this study was to construct a soil-quality assessment based on soil samples, and in the process the minimum data set theory was introduced to screen the assessment indicators. The geographically weighted regression method was used to complete the spatial interpolation process of indicators, and the fuzzy logic model was constructed to evaluate the soil quality. The results showed that the spatial distributions of soil quality and indicators were similar. The soil quality was the best in the upstream while poor in the downstream, and the dry fields in the west and the forests in the east of the basin were better than other areas nearby. However; the soil qualities of paddy fields in the middle and east of the basin were poor due to the lack of soil nutrient supply when the fields were unused

Measurement, Temporal-spatial Evolution Characteristics and Countermeasures of High-quality Agricultural Development in China

The evaluation system of China’s high-quality agricultural development is constructed from four aspects: efficiency improvement, innovation-driven, green development, and coordinated sharing, which level is measured based on the entropy weight method (EWM), Besides, using the Theil index decomposition, spatial clustering and convergence theory, this paper analyzes the temporal-spatial evolution characteristics of high-quality agricultural development from 2003 to 2017. The results show that it has obvious spatial agglomeration and convergence in China. First, the quality of China’s agricultural development has steadily improved; besides, the provinces with it are mainly concentrated in the major grain-producing areas in the Northeast Plain and the Yangtze River Basin. Second, it is characterized by conditional convergence in China, and there are also club convergence in major grain-producing areas and non-major grain-producing areas. Third, the conditional convergence rate is 0.067-0.071, the half-life is about 11-12 years, the conditional convergence rate of the main and the non-main production area are 0.095 and 0.075, and the half-life is about 8 years and 10 years, respectively. Finally, combined with the specific statistical indicators, this paper sorted out the reasons restricting the high-quality development of agriculture in various regions and put forward the corresponding countermeasures.

Incentives or restrictions: policy choices in farmers’ chemical fertilizer reduction and substitution behaviors

Abstract Based on 804 samples of farmers in Hubei Province, a typical major grain-producing area in China, this study empirically analyzed the effects of two different policy tools, i.e. economic incentives (subsidies) and order enforcements (regulatory restrictions), as well as the effects of their interaction, on farmers’ chemical fertilizer reduction and substitution behaviors. Samples were grouped according to the degree of concurrent employment to analyze the effects on different groups. The results show that (1) the influences of these policies on the behaviors were significantly positive; (2) after constructing the interactive variables of the policies, the influence of the order enforcement policy was no longer significant, but the influence of the interaction was significantly positive; (3) the low-degree concurrent employment farmers were more likely to be affected by the order enforcement policy, whereas the high-degree ones were more affected by the economic incentive policy; and (4) the behaviors of the low-degree ones were strongly affected by family management characteristics, whereas the high-degree ones were more affected by the farmers’ individual characteristics.

Cropland heterogeneity changes on the Northeast China Plain in the last three decades (1980s-2010s).

The Northeast China Plain is one of the major grain-producing areas of China because of its fertile black soil and large fields adapted for agricultural machinery. It has experienced some land-use changes, such as urbanization, deforestation, and wetland reclamation in recent decades. A comprehensive understanding of these changes in terms of the total cropping land and its heterogeneity during this period is important for policymakers. In this study, we used a series of cropland products at the 30-m resolution for the period 1980–2015. The heterogeneity for dominant cropland decreased slowly over the three decades, especially for the large pieces of cropland, showing a general trend of increased cropland homogeneity. The spatial patterns of the averaged heterogeneity index were nearly the same, varying from 0.5 to 0.6, and the most heterogeneous areas were mainly located in some separate counties. Cropland expansion occurred across most of Northeast China, while cropland shrinking occurred only in the northern and eastern sections of Northeast China and around the capital cities, in the flat areas. Also, changes in land use away from cropland mainly occurred in areas with low elevation (50–200 m) and a gentle slope (less than 1 degree). The predominant changes in cropland were gross gain and homogeneity, occurring across most of the area except capital cities and boundary areas. Possible reasons for the total cropland heterogeneity changes were urbanization, restoration of cropland to forest, and some government land-use policies. Moreover, this study evaluates the effectiveness of cropland policies influencing in Northeast China.

Impact assessment of agriculture, energy and water on CO2 emissions in China: untangling the differences between major and non-major grain-producing areas

ABSTRACT Due to the use of abundant fossil and non-fossil fuels, the agricultural sector has contributed to large amounts of carbon dioxide (CO2) emissions in China. Meanwhile, the agricultural sector is the largest consumer of water in China. To investigate the effects of agricultural output, energy consumption and water use on CO2 emissions in China, a panel of 30 provinces for 2004–2017 is utilized. Also, to control the potential endogeneity, the orthogonal-difference Generalized Method of Moments (GMM) is used as the benchmark estimation method. Moreover, the Dumitrescu and Hurlin (D-H) panel causality test is employed to discover the causal relations among all the variables. Considering the differences in various agricultural areas in China, the 30 provinces are further divided into major and non-major grain-producing areas. The empirical results indicate that CO2 emission is responsive to economic growth, energy consumption, agricultural output and water use with positive elasticities in China. However, at the regional level, agricultural output only has significant impact on CO2 emissions in major grain-producing areas. Also, major and non-major grain-producing areas provide mixed directionality of causality among the variables. Finally, several policy implications are highlighted for the Chinese government with respect to mitigating CO2 emissions and promoting growth in the agricultural sector.

Changes in China's Grain Production Pattern and the Effects of Urbanization and Dietary Structure

Grain production patterns are the basis of a nation's food security. Since China's reform and opening-up began in 1978, China's urbanization process, driven by rapid social and economic development, has accelerated steadily. During this time, the dietary structure of urban and rural Chinese has also changed significantly. Accordingly, grain production patterns have undergone major changes. First, traditional grain production patterns in the north and the south have changed, and the food production center has shifted toward the north. In 1980, the grain yield of southern provinces accounted for 60% of China's total, while that of northern provinces accounted for 40%. In 2015, the grain yield of southern provinces accounted for 56% of the total, while that of northern provinces accounted for 44%. Second, grain production by regions of the country is “shrinking in the east but expanding in the central regions,” meaning that grain production in eastern coastal provinces has decreased significantly, while that in the central region has expanded. The proportions of the nation's total grain production from the eastern, central and western regions were 38%, 36% and 26%, respectively, in 1980. These had changed to 27%, 46%, and 27%, respectively, in 2015. Third, the spatial centralization of grain production has increased. The total grain yield of 13 major grain-producing provinces and regions in the country accounted for 69.27% of nation's total in 1980, and it had reached 76.18% in 2015, showing that the impact of major grain-producing areas on national food security has increased. The influence of rapid urbanization on grain production areas shows remarkable regional differences. As the level of urbanization has increased, build-up land occupies a large number of high-quality farmland, especially in east coastal provinces and thus the grain planting area decreased obviously. The effect of dietary structure changes on grain production patterns was evident in two ways. On the one hand, as dietary diversity has increased, total grain consumption has decreased. The reduction in the proportion of planting area for grain crops to total crop planting area dropped from 82% in 1980 to 68% in 2015, making this change in total grain consumption evident. On the other hand, the ratio of grain for human consumption declined as the ratio of grain consumed by animals increased. The reduction in the proportion of rice and wheat grown and an increase in the proportion of feed grain production (mostly maize) from 20% in the 1980s to 36% in 2015 makes this change in grain production and consumption evident. In the future, with the establishment of national functional areas for grain production, the spatial pattern of grain production will return, while the demand for feed grains will continue to increase but with the space for expansion limited.

Climate factors during key periods affect the comprehensive crop losses due to drought in Southern China

Southern China is a major grain-producing area, but has been suffering from increasingly serious droughts caused by global warming. As a result, crop losses have become serious. To provide insights into these losses, we obtained data to support a systematic and comprehensive analysis of how agricultural drought has caused crop losses from 1961 to 2011 and of the relationship between these changes and the climatic factors responsible for the losses. We found an obvious increase in the loss of crops due to agricultural drought in southern China, with the greatest increase in crop loss in the southwest and smaller increases in the south and southeast. Moreover, because each crop growth stage is affected differently by climatic factors and because the values of these factors show an uneven seasonal distribution, the losses were greatest when changes in various climatic factors occurred during key crop developmental periods. The fittings of the relationship between crop loss and various climatic factors was often strongest based on data from key developmental periods rather than based on data for the whole year. In addition, we found improved prediction of losses using multiple regression, and developed a model for assessing crop losses. Our results provide a scientific reference for developing methods to evaluate the losses caused by agricultural drought in southern China.

Changes in spatiotemporal drought characteristics over northeast China from 1960 to 2018 based on the modified nested Copula model

Drought forecasting is helpful for understanding the inherent mechanism of hydrological extremes and taking corresponding measures to mitigate drought impacts. Northeast China, which is an important, major grain-producing area in China, has been challenged by substantial losses due to frequent drought. In this study, to predict the spatiotemporal variation in drought events over Northeast China, a model-based simulation framework is proposed based on precipitation data at 70 meteorological stations from 1960 to 2018. The core of the model framework is run theory, modified Copula model- based Bayesian-MCMC, Gibbs sampling, and a new definition of drought intensity center and drought intensity accumulation area. The results showed that a total of 6408 drought events occurred at the 70 meteorological stations in Northeast China over the past 59 years. The empirical distribution functions of longitude, latitude, and time can be used to fit the edge distribution of the original variable. In comparison to the traditional maximum likelihood method, the Bayesian-MCMC method is more accurate for parameter estimation of the Copula model. The Frank Copula is the optimum joint function of longitude and latitude, while the Gaussian Copula is the optimum joint function of location and time. Gibbs sampling can provide a relatively larger sample size for predicting future drought conditions. The spatiotemporal variation in drought in Northeast China changes similarly throughout the year. Drought is mainly concentrated in southwestern Liaoning from February to April. The drought intensity center moves to the northeast from May to September. Western Heilongjiang is the main drought-stricken area from October to November. The drought intensity center moves southwest from December to January of the following year. This study provides a method for effectively predicting drought events and is of great significance to the protection, development, and utilization of water resources.

Regional 1932–1933 Famine Losses: A Comparative Analysis of Ukraine and Russia

AbstractThough the 1932–1933 Famine affected both Ukraine (UkrSSR) and Russia (RSFSR), there is still no clear concept of the causes of the Famine and its scale. This study is undertaken to make a comparative assessment of the 1932–1934 direct losses within and between UkrSSR and RSFSR in order to answer the questions as to whether the major grain-producing areas of both republics suffered from the Famine to the same extent and whether the intensity of regional losses was determined exclusively by the grain specialization of the region. Our results show that the regions seriously affected by the Famine comprised a much larger proportion (in terms of territory and population) of UkrSSR than of the RSFSR. The highest excess deaths in UkrSSR are found in the regions that did not play a major role in grain procurement, while in the RSFSSR four grain-producing regions suffered the most. Our analysis suggests that (a) the link between Famine losses and grain procurement is not confirmed in Ukraine, but is partially confirmed in Russia, and (b) extremely high losses are mostly found in the regions where repression policies were much more severe than those introduced elsewhere and for which nationality may be a key factor.

Spatio-Temporal Variation Characteristics and Driving Forces of Farmland Shrinkage in Four Metropolises in East Asia

The shrinkage of cultivated land is a general trend in metropolitan areas. However, previous studies have mainly paid attention to the shrinkage of arable land in major grain-producing areas, mixed agro-pastoral areas, ecologically fragile areas and construction areas of major engineering projects (such as the Three Gorges project). This paper analyses the characteristics and driving factors of cultivated land change on the metropolitan area scale and longer time dimension. Exemplified by four metropolises in East Asia, Tokyo, Beijing, Shanghai and Guangzhou, based on official statistics for the cities involved, using correlation analysis, principal component analysis and regression analysis methods and Statistical Product and Service Solutions (SPSS) 25 software, the main driving factors and differences in cultivated land shrinkage in Beijing, Shanghai, Guangzhou and the Tokyo metropolitan area are quantitatively revealed. The results show the following: (1) there are some differences in the shrinkage in arable land and spatial distributions among different cities. Tokyo and Guangzhou still have some cultivated land in central urban areas, while there is no arable land in the central areas of Beijing and Shanghai. (2) There is a clear difference in the main driving factors of cultivated land shrinkage between the Tokyo metropolitan area and Beijing, Shanghai and Guangzhou. Residential area and population are the main driving factors for the former, while economic development and urbanisation are the main driving factors for the latter three areas. It shows that the shrinkage of cultivated land is closely related to the developmental stage of urbanisation. (3) There is a rather obvious difference in the main driving factors of cultivated land change among Beijing, Shanghai and Guangzhou. Gross Domestic Product (GDP) is the primary factor leading to the shrinkage of arable land in Beijing, built-up area is the primary factor in Shanghai, and the Engel’s coefficient for rural residents is the primary factor in Guangzhou. This reflects the difference in measures for the utilisation and protection of cultivated land among different cities. (4) The socioeconomic factors that affect the contraction of cultivated land are varied. In this study, industrial restructuring is included in the evaluation index system, mainly because industrial transformation and upgrading is essential for sustainable development of emerging global cities, and agricultural production conditions are not included in the evaluation index system, mainly because they are more the result of urbanisation than the cause.

Evaluating the vulnerability of agricultural drought in Hetao Irrigation Area of Inner Mongolia Based on super efficiency DEA

Drought vulnerability has become a key point for agricultural sustainable development in such a changing context. In this study, Hetao Irrigation Area which is the major grain-producing area is selected as the research area, where frequent drought threatens food production. Firstly, super efficiency data envelopment analysis (SEDEA) model is used to evaluate the agricultural drought vulnerability of Hetao Irrigation Area from 1997 to 2016. And then the spatial and temporal differences of vulnerability are analyzed. Moran’s I Index is also adopted for further spatial autocorrelation analysis. The results show that the vulnerability decreases with the investment of agricultural science and technology, and the drought vulnerability in different irrigation fields are affected by the irrigation area coverage rate. The drought vulnerability is much higher in the east of Hetao Irrigation Area than that in the west due to the worse water supply in the east. And the vulnerability in Wuyan is the highest due to the largest cropping sown area, while Linhe stays the lower value due to the highest GDP.