Agricultural Vulnerability Assessment of High-Temperature Disaster in Shaanxi Province of China

Abstract

The negative impact of high-temperature disaster on agricultural production is becoming more and more serious, and reducing the vulnerability to high-temperature disaster is fundamental to achieving sustainable agricultural development. This study is mainly focused on the vulnerability to agricultural high-temperature disaster in Shaanxi Province, China. Firstly, 15 indicators were selected from the perspectives of exposure, sensitivity, and adaptability. Secondly, the combined weighting method (Critic-G1 model) was used to determine the weight of each index. Based on the aforementioned procedures, the Kullback–Leibler (KL)-distance-improved TOPSIS model was utilized to evaluate the vulnerability. Lastly, the obstacle model was used to analyze the influencing factors and to make recommendations for disaster prevention and mitigation. The results show that: (1) The improved TOPSIS model was closer to the results of the synthetical index method. (2) The northern and southern area of Shaanxi is more vulnerable to high-temperature disaster, especially in Ankang and Tongchuan. Low values are distributed in the Guanzhong Plain. (3) Sensitivity is the biggest obstacle to reducing the vulnerability to high-temperature disaster. Among the influencing factors, the meteorological yield reduction coefficient of variation, multiple cropping index and per capita net income of rural residents of the obstacle are high. Decreasing sensitivity should be accompanied by increasing adaptability to improve regional disaster preparedness and mitigation. The results of this study can provide a basis for the development of agricultural high-temperature disaster mitigation and loss reduction strategies and provide new ideas for future research.

Effects of Irrigation and N Fertilization on 15N Fertilizer Utilization by Vitis vinifera L. Cabernet Sauvignon in China

“…Using this irrigation and fertilization combination, only part of the N will be absorbed and utilized by the plant root system; some will be rapidly assimilated and will remain in the soil, and some will be lost through the leaching of nitrate N and denitrification as gaseous N. Thus, only a small amount of fertilizer will permeate below the root zone. This irrigation and fertilization technique saves water and fertilizer resources, reduces the loss of N, and decreases groundwater pollution [2][3][4].…”

“…Grape is one of the primary fruits cultivated in China and plays an important role in promoting local economic development and increasing agricultural income. At present, N management in many grape-producing areas in China is highly problematic [3][4][5] due to excessive and extensive N application, as well as the incongruous application of water and N, which negatively impacts soil physical, chemical, and biological properties and causes imbalances in soil water, fertilizer, gas, and heat factors, resulting in extensive soil hardening. This weakens the ability of the soil to provide a buffer against water stress and nutrient deficiencies, forcing farmers to irrigate more frequently and apply fertilizer regularly to maintain yields.…”

Spatial Vulnerability Assessment for Mountain Cities Based on the GA-BP Neural Network: A Case Study in Linzhou, Henan, China

“…With respect to the ecosystem, the aridity index [14], soil erosion intensity [48], and normalized difference vegetation index [42] were selected to characterize the ecosystem in terms of climate, soil, and vegetation, reflecting the likelihood of ecosystems being disrupted by external pressures. In the agricultural system, annual average precipitation, annual average temperature [49], slope, and distance from a water source [50] were selected to characterize the stability of mountainous agricultural production in terms of climate, topography, and water source, and farmland production potential [15] was selected to reflect the production stability of existing farmland. In the urban system, elevation, topographic undulation [16], and the rate of natural population increase [21,51] were selected to describe the stability of urban geography and population change.…”

Impact of demonstration zone policy on agricultural science and technology innovation: evidence from China

“…According to statistics, at present, the central government has invested more than 15 billion yuan in subsidies for the construction of the National Modern Agricultural Demonstration Zone, driving local support of approximately 12 billion yuan. Agriculture is highly dependent on the natural environment, which makes agriculture show greater vulnerability in the face of external factors such as climate change and natural disasters (Ma et al, 2022). Moreover, agricultural science and technology innovation has positive externalities and public goods attributes, which are important for the sustainable development of the agricultural sector and rural economy.…”