Global warming is one of the greatest threats to the social development of human beings. It is a typical example of global climate change, and has profoundly affected human production and life in various aspects. As the foundation of human existence, agricultural production is particularly vulnerable to climate change, which has altered environmental factors such as temperature, precipitation, and wind speed, and affected crop growth cycles, the frequency of extreme weather events, and the occurrence patterns of pests and diseases directly or indirectly, ultimately influencing crop yield and quality. This article reviews the latest research progress in this field, summarizes the impact of global climate change on agricultural production as well as the feedback mechanisms of agricultural activities on climate change, and proposes strategies for agricultural production to cope with global climate change. This paper aims to provide a scientific basis and suggestions for ensuring the sustainable development of agricultural production.

Wheat is a staple crop widely sown in Northwest China, and understanding and modelling evapotranspiration (ET) during the wheat-growing stage is important for irrigation scheduling and the efficient use of agricultural water resources. In this study, a four-year observation was conducted on a spring wheat field with border irrigation (BI) treatment and drip irrigation (DI) treatment, based on two Bowen ratio energy balance (BREB) systems. The results showed that the average ET across the whole growing stage scale was 512.0 mm for the BI treatment and 446.9 mm for the DI treatment, and the DI treatment reduced ET by 65.1 mm across the growing stage scale. The driving factors of the changes in ET in the two treatments were investigated using partial correlation analysis after understanding the changing pattern of ET. Net radiation (Rn), soil water content (SWC), and leaf area index (LAI) were the main meteorological, soil, and crop factors leading to the changes in ET in the two treatments. In terms of ET simulation, the SWAP model and different types of machine learning algorithms were used in this study to numerically simulate ET at a daily scale. The total ET values simulated by the SWAP model at the interannual scale were 11.0–14.2% lower than the observed values of ET, and the simulation accuracy varied at different growing stages. In terms of the machine learning simulation of ET, this study is the first to apply five machine learning algorithms to simulate a typical irrigated wheat field in the arid region of Northwest China. It was found that the Stacking algorithm as well as the SWAP model had the optimal simulation among all machine learning algorithms. These findings can provide a scientific basis for irrigation management and the efficient use of agricultural water resources in spring wheat fields in arid regions.

Two years of field experiments were conducted at the National Field Observation Experiment Station for Efficient Agricultural Water Use in the Wuwei Oasis, Gansu Province. Based on the eddy correlation system, the evapotranspiration (ET) of the cabbage agroecosystem during the growth period was obtained and the main driving factors of ET changes were determined. The Root Zone Water Quality Model 2.0 version (RZWQM2 model) was used to simulate ET during the growth period. The results showed the following: (1) The ET of cabbage during the growth period was 260. 1 ± 24.2 mm, which was basically lower than other crops planted in this area. (2) Through partial correlation analysis and principal component analysis, it can be found that environmental and physiological factors jointly drive changes in ET. The main driving factors include gross primary productivity, net radiation, and water use efficiency. (3) The RZWQM2 model can simulate the ET of the cabbage agroecosystem well, especially in simulating the total ET value and its trend. The growth period ET_s were 7.3% lower than the ET_m. Cabbage is an important cash crop in Northwest China, and ET is an important component of the water cycle in the agroecosystem. Determining the main driving factors of ET is of great significance for the sustainable utilization of agricultural water resources in Northwest China. Our results can provide a scientific basis for the cultivation of cabbage as a cash crop and the development of water saving agriculture.