Spatial-Temporal Differences in Water Footprints of Grain Crops in Northwest China: LMDI Decomposition Analysis

Competitiveness and sustainable development of Chinableapple industry

Agriculture faces a contradiction between sustainable resource utilization and maintaining market competitiveness. As a major agricultural product, the sustainability and competitiveness of the apple industry have become important topics. This study analyzes the competitiveness of China’s apple industry and the factors affecting it. Using 2004 and 2018 data for eight Chinese provinces, principal component analysis and spatial autocorrelation are used to examine competitiveness in terms of five aspects: market, production, technology, organization, and environment. The results indicate that Shandong, Shaanxi, and Gansu were the most competitive during the study period while Hebei, Henan, and Ningxia lagged behind. Regional differences are obvious, with Shandong in particular showing a clear competitive advantage. Although no spatial agglomeration is observed in China’s apple industry, with ongoing industrial development, local spatial correlations in the five aspects of competitiveness in the eight provinces have been increasing and gradually stabilizing. This study’s findings suggest that improved scientific production, reasonable capital investment, and an established industrial chain are needed to promote local agriculture, economic development, and the central role of the apple industry.

The impact of climate changes on the water footprint of wheat and maize production in the Nile Delta, Egypt

Spatial-temporal information of different water resources is essential to rationally manage, sustainably develop, and optimally utilize water. This study focused on simulating future water footprint (WF) of two agronomically important crops (i.e., wheat and maize) using deep neural networks (DNN) method in Nile delta. DNN model was calibrated and validated by using 2006-2014 and 2015-2017 datasets. Moreover, future data (2022-2040) were obtained from three Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5, and incorporated into DNN prediction set. The findings showed that determination-coefficient between historical-predicted crop evapotranspiration (ET_c) varied from 0.92 to 0.97 for two crops. The yield prediction values of wheat-maize deviated within the ranges of -3.21% to 3.47% and -4.93% to 5.88%, respectively. Based on the ensemble of RCP, precipitation was forecasted to decease by 667.40% and 261.73% in winter and summer in western as compared to eastern, respectively, which will ultimately be dropped to 105.02% and 60.87%, respectively parallel to historical. Therefore, the substantial fluctuations in precipitation caused an obvious decrease in green WF of wheat (i.e., 24.96% and 37.44%) in western and eastern, respectively. Additionally, for maize, it induced a 103.93% decrease in western and an 8.96% increase in eastern. Furthermore, increasing ET_c by 8.46% and 12.45% gave rise to substantially increasing (i.e., 8.96% and 17.21%) in western for wheat-maize compared to the east, respectively. Likewise, grey wheat-maize WF findings reveals that there was an increase of 3.07% and 5.02% in western as compared to -14.51% and 12.37% in eastern. Hence, our results highly recommend the optimal use of the eastern delta to save blue-water by 16.58% and 40.25% of total requirements for wheat-maize in contrast to others. Overall, the current research framework and results derived from the adopted methodology will help in optimal planning of future water under climate change in the agricultural sector.