Spatial-temporal variations in green, blue and gray water footprints of crops: how do socioeconomic drivers influence?

ENVIRONMENTAL RESEARCH LETTERS(2022)

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摘要
Nowadays, more than 70% of global freshwater is used for agriculture. The evaluation of the water footprint of crops (CWFs) is an important method to measure the effects of crop production on water resource utilization and water environmental pollution. However, little attention is paid to the impact of socioeconomic development differences on the water footprint of each crop. In this study, the green, blue, and gray water footprints of crop production were quantified, and the socioeconomic drivers of changes in the CWFs were revealed. It is of great significance to provide targeted guidance for agricultural water management in Heilongjiang, a province with the largest crop production in China. Here, we show that the total water footprint of crop production (TWF) increased from 62.2 billion m(3) to 101.8 billion m(3), and high-value areas were mainly concentrated in the west and south of Heilongjiang Province. Over 95% of the total grain crops sown were covered by maize, rice and soybean, which presented the greatest TWF. The share of green water footprint in TWF has increased, and crop growth is increasingly dependent on rainfall. Furthermore, our results highlight that the effective irrigated quota and crop-planting scale for maize and rice contribute to TWF increase. The TWF and agricultural value-added score were weakly decoupling in most municipalities, indicating the improved efficiency of crop water use; the TWF is growing slower than the economy, which is undesirable. Changes in TWF and agricultural value-added score were the same as the left half of the inverted 'U of the 'Environmental Kuznets Curve', which has not reached the 'inflection point'. More efforts to control the effective irrigated quota and crop-planting scale while improving effective irrigated efficiency are needed to ensure that economic growth does not come at the expense of consuming enormous quantities of water.
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关键词
water footprint, socioeconomic driving factors, logarithmic mean divisia index (LMDI), Tapio decoupling, Heilongjiang
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