Cao Xinchun, Liu Zhe, Wu Mengyang, Guo Xiangping, Wang Weiguang. Temporal-spatial distribution and driving mechanism of arable land water scarcity index in China from water footprint perspective[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(18): 94-100. DOI: 10.11975/j.issn.1002-6819.2019.18.012
    Citation: Cao Xinchun, Liu Zhe, Wu Mengyang, Guo Xiangping, Wang Weiguang. Temporal-spatial distribution and driving mechanism of arable land water scarcity index in China from water footprint perspective[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(18): 94-100. DOI: 10.11975/j.issn.1002-6819.2019.18.012

    Temporal-spatial distribution and driving mechanism of arable land water scarcity index in China from water footprint perspective

    • Efficient water use in agriculture production system is widely accepted as an important foundation of regional water resources management, water shortage alleviation and environmental sustainability. The arable land water scarcity index (AWSI) to describe relationship between crop production and potentially water resources was established based on water footprint framework in current study. AWSI was defined as the ratio of total water footprint in regional crops cultivation to available agricultural water resources, including blue and green water. AWSI in 31 provinces, municipalities and autonomous regions of China from 1999 to 2014 was calculated. Then, the spatial-temporal pattern and driving mechanism in the observed period were explored with the help of the methods of spatial autocorrelation analysis. A total of 10 potential factors such as relative humidity (RH), average temperature (AT), precipitation (P), sunshine hours (SH), chemical fertilizer per area (CF), pesticides per area (PP), power of machinery per area (MP), irrigation rate (IR), irrigation efficiency (IE), proportion of grain area (GA) and per capita GDP (GP) were selected in driving mechanism assessment. Given that the high co-dependence of these potential factors, partial least squares regression (PLSR) was used to elucidate the linkages between the ASWI and the selected factors. The results showed that, annual value of AWSI in China was estimated about 0.413, and the country faced high water stress during the studied period; AWSI in almost all of the provinces, municipalities and autonomous regions increased over time, indicating that water scarcity in agricultural production system of China was intensifying. Spatial autocorrelation analysis showed that the global Moran's I was higher than 0 in all the calculated years, implying provinces, municipalities and autonomous regions with similar AWSI presented an obvious aggregation characteristic in agriculture production of China. Provinces with high AWSI was in the North China Plain and all the regions facing extremely high water stress (AWSI>0.800) were distributed in the north of China; most of the provinces located in south of the Yangtze River were classified as moderate water stress (0.100
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