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长春市玉米生产水足迹时序变化及影响因素研究 被引量:9

Temporal variability and influence factors of water footprint for maize production in Changchun
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摘要 对长春市1960—2012年53年来玉米生产水足迹进行了计算和分析.结果表明:长春市玉米生产水足迹呈显著下降趋势,组成结构不断变化,绿水、蓝水足迹比重降低,灰水足迹比重显著上升;玉米生产水足迹多年平均值为1.53m^3/kg,其中绿水占59%,蓝水占23%,灰水占18%,绿水是玉米生长的主要水源;玉米生产水足迹受气候和农业投入等因素影响,相同气候因子或农业投入对绿水、蓝水、灰水、总水足迹的影响程度不同,其中生长季积温、风速、化肥施用量和农业机械总动力对水足迹的影响较大. Changchun is one of the commercial food production bases in China, with maize as the main crop. This study analyzed the interannual variability and influential factors of total water footprint and green,blue and grey water footprints of maize production in Changchun from 1960 to 2012. Results indicate that:the total water footprint of maize production showed a significant downward trend, and the composition structure of the total water footprint is constantly changing. The green and blue water footprints presented decreasing trends, hut the grey water footprint had a clear increasing trend; the multi-year average water footprint of maize production was 1.53 m^3 /kg, which was 59% green,23% blue,and 18% grey. The major portion of maize production water footprint was green water; water footprint of maize production was affected by meteorological factors and agricultural inputs, among which the wind speed, accumulated temperature during growth period, machinery power and fertilizer input were the main factors. The influence of the same meteorological factors and agricultural inputs on the green, blue,grey and total water footprint varies. According to this study,it clearly shows that green water occupies an important position in maize production in Changchun,.and it is useful for the rational utilization of water resources, the protection of ecological environment and the sustainable agricultural development.
出处 《东北师大学报(自然科学版)》 CAS CSCD 北大核心 2017年第2期120-126,共7页 Journal of Northeast Normal University(Natural Science Edition)
基金 国家自然科学基金资助项目(41571526) 国家水体污染控制与治理科技重大专项课题(2014ZX07201-011)
关键词 玉米 生产水足迹 长春市 年际变化 影响因素 maize production water footprint interannual variability influence factors
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