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中国沙漠 ›› 2010, Vol. 30 ›› Issue (2): 369-375.

• 生物土壤与生态 • 上一篇    下一篇

绿洲灌区小麦水分生产率及其影响因素的灰色关联分析

胡广录1,2, 赵文智1*, 武俊霞3   

  1. 1.中国科学院 寒区旱区环境与工程研究所, 中国生态系统研究网络 临泽内陆河流域研究站, 甘肃 兰州 730000; 2.兰州交通大学 环境与市政工程学院, 甘肃 兰州 730000; 3.高台县水务局, 甘肃 张掖 734300
  • 收稿日期:2008-07-20 修回日期:2008-12-21 出版日期:2010-03-20 发布日期:2010-03-20

Gray Correlative Analysis of Wheat Water Productivity and Impact Factors in Oasis Irrigation Districts

HU Guang-lu1,2, ZHAO Wen-zhi1, WU Jun-xia3   

  1. 1.Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences; Linze Inland River Basin Research Station of China Ecosystem Research Network, Lanzhou 730000, China; 2.College of Environmental Science, Lanzhou Jiaotong University, Lanzhou 730070, China; 3.Gaotai County Bureau of Water Resources, Zhangye 734300, China
  • Received:2008-07-20 Revised:2008-12-21 Online:2010-03-20 Published:2010-03-20

摘要: 以黑河流域的洪水河灌区为例,利用1995—2006年的灌溉用水量、农作物产量、气象等资料,分析计算了绿洲灌区的小麦水分生产率。结果表明,1995—2000年小麦水分生产率为0.983 kg\5m-3,节水改造项目实施后的2001—2006年为1.070 kg\5m-3,提高了8.9%。水分生产率是衡量农业生产水平和农业用水科学性与合理性的综合指标,其影响因素比较多。根据洪水河灌区小麦生长发育期的实际情况,选取了11个影响因素进行灰色关联分析,结果显示,≥10 ℃积温、农药费用、劳动力和管理费用、化肥施用量、水费依次是影响水分生产率的前5位主要因素。研究表明,在有限的水资源利用条件下,绿洲灌区小麦生产应加大生产资料、劳动力和管理费用等的投入力度,才能生产更多的粮食,以确保区域粮食供给安全。

关键词: 小麦, 水分生产率, 影响因素, 灰色关联分析, 绿洲灌区

Abstract: Water productivity (WP) is not only an integrated criterion of agriculture production, but also an important index of the scientific soundness and reasonability of water use strategy. Taking HongShuiHe irrigation districts of the Heihe River Basin as an example, we estimated the WP of the spring wheat by collecting and using the irrigation water use, crop yields and weather data from 1995 to 2006. It was showed that the average water productivity of spring wheat is 0.983 kg\5m-3 during the period of 1995—2000, and the value has been increased 8.9% to 1.070 kg\5m-3 since the water-saving project was launched and realized during the period of 2001—2006. Due to the fact that there are many kinds of factors influent the value of WP, we chose the most possible factors (totally 11 factors ) to do a gray correlative analysis in the irrigation districts. The results indicated that the 5 most important factors controlling WP are cumulative temperature of ≥10 ℃, pesticide inputs, labor force and management investment, and chemical fertilization and agricultural water fees, respectively. We argued that more agricultural production materials, labor forces inputs, and management investment are necessary to produce more wheat and maintain the food supply safety of the irrigation districts, especially when considering the limited water resources in this region.

Key words: Spring wheat, water productivity, influential factors, gray correlative analysis, oasis irrigation districts

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