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引用本文:刘婷婷,朱秀芳,刘莹,徐昆.我国主要粮食作物蓝水用水时序分布图制作[J].中国农业资源与区划,2020,41(9):93~103
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我国主要粮食作物蓝水用水时序分布图制作
刘婷婷1, 朱秀芳1,2, 刘莹1, 徐昆1
1.北京师范大学地理科学学部,北京100875;2.北京师范大学北京市陆表遥感数据产品工程技术研究中心,北京100875
摘要:
[目的]明确实际蓝水用水的空间分布,有利于用水供需矛盾和水资源短缺分析,为进一步评价蓝绿水的投入量和利用效率,以及合理和高效管理农业水资源提供参考信息。然而目前有关农业用水的数据只有行政单元的统计数据,不利于进行空间分析。发展空间化模型,将统计数据空间化是解决该问题的有效途径。[方法]文章基于蓝水消耗量和蓝水需求量成正比的假设,构建蓝水用水空间化模型,利用气象数据、农业用水统计数据、灌溉农田分布图、主要粮食作物空间分布图、作物系数和生育期数据,生成2003—2012年1km分辨率的我国主要粮食作物(小麦、玉米和水稻)的蓝水用水空间分布图,分析蓝水用水的总体变化趋势以及影响各区域蓝水用水量的主导作物。[结果](1)华北地区平均蓝水用水量最高。(2)大多数灌溉区蓝水用水量没有显著变化,每年蓝水用水量的标准差低于0004km3。蓝水用水量变化率的绝对值在夏季最大、冬季最小。(3)就各地来说,蓝水用水总量增加趋势最明显的是江苏省,减少趋势最明显的是上海市。(4)就不同作物来说,小麦、玉米和水稻的蓝水用水量增加趋势最明显的分别是江苏、黑龙江、江西,减少趋势最明显的分别是北京和上海。(5)东南沿海地区主要影响蓝水用水量的作物为水稻,在东北及华北地区主要影响蓝水用水量的作物为玉米,其他部分地区主要影响蓝水用水量的作物为小麦。(6)局部验证结果显示该文计算出的蓝水用水量与统计发布的数据存在很高的相关性(R2=095)。[结论]该文发展的蓝水空间化模型可以用于时序蓝水用水分布图的制作,具有一定的应用推广价值。
关键词:  灌溉需水量蓝水用水量空间分配模型空间化粮食作物
DOI:
分类号:S27
基金项目:北京市陆表遥感数据产品工程技术研究中心资助项目; 国家“高分辨率对地观测系统”重大专项资助项目
DEVELOPMENT OF TIME SERIES GRIDDED MAPS OF MAJOR FOOD CROPS BLUE WATER CONSUMPTION IN CHINA
Liu Tingting1, Zhu Xiufang1,2, Liu Ying1, Xu Kun1
1.Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China;2.Beijing Engineering Research Center for Global Land Remote Sensing Products, Beijing Normal University, Beijing 100875, China
Abstract:
Defining the spatial distribution of actual blue water consume is beneficial to the analysis of water supply and demand contradiction and water shortage, and provides reference information for further evaluating the input and utilization efficiency of blue and green water, as well as rational and efficient management of agricultural water resources. However, the current data on agricultural water use are only the statistics of administrative units, which is not conducive to spatial analysis. The development of spatialization model to spatialize statistical data is effective way to solve this problem. Based on the hypothesis that the consumption of blue water was directly proportional to the demand of blue water, a spatial model of blue water was constructed in this paper. Using climatic data, agricultural water statistics, irrigation farmland distribution map, spatial distribution map of main grain crops, crop coefficient and growth period data, the gridded maps of major food crops blue water consumption in China with a resolution of 1 km from 2003 to 2012 were generated. The overall trend of blue water consumption and the dominant crops affecting the blue water consumption in different regions were analyzed. The results showed that the average blue water consumption in North China was highest. There was no significant change in blue water consumption in most irrigation districts. The standard deviation of blue water consumption per year was less than 0.004 cubic kilometers. The absolute change rate of water consumption of blue water was the largest in summer and the smallest in winter. As far as the provinces were concerned, the most obvious increasing trend of total blue water consumption was in Jiangsu province, and the most obvious decreasing trend was in Shanghai. For different crops, the most obvious increasing trend of blue water consumption of wheat, maize and rice occurred in Jiangsu, Heilongjiang and Jiangxi, and the most obvious decreasing trend occurred in Beijing and Shanghai. Rice was the main crop affecting blue water consumption in the southeast coastal area of China, maize was the main crop affecting blue water consumption in the northeast and North China, and wheat was the main crop affecting blue water consumption in other parts of China. Local validation results showed that the blue water consumption calculated in this paper was highly correlated with the statistical data (R2 = 0.95). The spatialization model of blue water developed in this paper can be used to make time series blue water distribution map, and has certain application value.
Key words:  irrigation water demand  blue water consumption  spatial distribution model  spatialization  grain crops
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