| 摘要: |
| 中国作为世界农业大国之一，农业可持续发展受到水资源短缺的限制。提高农作物水生产力是保障粮食安全和缓解水资源供需矛盾的最有效措施之一。为揭示中国(统计数据未包含港、澳、台地区。下同)各省份主要粮食作物水分生产力的时空演变特征，基于气象数据和统计产量，首先计算得到中国各省份玉米、小麦的水分生产力，并利用相关分析、共线性诊断以及偏最小二乘回归分析法对选取的各气象因素和管理因素进行分析，以确定影响中国玉米和小麦水生产力的主要因素。结果表明: 1)2010—2019年我国玉米和小麦的水生产力均呈现增长趋势，变化范围分别为1.19~1.33 kg/m3和0.90~1.04 kg/m3。在九大农业分区中，玉米水生产力的高值出现在东北平原区，其中吉林省玉米水生产力达到最大值2.00 kg/m3；小麦水生产力的高值出现在长江中下游地区和华南区，其中位于华南区的广东省小麦水生产力达到最大值1.91 kg/m3。2)根据相关性分析和偏最小二乘回归分析结果发现影响玉米水生产力的主要因素为年蒸散量和单位面积产量，影响小麦水生产力的主要因素为单位面积产量、化肥折纯用量、播种密度、年平均气温、年平均相对湿度以及土壤因素中的全氮、全磷、全钾、土壤容重(土层厚度0~30 cm)和土壤有机碳(0~100 cm)。本研究结果对提升我国玉米和小麦水生产力具有积极的参考价值。 |
| 关键词: Penman-Monteith模型 作物水生产力 影响因素 偏最小二乘回归分析 |
| DOI：10.11841/j.issn.1007-4333.2023.12.01 |
| 投稿时间：2023-04-28 |
| 基金项目:国家自然科学基金面上项目(51979273) |
|
| Analysis of spatio-temporal evolution of water productivity patterns of major crops in China |
|
BAO Yongfang,FAN Yunfei,WU Xinlei,WANG Sufen
|
| (College of Water Resources & Civil Engineering, China Agricultural University, Beijing 100083, China) |
| Abstract: |
| As one of the major agricultural countries in the world, the sustainable development of agriculture in China is limited by the shortage of water resources. Improving crop water productivity is one of the most effective measures to ensure food security and alleviate the contradiction between supply and demand of water resources. To reveal the spatio-temporal evolution characteristics of the water productivity(WP)of main grain crops in various provinces of China(Data do not include those of HongKong, Macao and Taiwan regions. The same below), this study calculated the WP of maize and wheat in various provinces of China based on meteorological data and statistical yield, and analyzed the selected meteorological and management factors by using correlation analysis, collinear diagnostic analysis and partial least squares regression analysis, to determine the main factors affecting the WP of maize and wheat. The results showed that: 1)The WP of maize and wheat increased in the range of 1. 19-1. 33 kg/m3 and 0. 90-1. 04 kg/m3 from 2010 to 2019, respectively. In the nine agricultural regions, the high value of maize WP appeared in the Northeast Plain, and the highest value of maize WP was 2. 00 kg/m3 in Jilin Province. The value of wheat WP was high in the middle and lower reaches of the Yangtze River and South China, and the highest value of wheat WP was 1. 91 kg/m3 in Guangdong Province, which was located in South China. 2)According to the results of correlation analysis and partial least squares regression analysis discovered that the main factors affecting the WP of maize were annual evapotranspiration and yield per unit area, and that affecting wheat WP were yield per unit area, fertilizer amount, seeding density, annual mean air temperature, annual mean relative humidity, and total nitrogen, total phosphorus, total potassium, soil bulk density(soil thickness 0-30 cm)and soil organic carbon(0-100 cm)in soil factors. The results of this study have positive reference value for improving the water productivity of maize and wheat in our China. |
| Key words: Penman-Monteith model crop water productivity influencing factor partial least squares regression analysis |
