| 摘要: |
| 目的 探究中国蒸散发时空变化规律，揭示耕地蒸散发特征与干旱灾害间的关系，为我国农业干旱灾害预警体系提供参考。方法 文章基于MODIS ET模型，将2001—2018年8天复合遥感数据及每日气象再分析数据输入模型估算陆面蒸散量，分析中国陆面蒸散量时空变化规律；根据土地覆盖类型提取中国耕地地块，探究中国耕地蒸散量变化特征；结合干旱灾害统计数据，揭示我国耕地地表类型中蒸散变化对干旱灾害的作用机制。结果 （1）2001—2018年中国陆地年总蒸散量和年均蒸散量总体呈上升趋势，空间上呈东南—西北逐渐减少的分布特征，高值区位于华南地区和西南地区，其次是华北地区，低值区位于东北地区和西北地区。（2）不同季节、不同月份之间蒸散发差异较大，夏季的蒸散量最高，春、秋次之，冬季蒸散量最小。（3）2001—2017年中国耕地面积呈现先增加后减少的趋势，2004年耕地面积达到峰值1.424亿hm2；截止2017年末，我国耕地面积达到谷值，为1.421亿hm2。（4）2001—2018年全国耕地年蒸散总量整体呈略微上升趋势，年际变化较大。五大粮食主产区中，长江中游及江淮地区年均蒸散量最大，四川盆地和黄淮海平原次之，三江平原和松嫩平原相对年均蒸散量最小。（5）在长江中游及江淮地区、四川盆地和黄淮海平原，蒸散发和干旱灾害具有较强的相关性；但在三江平原及松嫩平原，两者的相关性并不显著。结论 蒸散发作为大尺度可观测量在部分地区可以较好的反演干旱特征，研究中国不同下垫面蒸散发变化规律同时辅助其他变量，或许能为农业干旱监测预警进而估测粮食产量提供新的思路和方法。 |
| 关键词: 蒸散 MODIS 耕地 干旱 时空变化 |
| DOI：10.7621/cjarrp.1005-9121.20210905 |
| 分类号:P426.2;P426.616 |
| 基金项目:草地碳收支监测评估技术合作研究（2017YFE0104500）；中央级公益性科研院所基本科研业务费专项（1610132020014） |
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| TEMPORAL AND SPATIAL VARIATION OF EVAPOTRANSPIRATION IN CHINA AND ITS IMPACT ON DROUGHT OF CROPLAND |
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Yang Yanying1, Mao Kebiao1,2
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1.Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China;2.School of Physics and Electronic-Electrical Engineering, Ningxia University, Yinchuan 750021, Ningxia, China
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| Abstract: |
| The research aims to explore spatio-temporal characteristics of evapotranspiration in China and analyze the relationship between evapotranspiration and drought disasters, which can provide reference for China's agricultural drought disaster prediction system. Based on the MODIS ET model, we used the 8-day composite remote sensing data and daily meteorological reanalysis data from 2001 to 2018 to estimate the land surface evapotranspiration, in order to analyze the temporal and spatial variation of land surface evapotranspiration in China. Then, according to the land cover type, China's cropland was extracted to explore the characteristics of evapotranspiration. Combined with the statistics of drought disasters, the relationship between evapotranspiration of cultivated land types in China was analyzed. The results were indicated as follows.①The total annual evapotranspiration and annual average evapotranspiration of China's land showed an upward trend from 2001 to 2018, and the spatial distribution showed a decreasing distribution from southeast to northwest. High-value areas were located in South and Southwest China, followed by North China, and low-value areas were located in Northeast and Northwest. ②There were big differences in evapotranspiration in different seasons and different months. In summer, the evapotranspiration was the highest, followed by spring and autumn, and the evapotranspiration was the smallest in winter. ③From 2001 to 2017, the area of cultivated land in China showed a trend of increasing first and then decreasing. In 2004, the cultivated land area reached a peak of 1.424 hundred million hm2. By the end of 2017, China's cultivated land area reached a valley value of 1.421 hundred million hm2. ④From 2001 to 2018, the total annual evapotranspiration of cultivated land in the country showed a slight upward trend, with large interannual changes. Among the five major grain producing areas, the average annual evapotranspiration was the largest in the middle reaches of the Yangtze River and the Jianghuai area, followed by the Sichuan Basin and the Huanghuaihai Plain. The annual average evapotranspiration was relatively the smallest in the Sanjiang Plain and the Songnen Plain. ⑤In the middle reaches of the Yangtze River and the Jianghuai area, the Sichuan Basin, and the Huanghuaihai Plain, there was a strong correlation between evapotranspiration and drought disasters. However, in the Sanjiang Plain and the Songnen Plain, the correlation between the two was not significant. As a large-scale observation, evapotranspiration can better characterize drought characteristics in certain areas. By studying the changes of evapotranspiration in different land cover conditions in China, and adding more other variables, it can provide new ideas and methods for agricultural drought monitoring and forecasting, and even for crop yields estimating. |
| Key words: evapotranspiration MODIS cropland drought spatio-temporal variation |
