Variation of evapotranspiration and its response to vegetation productivity in the North China Plain
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摘要: 华北平原是我国粮食主产区, 水资源短缺是限制区域粮食生产和社会经济发展的重要因素。研究蒸散发动态变化、分析演变发展的驱动因素, 对于探明区域水资源演变、优化水资源管理具有重要参考价值。本文基于500 m空间分布率的PML_V2遥感蒸散产品, 选择华北平原和蒸散量变化存在差异的3类农业类型区的4个典型区: 以石家庄和保定为代表的山前平原区, 以衡水为代表的中部低平原区, 以德州为代表的黄河灌区, 对像元尺度蒸散发变化、变化的显著性和影响因素开展研究。结果表明: 1) 2001—2019年, 华北平原年均蒸散量为588.1 mm, 年际变化呈震荡波动上升态势; 小麦季蒸散量受地下水压采、休耕政策影响, 呈不显著下降趋势; 玉米季蒸散量上升趋势显著(P<0.05)。2)基于Theil-Sen Median斜率和Mann-Kendall方法的显著性检验结果表明, 蒸散量显著增加的区域主要位于中部低平原和黄河灌区; 不同土地利用类型下蒸散量变化有显著差异, 农业用地内有85.5%的地区蒸散量变化呈上升趋势, 其中有42.3%达到显著上升(P<0.05), 主要分布在黄河灌区一带, 城市化发展导致城市外围区蒸散量显著减少(P<0.05), 但在北京、天津等大城市内部蒸散量有增加趋势。3)蒸散量与总初级生产力(GPP)和归一化植物指数(NDVI)相关性分析表明, 蒸散量与GPP的相关性较高, 更能反映粮食主产区植被生产力对蒸散发的影响, 尤其在黄河灌区和中部低平原区均达到显著相关水平(P<0.05)。Abstract: The North China Plain is a main grain production area in China, where the shortage of water resources is the main factor restricting regional grain production and socioeconomic development. Clarifying the temporal and spatial variation of evapotranspiration (ET) and analyzing the main driving factors are critical for exploring regional water resource evolution and optimizing water resource management. Based on the PML_V2 (Penman-Monteith-Leuning Evapotranspiration V2) remote sensing ET product released in 2019 with a spatial resolution of 500 m and temporal resolution of 8-day, Theil-Sen Median slope estimation and Mann-Kendall trend analysis were used to evaluate the changing trend of ET; and the correlation coefficient method was used to analyze the relationship between ET and vegetation productivity. To evaluate the ET variation at the pixel scale, the significance of variation, and driving factors in four agricultural areas representing three agricultural area types were selected: Shijiazhuang and Baoding, Hengshui, and Dezhou, which represented the piedmont plain of Taihang Mountains, central low plain, and Yellow River irrigation area, respectively. The results showed that the annual average ET was 588.1 mm from 2001 to 2019 in the whole North China Plain, the interannual variability was characterized by a low-high-low dynamic trend, and the maximum (665.4 mm) and minimum (542.2 mm) ET occurred in 2015 and 2001, respectively. The ET trends during different crop growth seasons were significantly different. During the wheat growth season, the overall ET trend was declining, possibly resulting from the policies, such as wheat conversion to fallow, and limitation of groundwater pumping, which are being implemented to alleviate the groundwater funnel in North China. The overall ET trend was significantly upward in the corn growth season. Additionally, there were significant differences among the annual average ET for different land use types. The ET in 85.5% of the agricultural land areas showed an upward trend, of which 42.3% increased significantly and was mainly distributed in the Yellow River irrigation area. For the annual average ET in urban land, the areas with decreasing and increasing trends were 50.9% and 49.1%, respectively. Urbanization resulted in a significant decline in ET in the expanding areas of large cities, whereas an increasing trend was observed in the downtown regions of large cities, such as Beijing and Tianjin. Correlation analysis showed that areas with a positive correlation between ET and NDVI (normalized difference vegetation index) accounted for 76.54% of the North China Plain, and areas with a positive correlation between ET and GPP (gross primary production) accounted for 87.6% of the entire region. The stronger correlation between ET and GPP indicated the influence of higher crop productivity on ET in major grain-producing areas, which was also proven by the correlation between ET and vegetation productivity in the four typical agricultural areas. There were significant correlations between ET and GPP/NDVI in the Yellow River irrigation area represented by Dezhou. The only significant correlation between ET and GPP was observed for the central low plain, represented by Hengshui. Non-significant correlations between ET and GPP/NDVI were seen in the piedmont plain represented by Shijiazhuang and Baoding, possibly resulting from multiple ET driving factors, including vegetation productivity.
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图 2 2001—2019年华北平原全年和不同作物生长季的蒸散量(ET)变化特征
Figure 2. Evapotranspiration (ET) of year and crop growth seasons in the North China Plain from 2001 to 2019
图 3 华北平原全年及不同作物生长季蒸散量及其显著性变化趋势的空间分布
SI: 显著上升趋势; NSI: 不显著上升趋势; SD: 显著下降趋势; NSD: 不显著下降趋势。SI: significant increase; NSI: non-significant increase; SD: significant decrease; NSD: non-significant decrease.
Figure 3. Spatial distribution of evapotranspiration (ET) and its’ significant change trends in the North China Plain for annual and different crop growing seasons
图 4 2001—2019年华北平原及典型区不同土地利用类型蒸散量(ET)变化
Figure 4. Evapotranspiration (ET) under different land use types in the North China Plain and typical areas from 2001 to 2019
图 5 2001—2019年华北平原蒸散量(ET)与归一化植被指数(NDVI)、总初级生产力(GPP)的相关系数及显著性相关的区域
SPC: 显著正相关; SNC: 显著负相关。SPC: significantly positive correlation; SNC: significantly negative correlation.
Figure 5. Distributions of correlation coefficients and significance between evapotranspiration (ET), gross primary productivity (GPP) and normalized difference vegetation index (NDVI) in the North China Plain from 2001 to 2019
图 6 2001—2019年华北平原4个典型区域蒸散量(ET)、总初级生产力(GPP)、归一化植被指数(NDVI)的年际变化
Figure 6. Annual evapotranspiration (ET), gross primary productivity (GPP) and normalized difference vegetation index (NDVI) in four typical agricultural areas of the North China Plain from 2001 to 2019
图 7 华北平原4个典型农业区蒸散量(ET)与归一化植被指数(NDVI)、总初级生产力(GPP)的相关性
Figure 7. Correlations between evapotranspiration (ET) and normalized difference vegetation index (NDVI) / gross primary productivity (GPP) in four typical agricultural areas of the North China Plain
图 8 2001—2019年华北平原玉米季蒸散量(ET)与总初级生产力(GPP)的相关性及显著性
Figure 8. Correlation and significance between evapotranspiration (ET) and gross primary productivity (GPP) for corn growing season in the North China Plain from 2001 to 2019
表 1 数据类型、名称和来源及时空分辨率
Table 1. Data type, name and source, and temporal and spatial resolution used in the study
数据类型
Data type时间分辨率
Temporal resolution空间分辨率
Spatial resolution数据名称及来源
Data name and source蒸散发
Evapotranspiration (ET)8 d 500 m 全球PML_V2陆地蒸散发与总初级生产力(GPP)数据集
PML_V2 global evapotranspiration and gross primary (GPP) productionhttps://earthengine.google.com/ 总初级生产力
Gross primary productivity (GPP)8 d 500 m 全球PML_V2陆地蒸散发与GPP数据集
PML_V2 global evapotranspiration and GPPhttps://earthengine.google.com/ 归一化植被指数
Normalized Difference Vegetation Index (NDVI)月度 Month 1 km 中国月度1 km归一化植被指数(NDVI)空间分布数据集
China month vegetation index (NDVI) spatial distribution datasethttps://www.resdc.cn/Default.aspx 土地利用
Land use— 30 m 30 m全球地表覆盖数据
GLOBELAND30http://www.globallandcover.com/home.html?type=data 
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表 2 2001—2019年华北平原不同土地利用类型蒸散变化显著性区域面积比例及主要分布区
Table 2. Significant area proportions and main distribution areas of evapotranspiration change under different land use types in the North China Plain from 2001 to 2019
土地利用类型
Land use type面积比例 Area proportion (%) 分布区 Distribution area 增加趋势
Increasing显著增加趋势
Significant increasing减少趋势
Decreasing显著减少趋势
Significant decreasing增加区域
Increasing area减少区域
Decreasing area农业用地
Agricultural land85.5 42.3 14.5 1.0 黄灌区、太行山前平原
Yellow River irrigation area / Piedmont plain of the Taihang Mountains与城市交界地带
Junction with the city城市用地
City land49.1 11.4 50.9 8.6 北京、天津主城区
Main urban areas of Beijing and Tianjin大部分城市区域
Most urban areas
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