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Abstract: The Baiyangdian Catchment is facing a growing shortage of water resources. Identifying the sensitive drivers of evapotranspiration (ET) changes from land and crop management will be critical to understanding the reasons for mountainous runoff reduction and depletion of groundwater resources in the plain. It will also be important for making Xiong’an become a Future Example City for green and sustainable development. In this study, remotely sensed ET data from PML V2 products with a spatial resolution of 500 m was used to analyze the trend of ET at the pixel level and to understand its influence on vegetation such as GPP (Gross Primary Production) and NDVI (Normalized Difference Vegetation Index) under different land-use types for 2002‒2018. Results showed that there was a significant increase in ET in mountain regions and a slight increase in plain regions of the catchment. The spatial pattern of mean annual ET was very much relevant to the changing trend of GPP and NDVI. For the whole catchment, the average increases of ET, GPP, and NDVI were respectively 2.4 mm∙a−1, 9.8 g∙cm−2∙a−1, and 0.0021 at an annual rate. In the mountainous region, changes in annual precipitation and vegetation recovery together caused a total increase of ET by 56.5 mm over the period and negatively affected the runoff. In the plain region, there were 3 factors influencing the change of ET. While intensification of urbanization and reduction in the cultivation of wheat, the water consumptive crop, had both resulted in the decrease of ET and water consumption, ET or water consumption in most irrigated fields increased. Since the beneficial effects from urbanization and crop adjustment were not enough to offset the increase of ET in irrigated fields, an overall ET increase of 6.4 mm over the period was found. In conclusion, both in the mountainous and plain regions, ET increased. And therefore, more efforts are needed to control the ET increase in natural vegetation and cropland for a green and sustainable catchment.
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Keywords:
- Evapotranspiration /
- Vegetation change /
- Urbanization /
- Winter wheat /
- Irrigated land /
- Baiyangdian Catchment
摘要: 白洋淀流域位于雄安新区上游, 山区植被和下垫面变化、平原区农业灌溉加大了区域蒸散发, 造成山区产流减少和平原区地下水超采。研究区域蒸散发(ET)时空格局的演变趋势、甄别植被、作物种植结构、城市化等对蒸散发变化的影响, 对深入揭示白洋淀流域水资源枯竭的成因, 建设绿色雄安“未来之城”具有重要意义。本研究基于500 m空间分辨率的PML_V2遥感蒸散产品, 从像元尺度分析了2002—2018年研究区ET的变化趋势和显著性, 揭示植被变化、冬小麦压采、城市化等对山区和平原区ET的影响。结果表明, 1)研究时段内白洋淀流域ET和植被总初级生产力(GPP)及归一化植被指数(NDVI)均呈增加趋势, 平均增长量为2.4 mm∙a−1、9.8 g∙cm−2∙a−1和0.0021∙a−1。2)降雨和植被恢复带来的GPP、NDVI增长是山区ET增加的主要因素, ET与GPP和NDVI的趋势变化在空间分布上具有很好的相似性, 研究时段内山区ET增加56.5 mm。3)平原区ET受快速城市化、小麦种植面积压减和农田ET增加3个因素影响, 虽然城市化和小麦压减都带来蒸散发减少, 但仍无法抵消农田ET增加的效果, 平原区ET总体增长了6.4 mm。就整个流域而言, 减少山区植被和灌溉农田带来的ET增加对维持区域水资源可持续利用和绿色发展至关重要。 -
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Figure 1. Location of the Baiyangdian Catchment [ a: map of elevation with meteorological stations; b: map of land use types in 2020; the map is separated into the mountain region (Region Ⅰ) and plain region (Region Ⅱ) by the elevation of 100 m asl]
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Figure 2. Spatial distribution of annual average evapotranspiration (ET, a), gross primary production (GPP, b), and normalized difference vegetation index (NDVI, c) for the period of 2002–2018 in the Baiyangdian Catchment
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Figure 3. Variation and trend in annual evapotranspiration (ET) and precipitation (P) in mountain areas (Ⅰ), plain areas (Ⅱ), and the whole catchment (BYD)
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Figure 4. Trend and significance of Gross Primary Production (GPP) (a) and Normalized Difference Vegetation Index (NDVI, b) in mountainous areas (Ⅰ), plain areas (Ⅱ), and the whole catchment (BYD) from 2002 to 2018
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Figure 5. Temporal trends in evapotranspiration (ET, a), gross primary production (GPP, b), and normalized difference vegetation index (NDVI, c) in Baiyangdian Catchment for the period 2002–2018
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Figure 6. Temporal trends in monthly evapotranspiration (ET, a), gross primary production (GPP, b), and normalized difference vegetation index (NDVI, c) in the mountain region (Ⅰ), plain region (Ⅱ), and the whole catchment (BYD) for the period 2002–2018
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Figure 7. Correspondence of evapotranspiration (ET) changes (ET2014–2018 minus ET2002–2006) and Normalized Difference Vegetation Index (NDVI) changes (NDVI2014–2018 minus NDVI2002–2006) in pixels of the mountainous region (Region Ⅰ, a), urban (b) and cropland (c) in the plain region (Region Ⅱ)
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