2000—2015年中国陆地生态系统蒸散时空变化及其影响因素
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摘要
准确量化区域蒸散时空格局及其影响因素对理解陆地生态系统碳水循环具有十分重要的意义。近年来中国经历了严重的空气污染及气候波动,亟须探讨蒸散的时空变化及其影响因素。基于PT-JPL(Priestly-Taylor Jet Propulsion Laboratory)模型,集成遥感数据和气象数据模拟了中国陆地生态系统2000—2015年蒸散,并分析其时空变化及影响因素。结果表明:1)参数优化后PT-JPL模型可解释蒸散年际变化的68%,优于原始模型及MODIS蒸散产品;2)中国地区多年平均蒸散为440.16 mm/a,呈东南沿海到西北内陆逐渐递减的空间格局;3)2000—2015年蒸散整体呈轻微下降趋势(slope=6.48 Gt/a,P=0.17),但具有年代际差异,2000—2010年中国地区蒸散呈显著下降趋势(slope=21.05,P<0.01),占全国蒸散总量45.05%的内蒙古地区、甘新地区、黄土高原地区及青藏地区解释了61.88%的年际变化;2010—2015年呈轻微上升趋势(slope=10.48,P=0.71),各地区均无显著变化趋势;4)辐射主导了蒸散的年代际差异,分别解释了2010年前后蒸散下降及上升趋势的51.45%、85.26%。蒸散呈显著变化趋势的内蒙古地区、黄土高原地区及青藏地区主要受辐射控制,甘新地区主要受降水和温度的影响。
Accurately quantifying the spatial and temporal patterns of regional evapotranspiration and their influencing factors has significant implications for understanding carbon and water cycles in the terrestrial ecosystem. Based on MODIS remote sensing data and meteorological data from 2000 to 2015, we used the modified Priestly-Taylor Jet Propulsion Laboratory(PT-JPL) model to simulate evapotranspiration and its spatial distribution in the Chinese terrestrial ecosystem and analyzed the temporal and spatial variation of evapotranspiration and its influencing factors. The results revealed the following. 1) The observation data demonstrated that the PT-JPL model with optimized parameters illustrated 68% of the seasonal variation and spatial distribution patterns of evapotranspiration better than the original model and the MODIS evapotranspiration product. 2) The mean evapotranspiration over the years was 440.16 mm/a with obvious spatial heterogeneity, gradually decreasing from the southeast coast to the inland of the northwest. 3) The total evapotranspiration showed a slight downward trend(slope = 6.48 Gt/a, P=0.17) from 2000 to 2015; however, there was an interdecadal difference as the evapotranspiration significantly decreased from 2000 to 2010(slope = 21.05 Gt/a, P<0.01). The Inner Mongolia region, Loess Plateau region, Gan-xin region, and Qinghai-Tibet region accounted for 45.05% of the total national evapotranspiration and 61.88% of the interannual change; these regions showed a slightly increasing but insignificant trend from 2010 to 2015(slope = 10.48 Gt/a, P=0.71). 4) Radiation was the main influencing factor of the trend of evapotranspiration before and after 2010, accounting for 51.45% and 85.26% of the total, respectively.
Accurately quantifying the spatial and temporal patterns of regional evapotranspiration and their influencing factors has significant implications for understanding carbon and water cycles in the terrestrial ecosystem. Based on MODIS remote sensing data and meteorological data from 2000 to 2015, we used the modified Priestly-Taylor Jet Propulsion Laboratory(PT-JPL) model to simulate evapotranspiration and its spatial distribution in the Chinese terrestrial ecosystem and analyzed the temporal and spatial variation of evapotranspiration and its influencing factors. The results revealed the following. 1) The observation data demonstrated that the PT-JPL model with optimized parameters illustrated 68% of the seasonal variation and spatial distribution patterns of evapotranspiration better than the original model and the MODIS evapotranspiration product. 2) The mean evapotranspiration over the years was 440.16 mm/a with obvious spatial heterogeneity, gradually decreasing from the southeast coast to the inland of the northwest. 3) The total evapotranspiration showed a slight downward trend(slope = 6.48 Gt/a, P=0.17) from 2000 to 2015; however, there was an interdecadal difference as the evapotranspiration significantly decreased from 2000 to 2010(slope = 21.05 Gt/a, P<0.01). The Inner Mongolia region, Loess Plateau region, Gan-xin region, and Qinghai-Tibet region accounted for 45.05% of the total national evapotranspiration and 61.88% of the interannual change; these regions showed a slightly increasing but insignificant trend from 2010 to 2015(slope = 10.48 Gt/a, P=0.71). 4) Radiation was the main influencing factor of the trend of evapotranspiration before and after 2010, accounting for 51.45% and 85.26% of the total, respectively.
引文
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