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Evaluation of MODIS-based estimates of water-use efficiency in Amazonia

机译:基于MODIS的亚马逊州用水效率评估的评估

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摘要

This study aimed to assess the spatial-temporal patterns of water-use efficiency (WUE) obtained through MODIS gross primary productivity (GPP) and evapotranspiration (ET) products (MOD17 for GPP and MOD16 for ET) in the Upper Tapajos and Curua-Una River basins, located in the oriental flank of the Amazon region, and to validate the results with flux tower measurements within the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) project. The spatial variation of WUE was primarily related to the larger presence of forested areas in the Upper Tapajos River basin (western part) compared with the Curua-Una River basin (eastern part), which is situated within the so-called arc of deforestation. Temporally, WUE showed a pronounced seasonal pattern, varying with the dry and wet seasons in the region. A decrease of similar to 3% in WUE was observed during the dry season, which was related to the low water availability and increased vapour pressure deficit during the dry period, which induces stomatal closure, leading to a decline in the photosynthetic rate. Comparison between the WUE estimates obtained by MODIS data and observations from the LBA towers showed an average error of 17%, varying between similar to 12% and similar to 28% for the different sites. MODIS WUE depends on the accuracy of both GPP and ET estimation. In this sense, we highlight that improvements in both MODIS GPP and ET products are necessary and should focus on reducing the uncertainties related to the biophysical vegetation parameters and meteorological data that serve as input information in the algorithms.
机译:这项研究旨在评估在上塔帕霍斯和库鲁阿乌纳通过MODIS总初级生产力(GPP)和蒸散(ET)产品(GPP17为GPP和ET16为ET)获得的水利用效率(WUE)的时空格局。流域位于亚马逊地区的东方侧翼,并通过亚马逊地区大型生物圈-大气实验(LBA)项目中的流量塔测量结果验证了结果。 WUE的空间变化主要与塔帕霍斯河上游流域(西部)与所谓的森林砍伐弧线内的库鲁瓦-乌纳河流域(东部)相比,森林面积更大有关。暂时,WUE表现出明显的季节性模式,随该地区的干旱和潮湿季节而变化。在干旱季节,WUE下降了约3%,这与干旱时期的水分利用率低和蒸气压不足增加有关,这导致气孔关闭,导致光合速率下降。通过MODIS数据获得的WUE估计值与来自LBA塔的观测值之间的比较显示,平均误差为17%,不同站点的平均误差在12%到28%之间。 MODIS WUE取决于GPP和ET估计的准确性。从这个意义上讲,我们强调必须对MODIS GPP和ET产品进行改进,并且应集中精力减少与生物物理植被参数和气象数据有关的不确定性,这些参数和气象数据可用作算法中的输入信息。

著录项

  • 来源
    《International journal of remote sensing》 |2017年第20期|5291-5309|共19页
  • 作者单位

    Univ Kansas, Dept Geog & Atmospher Sci, 1475 Jayhawk Blvd, Lawrence, KS 66045 USA|Natl Inst Space Res, Remote Sensing Div, Sao Jose Dos Campos, SP, Brazil;

    Univ Kansas, Dept Geog & Atmospher Sci, 1475 Jayhawk Blvd, Lawrence, KS 66045 USA;

    Natl Inst Space Res, Remote Sensing Div, Sao Jose Dos Campos, SP, Brazil;

    Natl Inst Space Res, Remote Sensing Div, Sao Jose Dos Campos, SP, Brazil;

    Natl Inst Space Res, Remote Sensing Div, Sao Jose Dos Campos, SP, Brazil;

    Univ Minnesota, Dept Soil Water & Climate, St Paul, MN 55108 USA;

    Natl Inst Space Res, Remote Sensing Div, Sao Jose Dos Campos, SP, Brazil|Univ Exeter, Coll Life & Environm Sci, Exeter, Devon, England;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
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