Measurement and Partitioning of Evapotranspiration for Application to Vadose Zone Studies
Measurement and Partitioning of Evapotranspiration for Application to Vadose Zone Studies
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DOI：
10.2136/vzj2017.08.0155
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发表时间：
2017-12-01
影响因子：
2.8
通讯作者：
Skaggs, Todd H.
中科院分区：
文献类型：
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作者：
Anderson, Ray G.;Zhang, Xudong;Skaggs, Todd H.
将蒸散量（ET）划分为蒸发量（E）和蒸腾量（T）这两个组成部分，对于评估管理措施对水资源利用效率的影响以及改进分别对E和T进行参数化的包气带模型的有效性等诸多水文目的都很重要。然而，大多数历史悠久的观测技术的观测时间尺度和空间足迹都很短，这就对这些测量的代表性提出了疑问。在过去的15年中，新的方法已经允许ET分区的空间尺度范围从土壤到地球仪和长时间尺度。在这次更新中，我们回顾了一些最近的方法发展分区ET。其中包括涉及高频涡动协方差观测的通量方差分割的微气象方法，以及光合作用和蒸腾作用的代理，如同位素分馏和羰基硫吸收的测量。我们讨论了利用遥感划分冠层和土壤之间的能量平衡的进展。我们的结论是，通量方差分区与原始涡度协方差数据和两个源的能量平衡方法与遥感平台可能有最大的潜力分区ET，部分原因是大型公共存储库的涡度协方差和卫星数据可以很容易地重新处理分区ET。
Partitioning evapotranspiration (ET) into its constituent components, evaporation (E) and transpiration (T), is important for numerous hydrological purposes including assessing impacts of management practices on water use efficiency and improved validation of vadose zone models that parameterize E and T separately. However, most long-established observational techniques have short observational timescales and spatial footprints, raising questions about the representativeness of these measurements. In the past 15 yr, new approaches have allowed ET partitioning at spatial scales ranging from the pedon to the globe and at long timescales. In this update, we review some recent methodological developments for partitioning ET. These include micrometeorological approaches involving the flux variance partitioning of high-frequency eddy covariance observations and proxies for photosynthesis and transpiration such as measurements of isotopic fractionation and carbonyl sulfide uptake. We discuss advances in partitioning the energy balance between canopy and soil using remote sensing. We conclude that the flux variance partitioning with raw eddy covariance data and the two-source energy balance approaches with remote sensing platforms may have the greatest potential for partitioning ET, in part because large public repositories of eddy covariance and satellite data could be readily reprocessed to partition ET.