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Partitioning evapotranspiration based on the total ecosystem conductance fractions of soil, interception, and canopy in different biomes
Journal of Hydrology ( IF 6.4 ) Pub Date : 2021-09-22 , DOI: 10.1016/j.jhydrol.2021.126970
My Ngoc Nguyen 1 , Yuefeng Hao 2 , Jongjin Baik 3 , Minha Choi 1, 2
Affiliation  

Partitioning evapotranspiration (ET) into soil evaporation (Esoil), canopy interception evaporation (Eic), and transpiration (T) yields both comprehensive insight into hydrological processes and better water management, but it is challenging. This study proposes a modified ecosystem conductance-based Priestley-Taylor (MEC-PT) algorithm for ET partitioning based on the total ecosystem conductance (GTotal) fractions of soil, interception, and canopy. Datasets from 24 flux towers around the world were used to estimate GTotal by coupling aerodynamic conductance and surface conductance (Gs). Results from the MEC-PT model were compared with those from an original best-fit ecosystem-level conductance (m-order) model that only partitions Gs into soil and canopy domains. The superior performance of the MEC-PT model, with the inclusion of an intercepted contributor and ability to fill the data gap associated with the m-order during wet conditions, describes the robustness of this approach for partitioning ET. The MEC-PT model results might reflect dew formation that produces minimal Eic volume under non-rainfall conditions with support from the diurnal temperature (DT) presence. The ratio of T to total ET (T/ET) was found highest in forest with 0.72 (±0.17 of standard deviation), followed by savanna (0.57 ± 0.11), cropland (0.48 ± 0.10), and grassland (0.39 ± 0.17). Also, sensitivity analysis was conducted with main input variables of the MEC-PT and m-order models over four land cover types and the whole study period of each site used in this study. The results demonstrated that, in general conditions, net radiation was the key driver controlling T/ET variations, whereas air temperature and wind speed indirectly and slightly affected T/ET. This study underlines that the inclusion of Eic might bridge the gap in knowledge about ET and its components regarding canopy dynamics and ecosystem behaviors in the context of climate change.



中文翻译:

基于不同生物群落中土壤、截留和冠层的总生态系统电导分数划分蒸散

将蒸散量 ( ET ) 划分为土壤蒸发量 (土壤)、冠层截留蒸发(我知道了) 和蒸腾作用 ( T ) 既可以全面了解水文过程,又可以更好地管理水资源,但它具有挑战性。本研究提出了一种基于生态系统电导的改良 Priestley-Taylor (MEC-PT) 算法,用于基于生态系统总电导的ET划分(G全部的) 土壤、截留和冠层的分数。来自世界各地 24 个通量塔的数据集用于估计G全部的 通过耦合空气动力电导和表面电导(G)。将 MEC-PT 模型的结果与原始最适合生态系统级电导(m 阶)模型的结果进行比较,该模型仅分区G进入土壤和树冠域。MEC-PT 模型的卓越性能,包括截获的贡献者和在潮湿条件下填充与 m 阶相关的数据间隙的能力,描述了这种划分ET方法的稳健性。MEC-PT 模型结果可能反映产生最小的露水形成我知道了在昼夜温度 ( DT ) 存在的支持下,非降雨条件下的体积。发现T与总ET的比率(T / ET)在森林中最高,为 0.72(标准差的±0.17),其次是稀树草原(0.57±0.11)、农田(0.48±0.10)和草地(0.39±0.17) . 此外,对 MEC-PT 和 m 阶模型的主要输入变量进行了敏感性分析,涉及四种土地覆盖类型以及本研究中使用的每个站点的整个研究期。结果表明,在一般条件下,净辐射是控制T/ET变化的关键驱动因素,而气温和风速间接和轻微影响T/ET. 本研究强调,纳入我知道了可能会弥合关于ET及其组成部分在气候变化背景下的冠层动态和生态系统行为方面的知识差距。

更新日期:2021-09-27
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