基于土壤和冠层阻力优化组合的蒸散发模拟

IF 5 1区 地球科学 Q2 ENVIRONMENTAL SCIENCES
Jinfeng Zhao, Shikun Sun, Yali Yin, Yihe Tang, Chong Li, Yongshan Liang, Yubao Wang, Alexander Winkler, Shijie Jiang
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引用次数: 0

摘要

双源遥感蒸散发(ET)模型需要基于土壤和冠层阻力准确分离土壤蒸发量(Es)、植物蒸发量(Ec)和降水截留量(Ei)。尽管有几种ET产品和算法可用,但对抗性配置的全面评估仍然很少。本研究在Shuttleworth-Wallace (S-W)框架下,系统评价了5种土壤阻力方法、8种冠层阻力方法和2种降水拦截算法的不同组合。利用119个FLUXNET站点的涡动相关数据和最新的ET产品,我们发现Ball-Berry-Leuning方法、统一气孔法和RL经验方法在不同植物功能类型(PFTs)和气候区域的表现相当且排名靠前,只有一个由遗传算法校准的自由参数。幂函数法(S2)对土壤表面含水量敏感,对Es建模最有效,特别是在水资源有限的地区。表现最好但尚未探索的组合(S2-C1、S2-C2、S2-C5)的表现与PML-V2、GLEAM4和潜在的水利用效率模型一致,解释了56%的日蒸散发变化,实现了低至1.02 mm day - 1的均方根误差。然而,这些模型在干旱地区显示出较低的准确性,在干旱地区,长期的水分胁迫导致R2降低38%。这突出表明需要更准确地表示干旱地区的土壤水分应力,这在现有模型中经常被忽视。我们的研究为跨PFTs和气候带的ET估算提供了稳健、简洁和广泛适用的模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advancing Evapotranspiration Modeling With Optimized Soil and Canopy Resistance Combinations
Dual-source remotely sensed evapotranspiration (ET) models require accurate separation of soil evaporation (Es), plant transpiration (Ec), and precipitation interception (Ei) based on soil and canopy resistances. Despite the availability of several ET products and algorithms, comprehensive evaluations of resistance configurations remain scarce. This study systematically evaluates various combinations of five soil resistance methods, eight canopy resistance methods, and two precipitation interception algorithms within the Shuttleworth-Wallace (S-W) framework. Using eddy covariance data from 119 FLUXNET sites and the latest ET products, we find that the Ball-Berry-Leuning method, unified stomatal method, and RL empirical method provide comparable and top-ranked performance across plant functional types (PFTs) and climate zones, with only a single free parameter calibrated by genetic algorithm. The power function method (S2), sensitive to soil surface water content proves to be the most effective for modeling Es, particularly in water-limited regions. The performance of best-performing but unexplored combinations (S2-C1, S2-C2, S2-C5) is consistent with PML-V2, GLEAM4, and underlying water use efficiency model, explaining 56% of the variation in daily ET and achieving an root mean square error as low as 1.02 mm day−1. However, these models show reduced accuracy in arid zones, where prolonged water stress led to a 38% reduction in R2. This highlights the need for a more accurate representation of soil moisture stress in arid regions, which is often overlooked in existing models. Our study offers robust, parsimonious, and broadly applicable models for ET estimation across PFTs and climate zones.
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来源期刊
Water Resources Research
Water Resources Research 环境科学-湖沼学
CiteScore
8.80
自引率
13.00%
发文量
599
审稿时长
3.5 months
期刊介绍: Water Resources Research (WRR) is an interdisciplinary journal that focuses on hydrology and water resources. It publishes original research in the natural and social sciences of water. It emphasizes the role of water in the Earth system, including physical, chemical, biological, and ecological processes in water resources research and management, including social, policy, and public health implications. It encompasses observational, experimental, theoretical, analytical, numerical, and data-driven approaches that advance the science of water and its management. Submissions are evaluated for their novelty, accuracy, significance, and broader implications of the findings.
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