陆地激光扫描导出的冠层存储量提高了修正Gash模型在温带森林中的性能

IF 5.6 1区 农林科学 Q1 AGRONOMY Agricultural and Forest Meteorology Pub Date : 2025-01-20 DOI:10.1016/j.agrformet.2025.110398
Yue Yu , Jiaojun Zhu , Tian Gao , Zhihua Liu , Lifang Liu , Fengyuan Yu , Jinxin Zhang
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引用次数: 0

摘要

森林冠层截流损失是森林生态系统中一个重要的水文过程,其准确建模对理解森林生态系统的水分平衡至关重要。修正后的Gash模型常用于I建模;但其性能受冠层存储量(S)精度的影响,而S是最敏感的参数之一。因此,在修正后的Gash模型中,优化S的估计,然后级联应用值得进一步关注。在本研究中,我们测量了2018年和2019年中国东北落叶松人工林(LPF)和蒙古栎林(MOF)的总降雨量、穿透量和茎流。引入地面激光扫描(TLS)来推导S (Sex)。然后将性别与两种常用的基于回归的方法(Smean和Smini)计算的值进行比较。最后,对修正后的Gash模型使用三种S进行运行,并对模型性能进行评价。结果表明,LPF的I(27.9%)高于MOF(20.1%)。对于LPF和MOF,由性别计算的S最大(1.45和0.51 mm),其次是Smean(0.98和0.32 mm)和Smini(0.29和0.13 mm)。与Smean和Smini运行的模型相比,无论是使用Penman-Monteith方程还是线性回归方法计算蒸发速率(修正后Gash模型的另一个敏感参数),Sex都提高了模型的性能。此外,使用Sex的模型特别提高了模型在中、强降雨水平的准确性。综上所述,基于tls的S提高了模型在东北温带森林中的性能。同时,与以往研究强调蒸发速率/降雨强度(E/R)在模拟大降雨事件中的贡献不同,本研究表明S的作用不容忽视。
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Terrestrial laser scanning-derived canopy storage capacity improves the performance of the revised Gash model in temperate forests
Rainfall interception loss (I) by forest canopy is a crucial hydrological process in forest ecosystems, and thus its accurate modeling is essential for understanding water balance. The revised Gash model is commonly employed in I modeling; however, its performance is affected by the accuracy of canopy storage capacity (S), which is identified as one of the most sensitive parameters. Consequently, optimizing the estimation of S and then cascading application in the revised Gash model warrants further attention. In this study, we measured gross rainfall, throughfall, and stemflow for the larch (Larix kaempferi) plantation forest (LPF) and the Mongolian oak (Quercus mongolica) forest (MOF) in Northeast China in 2018 and 2019. Terrestrial laser scanning (TLS) was introduced to derive S (Sex). Sex was then compared with values calculated from two commonly regression-based methods (Smean and Smini). Finally, the revised Gash model was run using the three types of S, and the model performances were evaluated. As a result, I of LPF (27.9 %) was higher than that of MOF (20.1 %). For LPF and MOF, S calculated from Sex was the largest (1.45 and 0.51 mm), followed in descending order by Smean (0.98 and 0.32 mm) and Smini (0.29 and 0.13 mm). Compared with models run with Smean and Smini, Sex improved the model performance, regardless of whether the Penman-Monteith equation or a linear regression method was used to calculate the evaporation rate (another sensitive parameter of the revised Gash model). Moreover, the model using Sex particularly enhanced the model's accuracy at middle and heavy rainfall levels. In conclusion, the TLS-derived S improves the model performance in temperate forests in Northeast China. Meanwhile, in contrast to previous studies, which emphasized the contribution of evaporation rate/rainfall intensity (E/R) in modelling larger rainfall events, this study suggests the role of S should not be overlooked.
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来源期刊
CiteScore
10.30
自引率
9.70%
发文量
415
审稿时长
69 days
期刊介绍: Agricultural and Forest Meteorology is an international journal for the publication of original articles and reviews on the inter-relationship between meteorology, agriculture, forestry, and natural ecosystems. Emphasis is on basic and applied scientific research relevant to practical problems in the field of plant and soil sciences, ecology and biogeochemistry as affected by weather as well as climate variability and change. Theoretical models should be tested against experimental data. Articles must appeal to an international audience. Special issues devoted to single topics are also published. Typical topics include canopy micrometeorology (e.g. canopy radiation transfer, turbulence near the ground, evapotranspiration, energy balance, fluxes of trace gases), micrometeorological instrumentation (e.g., sensors for trace gases, flux measurement instruments, radiation measurement techniques), aerobiology (e.g. the dispersion of pollen, spores, insects and pesticides), biometeorology (e.g. the effect of weather and climate on plant distribution, crop yield, water-use efficiency, and plant phenology), forest-fire/weather interactions, and feedbacks from vegetation to weather and the climate system.
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