Evaluating the influential variables on rainfall interception at different rainfall amount levels in temperate forests
Evaluating the influential variables on rainfall interception at different rainfall amount levels in temperate forests
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评估温带森林不同降雨量水平下截雨的影响变量
DOI：
10.1016/j.jhydrol.2022.128572
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发表时间：
2022
影响因子：
6.4
通讯作者：
Xiaohua Wei
中科院分区：
文献类型：
--
作者：
Yu Yue;Jiaojun Zhu;Tian Gao;Lifang Liu;Fengyuan Yu;Jinxin Zhang;Xiaohua Wei
林冠截留降雨是生态水文循环的重要组成部分，受降雨特征、气候条件、森林结构及其相互作用的影响。不同数量的降雨事件可能会改变降雨与林冠相互作用的方式，从而使影响因子对RI的影响发生显著变化。因此，根据降雨量分别分析影响RI值的变量需要进一步关注。本研究对2017年至2019年6月至9月四种森林类型的60块样地的降雨分配进行了测量。气象条件是从空间上代表所有研究小区的四个气象站获得的。从地面激光扫描中提取了详细的冠层结构变量。然后，用Boosted回归树(BRT)分析了不同降雨量下RI的贡献变量。结果共测得77次降雨事件，其中43次、19次和15次分为小雨事件(LR)、中雨事件(MR)和暴雨事件(HR)，分别为小雨事件(LR)、中雨事件(MR)和大雨事件(HR)，分别为总雨量(LR)、总雨量(≤)和总雨量(≥)。林地、林地和林地的RI值(总降雨量与穿透雨量和树干径流之和的差值)分别为2.0 mm、3.5 mm和6.6 mm。LR、MR和HR的平均RI比例(RI占总降雨量的比例)分别为74.8%、20.2%和17.1%。不同降雨量水平(LR、MR和HR)的RI数量和RI比例均存在显著差异。BRT结果表明，对于所有降雨量水平，RI量由降雨量决定，其次是冠层截留指数(CII)和湿度。受CII的影响最大，其次是降雨量、湿度和平均冠层高度。正如预期的那样，对于给定的降雨量水平，降雨量是对RI量影响最大的变量。自然，对RI比例影响最大的变量随着降雨量的不同而不同。对于LR和MR，影响最大的变量是CII；而对于HR，影响最大的变量是湿度。此外，各种显著变量(相对影响值高于平均值)，如降雨强度、风速和ACH，错综复杂地影响着每个降雨量水平上的RI数量和比例。此外，降雨量与RI量呈逐步正相关。CII对RI比例呈逐步正向影响，湿度对RI比例呈负向影响。全面了解不同降雨量水平对RI的影响变量有助于深入了解森林冠层截留降雨的方式，并为理解温带森林冠层水文过程提供有力支持。
Rainfall interception (RI) by forest canopy is an important part of the ecohydrology cycle, influenced by rainfall characteristics, weather conditions, forest structures and their interactions. Rainfall events with different amounts are likely to change the ways that rainfall interacts with forest canopies, and consequently vary the effects of influential variables on RI markedly. Thus, analyzing the influential variables on RI separately according to rainfall amounts need further attention. In this study, rainfall partitioning was measured in 60 plots of four forest types during June to September from 2017 to 2019. Weather conditions were obtained from four weather stations spatially representing all the study plots. Detailed canopy structural variables were retrieved from the terrestrial laser scanning. Then, boosted regression trees (BRT) analyses were performed to evaluate the contributing variables of RI at different rainfall amounts. As a result, a total of 77 rainfall events were measured, and 43, 19 and 15 events were classified as light rainfall events (LR, gross rainfall < 10 mm), middle rainfall events (MR, 10 mm ≤ gross rainfall < 25 mm) and heavy rainfall events (HR, gross rainfall ≥ 25 mm). The average values of RI amounts (the difference between gross rainfall and the sum of throughfall and stemflow) for LR, MR and LR were 2.0 mm, 3.5 mm and 6.6 mm, respectively. The average RI proportions (the proportion of RI amount to gross rainfall) for LR, MR and HR were 74.8 %, 20.2 % and 17.1 %, respectively. Both RI amount and RI proportion were significantly different among the rainfall amount levels (LR, MR and HR). BRT results showed that, for all rainfall amount levels together, RI amount was governed by rainfall amount, followed by canopy interception index (CII) and humidity. Whereas RI proportion was most influenced by CII, followed by rainfall amount, humidity and average canopy height (ACH). As expected, for a given rainfall amount level, rainfall amount was the most influential variable on RI amount. Naturally, the most influential variable on RI proportion varied with rainfall amount levels. For LR and MR, the most influential variables were CII; while it was humidity for HR. Furthermore, a variety of significant variables (with the relative influence value higher than the averaged value), such as rainfall intensity, wind speed and ACH, intricately and complexly affected RI amount and proportion at each rainfall amount level. In addition, the Rainfall amount exerted a stepwise positive correlation with RI amount. CII showed a stepwise positive and humidity a negative influence on RI proportion, respectively. A comprehensive understanding of the influence variable on RI at distinct rainfall amount levels provides valuable insights into how forest canopies intercept rainfall and greatly supports understanding of canopy hydrological processes in temperate forests.