Stemflow estimation models for Japanese cedar and cypress plantations using common forest inventory data
Stemflow estimation models for Japanese cedar and cypress plantations using common forest inventory data
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DOI：
10.1016/j.agrformet.2020.107997
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发表时间：
2020-08
影响因子：
6.2
通讯作者：
Seonghun Jeong;K. Otsuki;Yoshinori Shinohara;Akio Inoue;Ryuji Ichihashi
中科院分区：
文献类型：
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作者：
Seonghun Jeong;K. Otsuki;Yoshinori Shinohara;Akio Inoue;Ryuji Ichihashi
虽然树干茎流（SF）一直被认为是总降雨量（GR）的一小部分，最近的研究表明，根据林分结构，SF/GR的比例不应被忽视。本研究利用森林资源清查资料，推导出森林覆盖率/森林覆盖率的估算模型。收集了日本杉和柏树人工林的一组SF/GR比值和森林资源调查数据（林分密度（SD）、总断面积（BA）、平均胸径（D B H <$）、平均树高（H <$）、冠层覆盖度（CC）和叶面积指数（LAI））。为了进一步研究SF/GR比值与林分结构之间的关系，我们检查了来自清查数据的其他林分结构变量（平均断面积（B <$），平均茎表面积（SA <$）和总茎表面积（SA）），以及评估漏斗雨水效率的林分尺度漏斗比（FR林分）。在所有林分结构变量中，SD专门确定SF/GR比，提供最佳拟合的正一元线性回归方程作为基于密度的SF/GR模型，均方根误差（RMSE）为2.4%。虽然该模型只需要最基本的森林资源清查数据SD，对实际森林水分管理是有用的，但它在精细森林水分管理中有一个弱点，因为它不能反映树木生长对SF/GR比值的影响。因此，我们开发了一个基于大小的SF/GR模型（RMSE= 2.0%）的基础上，FR林分和D B H之间的强关系。该模型不仅反映了SD，而且反映了胸径生长对SF/GR的影响，适用于森林精细水分管理。这些模型是由森林资源清查数据得到的，可用于森林水分管理中的土壤水分评价和控制。
Although stemflow (SF) had been regarded as a small portion of the gross rainfall (GR), recent studies have revealed that, depending on the forest stand structure, the SF/GR ratio should not be neglected. This study derived SF/GR estimation models using common forest inventory data. A set of SF/GR ratio and forest inventory data (stand density (SD), total basal area (BA), mean diameter at breast height (D B H¯), mean tree height (H¯), canopy cover (CC), and leaf area index (LAI)) was collected from previous studies of Japanese cedar and cypress plantations. To further investigate the relation between SF/GR ratio and forest stand structures, we examined additional stand-structure variables (mean basal area (B A¯), mean stem surface area (S A¯), and total stem surface area (SA)) derived from the inventory data, and the stand-scale funneling ratio (FR stand) evaluating the efficiency of funneling rainwater. Among all the stand-structure variables, SD exclusively determined the SF/GR ratio, providing the best-fitting positive single linear regression equation as a density-based SF/GR model with a root mean square error (RMSE) of 2.4%. Although this model is useful for practical forest water management because it requires only SD which is the most basic forest inventory data, it has a weak point in meticulous forest water management because it cannot reflect the effect of tree growth on SF/GR ratio. Thus, we developed a size-based SF/GR model (RMSE= 2.0%) based on the strong relationship between the FR stand and D B H¯. This model is applicable to meticulous forest water management because it reflects the effects of not only SD but also tree growth by DBH on SF/GR ratio. These models derived from the common forest inventory data are potentially applicable to the evaluation and control of SF in forest water management.