Abstract
The factors that control throughfall in Pinus tabulaeformis plantations were investigated using linear and curve analyses based on direct measurements of rainfall, throughfall and stemflow from 36 rainfall events. The results showed the following: (1) there was significant spatial heterogeneity in throughfall rates in P. tabulaeformis plots; (2) the throughfall rate increased with increasing rainfall; and (3) the rate of increase gradually decreased. When rainfall reached approximately 25 mm, the throughfall rate stabilized. The coefficient of variation of the throughfall rate decreased with increasing rainfall, with a peak at approximately 10 mm of rainfall. The coefficient of variation of throughfall stabilized at 20%, and the coefficient of variation of the throughfall rate stabilized at 17%. A linear regression equation (R2 = 0.76) was derived by fitting the P. tabulaeformis average diameter at breast height (DBH), average tree height, average branch height, stand density, canopy thickness, canopy density, and the rainfall and throughfall rate. A highly positive correlation was found between the throughfall rate, canopy density, rainfall class and tree height (P < 0.01). By establishing a quadratic response surface model of the stand structure indicators and the throughfall rate, R2 was increased to 0.85 (P < 0.01). The quadratic regression analysis demonstrated a highly positive correlation between throughfall rate, canopy density and rainfall class.
Highlights
While many studies have been conducted on canopy interception because of its influential factors, there is no method to rapidly estimate forest TF
The coefficient of variation of throughfall steadied at approximately 20% (Fig. 3b), and the coefficient of variation of the throughfall rate steadied at approximately 17% (Fig. 3d)
The results indicate that the rainfall level (X7) and canopy density (X6) contributed significantly to the multiple correlation coefficient; they were the main factors that affected the throughfall rate
Summary
While many studies have been conducted on canopy interception because of its influential factors, there is no method to rapidly estimate forest TF. In this paper we established relationships between TF and the related factors using two mathematical models and tried to find out the most significant contributor to TF of P. tabulaeformis plantations. The results can provide further information about the forest water cycle in the study areas. (1) Monitor rainfall, TF, stemflow and interception loss in study area. We expect in-depth understanding of TF of P. tabulaeformis plantations and the relationship between the four in a variety of circumstances. (3) Compare all relevant factors, filter and establish model with mathematical method. We expect the most accurate model to determine the factors that have the most important impact on TF, by a variety of mathematical methods to calculate and verify
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