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Article

A Wind Tunnel Test for the Effect of Seed Tree Arrangement on Wake Wind Speed

by
Tae Kyung Yoon
1,
Seonghun Lee
1,
Seungmin Lee
1,
Sle-gee Lee
1,
Mariam Hussain
1,
Seungho Lee
2,
Haegeun Chung
3 and
Sanghoon Chung
4,*
1
Department of Forest Science, Sangji University, Wonju 26339, Republic of Korea
2
KOCED Wind Tunnel Center, Department of Civil Engineering, Jeonbuk (Chonbuk) National University, Jeonju 54896, Republic of Korea
3
Department of Environmental Engineering, Konkuk University, Seoul 05029, Republic of Korea
4
Forest Technology and Management Research Center, National Institute of Forest Science, Pocheon 11187, Republic of Korea
*
Author to whom correspondence should be addressed.
Forests 2024, 15(10), 1772; https://doi.org/10.3390/f15101772
Submission received: 19 August 2024 / Revised: 3 October 2024 / Accepted: 7 October 2024 / Published: 9 October 2024
(This article belongs to the Special Issue Forest Microclimate: Predictions, Drivers and Impacts)
Browse Figures
Versions Notes

Abstract

:
Changes in canopy structures caused by harvesting and regeneration practices can significantly alter the wind environment. Therefore, it is essential to understand the wind patterns influenced by seed tree arrangements for predicting seed dispersal by winds and ensuring the success of natural regeneration. This study aimed to identify how wind speed responds to seed tree arrangement designs with differing horizontal distances, vertical positions, and free-stream wind speeds. A wind tunnel test was conducted using pine saplings for a scale model of various seed tree arrangements, and the change in wake speed was tracked. The wake’s relative wind speed averaged 71%, ranging from 3.5% to 108.5%, depending on the seed tree arrangement, distance from saplings, and vertical position. It peaked within the patch of three seed trees compared to other arrangements and at the top canopy layer. The empirical function effectively described the wind speed reduction and recovery with distance from saplings. For instance, the minimum wind speed was reached at 0.6–2.2 times the canopy height, and a wind speed reduction of over 20% of the free-stream wind speed was maintained at a 1.6–7.6 canopy height. A negative relationship between the seed tree leaf area and the relative wind speed was observed only at the top canopy layer. This study presents empirical evidence on the patterns of wake winds induced by different types of heterogeneous canopy structures.

1. Introduction

Trees and wind interact through complex processes and patterns. Wind can have negative impacts on trees, causing damage such as windthrow and stem breakage, which can be fatal. However, wind also has a positive impact by promoting tree growth and aiding in seed dispersal [1,2]. For example, seeds or fruits of pioneer species with wings are dispersed long distances by wind and settle in areas that have been deforested or disturbed by forest fires [3,4]. The structure and arrangement of trees planted in forests, cities, and farmlands have a significant impact on the wind environment, such as changing wind speed/flow and creating turbulences/eddies [5,6]. Human society utilizes tree–wind interactions in various ways. For example, windbreaks are installed in agricultural areas to protect crops, by utilizing trees to block winds [7,8], and used to control aeolian erosion [9,10]. In urban areas, wind corridors are designed to introduce winds from the exterior to the core of the city and to ventilate hot polluted urban air by replacing it with clean, cool natural air [11,12]. Therefore, understanding the changes in the wind environment caused by trees is essential for forest management, safeguarding the ecological and economic values of forests, and positively leveraging their interactions.
Natural regeneration is the process of re-establishing a postharvest stand by applying the natural dispersal process of seeds instead of artificially planting seedlings grown in a nursery [3,13]. While the principles of natural regeneration are rational, their practical application in the field faces various risks and challenges concerning seed dispersal, germination, and/or seedling establishment [14,15]. To ensure successful seedling establishment, the practice of natural regeneration carefully considers remnant seed tree arrangement, aiming to ensure that seeds are adequately and evenly distributed across the harvested area [3].
The range of seed dispersal by wind can be predicted from the height of the seed tree, the wind speed, and the terminal velocity of the seeds, using a ballistic model [16,17,18]. While the height of seed trees and the terminal velocity of seeds are constant and easily determined [19,20], wind speed in forest environments is highly complex and difficult to predict [21]. This complexity arises from factors such as the canopy structure, mountainous topography, and temporal variations of energy flux among the atmosphere, canopy, and ground. [3,5]. In particular, harvested areas with remnant seed trees for natural regeneration have a heterogeneous canopy structure, resulting in spatiotemporal complexity of the wind environment. This complexity makes it difficult to predict the extent of seed dispersal during natural regeneration. Therefore, before predicting seed dispersal in natural regeneration practices, it is necessary to determine the wind environment of the harvested area, which simultaneously interacts with the arrangement of seed trees.
Wind monitoring of forests is conducted using automatic weather stations, flux towers, or unmanned aerial vehicles, but it is challenging to observe the spatiotemporal pattern of the wind environment of forests via these methods due to the complex interactions within forest environments. Computational simulation approaches, such as large-eddy simulations, can represent the spatiotemporal complexity of forest wind environments [22,23]; however, they require huge computational resources, restricting their applicability. Wind tunnel experiments that imitate forest environments using a scaled-down model are an affordable approach for predicting the forest wind environment within the desired controlled experimental conditions.
Wind tunnel experiments have been conducted to investigate how trees or plants affect the wind environment. Specifically, various studies have measured the drag of a single-tree model in a wind tunnel and reported the relationship between the leaf area (or crown density and porosity) and drag coefficients [24,25,26,27]. Other studies have examined the drag on windbreak models in which multiple tree miniatures were placed along a few rows [28,29]. The drag coefficient, which is determined by a wind tunnel experiment, can be applied to numerical simulations to predict the wind speed under conditions close to the actual windbreak [30,31]. While wind tunnel tests assuming a single tree or windbreak with a homogeneous canopy structure are abundant, there have been few attempts to simulate a forest wind environment under silvicultural practices, such as thinning, harvest, and regeneration. For instance, only a limited number of studies, such as that by Gardiner et al. [32,33], have investigated the changes in aerodynamics resulting from thinning or silvicultural systems (including even-aged, single-tree selection, group selection, and strip cutting) using wind tunnel tests. The aerodynamics around isolated trees or windbreaks are not necessarily identical to those around a patch (i.e., group) of trees with irregular canopy structures. The current knowledge regarding the wind environment influencing seed dispersal under natural regeneration is fragile.
This study conducted a wind tunnel experiment to track the changes in wind speed passing a scaled-down model of a single tree, a patch, and a strip of seed trees, representing different types of seed tree arrangements for natural regeneration, and to identify the influencing factors. Specifically, we aimed to (1) quantify the wind speed reduction by each seed tree arrangement, considering the effects of horizontal leeward distance, vertical position, and free-stream wind speed; (2) assess whether the leaf area of trees determined the reduction in wake speed; (3) determine whether changes in wind speed could be modeled empirically; and (4) determine the pattern of wakes passing through seed trees using a wind tunnel test to understand natural regeneration practices.

2. Materials and Methods

2.1. Experimental Saplings

Japanese red pine (Pinus densiflora Siebold and Zucc.) saplings were selected for the wind tunnel test to reproduce mature seed trees under natural regeneration conditions at a small scale. Most pine species release wind-dispersed seeds and are present worldwide. Moreover, Japanese red pine is the most dominant species in South Korea, as it covers 28.7% of forest area, and various silvicultural practices, such as seed collection, nursery, planting, thinning, and harvesting, are implemented for this species.
A key challenge in wind tunnel testing is selecting an experimental model for imitating a forest environment. Past studies have used plastic materials [9,24,29,33], branches of mature trees [26], and live seedlings/saplings [27,34,35]. While no tree model can satisfy all the aerodynamic characteristics of a real tree in terms of the plasticity, porosity, and Reynolds number, this study selected live saplings large enough to be placed in the wind tunnel. Considering the similarity of crown structure and plasticity between saplings and mature trees, this model increases the certainty and reliability of the results.
Twelve pine saplings (5-years-old) were collected from a nursery in Wonju, South Korea (N: 37°24′, E: 127°50′), on 30 October 2023. The height of the saplings was approximately 1 m, representing the 1:20 reduction scale to reference mature seed trees (~20 m height), which was field-investigated in a natural regeneration stand in Samcheok, Gangwon-do, South Korea (N: 37°14′, E: 129°09′). The reduction scales of clear length and stem diameter (diameter at the root collar for experimental saplings vs. breast height for reference seed trees) were close to 1:20, but that of the crown diameter, which was 1:8.6, was not consistent with the others (Table 1). Due to the differences in allometry between juvenile and adult organisms [36,37,38], the sizes of stems, crowns, and leaves cannot be identically reduced from reference mature seed trees to experimental saplings. Therefore, the experimental saplings had a relatively larger crown diameter than the reference trees. To resolve this mismatch in scale, the reduction scale of the spacing between saplings (1:8.3) was controlled to be close to that of the crown diameter (1:8.6). As a result, the canopy structure of the experimental saplings was analogous to that of the reference stand. Healthy saplings grown under full sunlight were selected and excavated using a root ball wrapped in a plastic bag to prevent wilting. Although we did not water them after excavation, the wind tunnel test was completed within four days after excavation, and there was no visible tree damage during the test period.
The leaf area of each sapling was determined immediately after the completion of the wind tunnel test. All leaves from each of the saplings were initially collected, and 30–40 leaves were randomly sampled and scanned using an electronic scanner at 300 dots per inch. The leaf area from the scanned images was calculated using ImageJ software [39]. All leaves and sampled leaves of the saplings were oven-dried at 85 °C until they reached a constant weight, and their dry weight was measured using an electronic balance. The total leaf area of each sapling was estimated from the measured leaf area and dry weight, using Equation (1) [40].
L A T = L A S × D W T D W S ,
where LAT and LAS are the leaf areas (mm2) of the total and sample leaves, respectively, and DWT and DWS are the dry weights (g) of the total and sample leaves, respectively.

2.2. Wind Tunnel Test

The wind tunnel tests were conducted at the Wind Tunnel Center of Korea Construction Engineering Development, Jeonbuk National University, South Korea. The large wind tunnel was operated using a closed-circuit system, and the test section was 12 m (width) × 2.5 m (height) × 40 m (length). The wind speed range was 0.3–12 m s−1 in the low-speed test section, the wind speed interval was less than 1% of the maximum wind speed, and the turbulence intensity was less than 1.5% [41].
To maintain a constant wind direction and speed in the scaled-down experimental model of the post-harvesting area, a 2 m (W) × 2 m (H) × 9 m (L) test structure was fabricated using wood plywood, square wood, and plastic films (Figure 1). Inside the wind tunnel test section, a rough surface can be created because of the material or paint on the bottom plate, resulting in a free boundary layer with an uneven flow [42]. The test structure was raised to a height of 53 cm above the floor to minimize the effects of the unstable wind flow at the bottom. The plywood subfloor had three horizontal and four axial holes for placing the saplings in various arrangements. A sapling pot containing a root ball was placed inside a hole, and all the empty holes were covered with a piece of plywood so that the plywood could mimic the natural ground. A space up to 1 m in front of and at least 4 m behind the sapling(s) was secured to measure the wind speed changes before and after passing the sapling(s). Plastic film walls with dimensions of 2 m (H) × 9 m (L) were installed on both sides of the test structure to block wind loss through the side and maintain a constant wind flow.
To test the effects of seed tree arrangement on wind speed change, five types of seed tree arrangement were designed: a single seed tree (hereafter “Single”), a patch of 3 seed trees (hereafter “Patch-3”), a patch of 5 seed trees (hereafter “Patch-5”), 2-strip seed trees (hereafter “Strip-2”), and 4-strip seed trees (hereafter, “Strip-4”) (Figure 1). Single was designed to represent a uniform seed tree method, in which individual, isolated seed trees remain at a sufficient distance. Patch-3 and -5 imitated the aggregated and group seed tree methods, respectively. Strip-2 and -4 modeled strip cutting and shelterbelt conditions, respectively.
The experimental wind speeds were defined at 1, 2, 3, and 5 m s−1, referring to light air, light breeze, and gentle breeze, respectively, of the Beaufort Scale and by considering the durability of the structure. The wind speed was measured using a Pitot tube equipped with a micromanometer (FCO 560, Furness Controls, East Sussex, UK). The Pitot tube was mounted on a three-axis (X, Y, and Z) traverse that was built into a large wind tunnel. In each set of seed tree arrangement types and experimental wind speeds, wind speeds were measured at three vertical and five horizontal points to test the response of the wind speed to height and distance from the seed tree(s). The vertical points of the measurements were vertically divided into the upper canopy layer at 110.1 cm above the floor of the structure, the canopy layer at 73.4 cm, and the stem layer at 36.7 cm. The horizontal points of the measurement were one point in front of and four points rear of the seed tree (s) at 1 m intervals (−1, 1, 2, 3, and 4 m from the seed tree(s)). Wind speed data were collected for one minute at a frequency of 5 Hz per point using a Pitot tube (N = 300) (Figure 1).

2.3. Data Analysis

All statistical analyses and data visualizations were performed using R 4.3.2 [43]. The relative wind speed was calculated as the ratio of the measured wind speed at each point (U) to the free-stream wind speed (Uf) set by the wind tunnel controller. The horizontal and vertical positions were expressed in terms of canopy height (H), indicated by the mean height of the experimental saplings. Therefore, 1 H was equivalent to 1.14 m. The differences in the wind residual rate by seed tree design, horizontal position, vertical position, and free-stream wind speed were determined using a four-way analysis of variance (ANOVA) with Tukey’s HSD post hoc analysis. In addition, a marginal change in the wind residual rate was determined using a multiple linear regression (MLR) analysis.
He et al. [44] developed an empirical function that models windbreak effects on wind speed reduction and recovery [Equation (2)]. This study adopted it to fit the change in the relative wind speed passing through the sapling(s), as follows:
U U f = 1 − a × e b × ( ln ⁡ X H + 10 − c ) 2 ,
where XH is the distance from the rearmost sapling(s) normalized by H, and a, b, and c are coefficients. These coefficients can be converted into parameters that directly indicate the key features of the empirical function, using Equations (3)–(5).
X m i n = e c − 10 ,
U m i n = 1 − a ,
L 20 = 2 × e c × s i n h ⁡ ( ln ⁡ ( a 0.2 ) b ) ,
where Xmin is the XH that the minimum relative wind speed reaches, Umin is the minimum relative wind speed after passing sapling(s), and L20 is the distance where the reduction in wind speed is maintained at more than 20% of the free-stream wind speed, named the shelter distance. Note that L20 cannot be available when the change in relative wind speed does not exceed 20% (a < 0.2).

3. Results

3.1. General Wake Patterns after Passing Seed Trees

Overall, the relative wind speed after passing the saplings averaged 71.0 ± 18.6%, ranging from 3.5% to 108.5% depending on the seed tree arrangement, horizontal and vertical positions, and free-stream wind speed (Figure 2). The relative wind speeds were significantly represented by the MLR (Table 2) and ANOVA models (Table S1). Assuming Single (69.4%) as a baseline, the relative wind speed increased in Patch-3 by 7.6 percentage points (% pt) and decreased in Strip-4 by 9.3%pt, significantly (p < 0.05); the relative wind speed of Patch-5 was not significantly different from that of Single (Figure 2a; Table 2).
After passing through the saplings, the wake speed decreased to 61.9% at 0.88 H from the rearmost saplings, gradually recovering as the distance from the saplings increased, reaching 77.2% at 3.51 H (Figure 2b). MLR suggested a 6.1%pt increase in the relative wind speed per 1 H increase in the distance from the rearmost sapling(s) (Table 2). Depending on the vertical layer, the mean relative wind speed decreased from the upper canopy layer (87.0%) to the stem layer (70.7%) to the canopy layer (51.8%) (Figure 2c). The relative wind speed increased with an increase in the free-stream wind speed from 1 to 5 m s−1 (Figure 2d); every 1 m s−1 increase in the free-stream wind speed resulted in a 2.0%pt increase in the relative wind speed (Table 2).

3.2. Changes in Wind Speed by Seed Tree Arrangement

Figure 3 and Figure S1 represent the horizontal and vertical changes in the wake speed caused by the seed tree arrangement and free-stream wind speed, respectively, focusing on the key features of local wind patterns in each seed tree arrangement. For Single, the reduction in wind speed was notable at the canopy layer; it dropped to 16.5% at the 0.88 H, and then recovered to 27.1% at 1.75 H, 50.6% at 2.63 H, and 61.7% at 3.51 H. On the other hand, the relative wind speed at the top canopy layer exceeded over 100% immediately after passing through the saplings, at 107.9% at 0.88 H, and 103.2% at 1.75 H (Figure 3). These contrasting wake patterns between the top canopy and the canopy layers resulted in significant local variability; the coefficient of variation of the relative wind speed was the highest for Single, at 40.1%.
For the seed-tree patches, the wake speed decreased in all layers. In particular, reductions in the wind speed occurred in the canopy layer (53.2%–67.2% in Patch-3, and 27.8%–69.1% in Patch-5) and stem layer (76.2%–86.0% in Patch-3, and 47.1%–67.1% in Patch-5). However, the wind speed in the upper canopy layer was relatively stable, maintaining 85%–100% in Patch-3 and Patch-5 (Figure 3).
For the strip-seed tree design, the wind speed was reduced in all layers. In Strip-2, for example, the relative wind speeds, overall at the horizontal positions, were 76.8%–84.4% at the upper canopy layer, 55.2–68.2 at the canopy layer, and 71.2%–88.8% at the stem layer. Moreover, in each vertical layer, the wind speed changed less along the distance from the saplings compared to the other seed tree designs. This pattern was strengthened in Strip-4 (Figure 3).

3.3. Curve Fitting of Wind Speed Reduction and Recovery Using an Empirical Model

Figure 4 illustrates the simplified patterns of wind speed changes by passing the sapling(s) using the empirical model developed for windbreak effects, and Figure 5 shows the distribution of the parameters for wind speed reduction and recovery curves by seed tree arrangement and vertical position. All the curves were statistically significant (p < 0.05), suggesting several patterns. First, the distance from the rearmost sapling(s) that reached the bottom peak (Xmin) ranged from 0.63 to 2.19 H, depending on the seed tree arrangement and the vertical distance. It was closest to the stem layer (1.02 H), followed by the top canopy (1.41 H) and canopy layer (1.44 H) (Figure 5). Second, wind speed reduction, indicated by the bottom peak, was greatest in the canopy layer, followed by the stem and top canopy layers. This is confirmed by the mean Umin of each vertical position: 85.0% for the upper canopy, 39.7% for the canopy, and 61.6% for the stem layer (Figure 5). Third, the shelter distance (L20) ranged from 1.57 to 7.60 H, being the longest at Strip-4 (6.12 H), followed by Patch-5 (5.42 H), the Single (3.73 H), Patch-3 (3.13 H), and Strip-2 (2.76 H).

3.4. Relationship between Leaf Area and Relative Wind Speed

A greater reduction in wind speed was observed in larger leaf areas in the top canopy layer (Figure 6a). Overall, a negative relationship between the leaf area and relative wind speed was observed from Single to Strip-4. However, the relative wind speed did not decrease from Patch-3 to Patch-5, but rather slightly increased, even though the leaf area of Patch-5 was approximately 1.7 times greater than that of Patch-3.
In contrast, in the canopy and stem layers, there was no clear pattern of change in the relative wind speed along the leaf area; rather, a complex interaction between the seed tree arrangement and the vertical position was observed (Figure 6b,c). For example, in the canopy layer, the single tree with the smallest leaf area was expected to achieve the highest relative wind speed; however, the relative wind speed in the Single arrangement was lower than that in the other seed tree arrangements, except Strip-4.

4. Discussion

4.1. Horizontal and Vertical Patterns of Wind Speed Passing Sapling(s)

The wind tunnel test quantified the effects of horizontal/vertical position and free-stream wind speed on changes in the wind speed (i.e., relative wind speed) using simple descriptive statistics and MLR. The relative wind speed increased by 2%pt per 1 m s−1 increase in free-stream wind speed. Increases in wind speed amplify the drag and tilting of the crown in the leeward direction, leading to a decrease in the frontal projection area of the crown. For example, Vollsinger et al. [26] reported that the frontal area of the crown was reduced by 20%–37% at 20 m s−1, depending on the species, in a wind tunnel test using crown samples of several broadleaved species. Therefore, more wind penetrated the porous space within, and around the canopy of the experimental sapling(s), as shown by the increase in the relative wind speed. Horizontally, as the distance from the rearmost sapling(s) increased by 1 H, the relative wind speed increased by 6.1% pt. Vertically, the relative wind speed decreased from the top canopy layer to the canopy layer and stem layer by 35.3% and 15.4%, respectively.
In addition, the empirical model developed for the windbreak forest can explain the patterns of wind speed reduction and recovery in more detail. It parameterizes the maximum wind speed reduction (Umin), the horizontal position at which it is reached (Xmin), and the distance over which the wind speed reduction persists (L20). All these effect sizes and parameters can be applied to predict the wind environment in natural regeneration practices.

4.2. Effects of Seed Tree Arrangement Design on Wind Speed Change and Seed Dispersal

Wind speed reduction was related to the leaf area of saplings only in the top canopy layer. In the other layers, the leaf area could not explain the changes in wind speed. Field investigations on windbreaks have reported that the intensity of wind reduction was significantly related to size indices of the windbreak, such as the basal area, crown index, and width × total area density [45,46]. However, our results are not consistent with these findings, suggesting that the pattern depends on the seed tree arrangement, not only the sum of the leaf area.
The wake flow passing Single was accelerated at the top canopy layer, whereas it was impeded at the canopy and stem layers. Horn et al. [47] reviewed the mechanism of shear-induced turbulent eddies at the top canopy layer, which release seeds from the canopy, lift them, and facilitate their long-distance dispersal. The results of this wind tunnel test suggested that an isolated seed tree design using a single seed tree had great advantages for upwind seed dispersal. This aligns with the results of a wind tunnel test conducted by Qin et al. [48], who demonstrated that the dispersal distance of seeds could be increased by the complex updraft around a canopy of a single tree. In addition, the shelter distance of the single sapling in this study (3.71 H) was lower than that of single arid shrubs (5 H) in a wind tunnel study by Bhutto [10]. This difference suggests that a single tree can allow more wind to pass through a stem layer, which is lacking in leaves and branches, than a shrub with little vertical stratification of its crown structure.
In comparing the seed tree patch designs, Patch-5 had a higher wind speed than Patch-3 in the top canopy layer. However, this was reversed in the canopy and stem layers; the wind speed in Patch-3 did not decrease as much as that in Patch-5. This was because as the patch size increased, more wind was intercepted by the canopy, and the stem layers flowed through the top canopy layer. The funneling effect between the canopy and stem layers may contribute to the wake flow through the seed trees being less blocked, which likely is due to the lack of seed trees behind the first three seed trees.
For the strip seed tree design, the wind speed of Strip-4 was reduced by a larger degree than that of Strip-2 at all vertical positions. Moreover, Strip-4 had the longest shelter distance (6.12 H) among all the other seed tree designs, indicating a poor recovery rate to the original wind speed. This pattern is analogous to a field study in a deciduous windbreak of South Korea that observed a 24.6% wind speed reduction at 6 H [49]. Another field study reported that the distance at which the reduction in wind speed was maintained at 30% or more (in this study, less than 20%) of the free-stream wind speed ranged from 2.6 to 14 H, depending on the structure and species of windbreak [45]. This implies that Strip-4 successfully reproduced the structure and wind reduction effect of an actual windbreak. As the number of tree rows increases, a higher density of leaves and branches blocks the wake flow and slows the wind speed [50].

5. Conclusions

The wake of sapling(s) representing various seed tree arrangements was tracked, and the effect sizes and parameters for changes in the wind speed were tracked via a wind tunnel test. The relative wind speed was 70.0 ± 20.1% on average and ranged from 0.0 to 110.2% depending on the seed tree arrangement and horizontal/vertical position. The relative wind speed was highest in Patch-3 among the seed tree arrangements and in the top canopy layer among the vertical layers. The relative wind speed was slightly increased by the higher free-stream wind speed owing to the streamlining effects on the crowns. The leaf area did not predominantly regulate wind speed reduction, and unexplained variations in wind speed reduction may have resulted from the seed tree arrangement.
Previous wind tunnel tests targeting single, isolated, or windbreak trees have succeeded in revealing their drag and regulating factors on changes in wind speed. However, this knowledge may be unsatisfactory for natural regeneration, in which diverse and heterogeneous seed tree arrangements can be designed. Changes in wind speed due to seed tree arrangements were determined using this wind tunnel test. In addition, empirical modeling described the patterns of wind speed reduction and recovery depending on the seed tree arrangement. These data will be valuable for enhancing the predictability and performance of seed dispersal in natural regeneration by applying an appropriate seed tree arrangement, considering the interaction between the canopy structure and wind environment.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f15101772/s1, Figure S1: Patterns of wind speed reduction and recovery according to seed tree arrangement; Table S1: Analysis of variance (ANOVA) test on the effects of seed tree design, horizontal and vertical positions, and free-stream wind speed on the relative wind speed of wake passing sapling(s) in a wind tunnel test.

Author Contributions

Conceptualization, T.K.Y., S.L. (Seonghun Lee) and S.C.; methodology, S.L. (Seonghun Lee), S.-g.L. and S.L. (Seungho Lee); formal analysis, S.L. (Seonghun Lee), S.L. (Seungmin Lee), S.-g.L. and M.H.; investigation, S.L. (Seonghun Lee), S.L. (Seungmin Lee), S.-g.L. and M.H.; resources, S.L. (Seungho Lee); writing—original draft preparation, T.K.Y. and S.L. (Seonghun Lee); writing—review and editing, T.K.Y. and H.C.; visualization, T.K.Y. and S.L. (Seungmin Lee); supervision, S.C.; project administration, T.K.Y.; funding acquisition, T.K.Y. and S.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by a research fund from the National Research Foundation of Korea (NRF) grant funded by the Ministry of Science and ICT of Korea (RS-2023-00213308) and the Forest Technology and Management Research Center, National Institute of Forest Science (SC0400-2021-01).

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Materials; further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. The schematic diagram of the wind tunnel experiment.
Figure 1. The schematic diagram of the wind tunnel experiment.
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Figure 2. Comparison of the changes in the relative wind speed by (a) seed tree arrangement, (b) vertical position, (c) horizontal position, and (d) free-stream wind speed. The relative wind speed is defined as the ratio of the measured wind speed (U) to the free-stream wind speed (Uf) set in the wind tunnel controller. Different letters indicate significant differences among the bars tested by a four-way analysis of variance with Tukey’s HSD test (p < 0.05). Error bars indicate one standard deviation. Patch-3 and -5 defined the patches of 3 and 5 seed trees. Strip-2 and -4 define the 2- and 4-strip seed trees. The vertical and horizontal positions are expressed in terms of the canopy height (H), which is equivalent to the average height of the experimental saplings (1.14 m).
Figure 2. Comparison of the changes in the relative wind speed by (a) seed tree arrangement, (b) vertical position, (c) horizontal position, and (d) free-stream wind speed. The relative wind speed is defined as the ratio of the measured wind speed (U) to the free-stream wind speed (Uf) set in the wind tunnel controller. Different letters indicate significant differences among the bars tested by a four-way analysis of variance with Tukey’s HSD test (p < 0.05). Error bars indicate one standard deviation. Patch-3 and -5 defined the patches of 3 and 5 seed trees. Strip-2 and -4 define the 2- and 4-strip seed trees. The vertical and horizontal positions are expressed in terms of the canopy height (H), which is equivalent to the average height of the experimental saplings (1.14 m).
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Figure 3. Changes in the wind speed by seed tree arrangement after passing through the sapling(s) at a series of free-stream wind speeds ((a): 1 m s−1, (b): 2 m s−1, (c): 3 m s−1, (d): 5 m s−1). A grid map with the spectral color indicates the wind speed, which is interpolated using the wind speed at each measurement point. The vertical and horizontal positions are expressed in terms of canopy height (H).
Figure 3. Changes in the wind speed by seed tree arrangement after passing through the sapling(s) at a series of free-stream wind speeds ((a): 1 m s−1, (b): 2 m s−1, (c): 3 m s−1, (d): 5 m s−1). A grid map with the spectral color indicates the wind speed, which is interpolated using the wind speed at each measurement point. The vertical and horizontal positions are expressed in terms of canopy height (H).
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Figure 4. Curve fitting for the changes in the relative wind speed along the distance from the rearmost sapling(s); at the top canopy, the canopy, and the stem layer in each seed tree arrangement. The curve fitting was made using an empirical model developed by He et al. [44]. The horizontal positions are expressed in terms of canopy height (H).
Figure 4. Curve fitting for the changes in the relative wind speed along the distance from the rearmost sapling(s); at the top canopy, the canopy, and the stem layer in each seed tree arrangement. The curve fitting was made using an empirical model developed by He et al. [44]. The horizontal positions are expressed in terms of canopy height (H).
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Figure 5. The parameters of the curve fittings for the changes in the relative wind speed by seed tree arrangement and vertical position. Xmin is the distance from the rearmost sapling(s) that the minimum relative wind speed reaches; Umin is the minimum relative wind speed after passing the sapling(s); and L20 is the distance at which the reduction in wind speed is maintained at more than 20% of the free-stream wind speed, named the shelter distance.
Figure 5. The parameters of the curve fittings for the changes in the relative wind speed by seed tree arrangement and vertical position. Xmin is the distance from the rearmost sapling(s) that the minimum relative wind speed reaches; Umin is the minimum relative wind speed after passing the sapling(s); and L20 is the distance at which the reduction in wind speed is maintained at more than 20% of the free-stream wind speed, named the shelter distance.
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Figure 6. Relationship between the leaf area and the relative wind speed at different vertical positions ((a): top canopy, (b): canopy, (c): stem).
Figure 6. Relationship between the leaf area and the relative wind speed at different vertical positions ((a): top canopy, (b): canopy, (c): stem).
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Table 1. Characteristics of the experimental saplings (Japanese red pine) used in a wind tunnel test, in comparison with those of seed trees in a reference stand. The reduction scale of the experimental saplings was estimated based on the pine growth data of the natural regeneration test stand.
Table 1. Characteristics of the experimental saplings (Japanese red pine) used in a wind tunnel test, in comparison with those of seed trees in a reference stand. The reduction scale of the experimental saplings was estimated based on the pine growth data of the natural regeneration test stand.
Experimental
Saplings (N = 12)		Seed Trees in a
Reference Stand		Reduction Scale
Height114.1 ± 16.0 cm22.0 m1:19.3
Clear length45.4 ± 10.2 cm10.4 m1:22.9
Crown diameter71.1 ± 18.3 cm6.1 m1:8.6
Diameter 2.5 ± 0.5 cm
(at root collar)		38.0 cm
(at breast height)		1:15.2
Spacing between trees0.8 m6.6 m1:8.25
Table 2. Multiple regression analysis of the effects of seed tree design, horizontal and vertical position, and free-stream wind speed on the relative wind speed (%) of wake passing sapling(s) in a wind tunnel test.
Table 2. Multiple regression analysis of the effects of seed tree design, horizontal and vertical position, and free-stream wind speed on the relative wind speed (%) of wake passing sapling(s) in a wind tunnel test.
VariableEstimateStandard
Error		tp
Intercept67.662.8124.10<0.001
Seed tree design: Patch-37.602.263.37<0.001
Seed tree design: Patch-5−1.512.26−0.670.51
Seed tree design: Strip-25.412.262.40<0.05
Seed tree design: Strip-4−9.262.26−4.10<0.001
Free-stream wind speed2.010.484.16<0.001
Height: canopy−35.281.75−20.17<0.001
Height: stem−16.351.75−9.35<0.001
Distance6.110.738.39<0.001
R20.709
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Yoon, T.K.; Lee, S.; Lee, S.; Lee, S.-g.; Hussain, M.; Lee, S.; Chung, H.; Chung, S. A Wind Tunnel Test for the Effect of Seed Tree Arrangement on Wake Wind Speed. Forests 2024, 15, 1772. https://doi.org/10.3390/f15101772

AMA Style

Yoon TK, Lee S, Lee S, Lee S-g, Hussain M, Lee S, Chung H, Chung S. A Wind Tunnel Test for the Effect of Seed Tree Arrangement on Wake Wind Speed. Forests. 2024; 15(10):1772. https://doi.org/10.3390/f15101772

Chicago/Turabian Style

Yoon, Tae Kyung, Seonghun Lee, Seungmin Lee, Sle-gee Lee, Mariam Hussain, Seungho Lee, Haegeun Chung, and Sanghoon Chung. 2024. "A Wind Tunnel Test for the Effect of Seed Tree Arrangement on Wake Wind Speed" Forests 15, no. 10: 1772. https://doi.org/10.3390/f15101772

APA Style

Yoon, T. K., Lee, S., Lee, S., Lee, S. -g., Hussain, M., Lee, S., Chung, H., & Chung, S. (2024). A Wind Tunnel Test for the Effect of Seed Tree Arrangement on Wake Wind Speed. Forests, 15(10), 1772. https://doi.org/10.3390/f15101772

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