*2.1. Study Site and Climate*

The experiment was conducted at a tea plantation located in Danyang, Jiangsu, P.R China (32.026177◦ N, 119.674201◦ E), at an elevation of 18.5 m above the sea. The study site is mainly dominated by homogeneous crops with trees on the boundaries (Figure 1). The tea plants were 2 years old at the time of experiment and plant height ranged from 0.7 to 0.8 m. The mean air temperature during the experimental seasons ranged from 10 to 15 ◦C in winter and 25 to 35 ◦C in summer, with mean annual precipitation of 2.73 mm.day−1. An EC system was installed at the study station, comprising a 3D sonic anemometer (CSAT3, Sonic anemometer, Campbell Scientific, Logan, UT, USA) and an open-path infrared gas analyzer (IRGA, EC150, Campbell Scientific, Logan, UT, USA) for the surface flux measurements. Both the sonic anemometer and infrared gas analyzer were placed at height of 2.3 m above the ground in the wind dominant direction. The EC system can measure surface fluxes including *H* and *LE* directly. For the additional measurements of relative humidity and air temperature, a sensor (HC2S3-L, Campbell Scientific, Logan, UT, USA) was placed above the ground on a tower along with the EC system.

**Figure 1.** A map representing the location of the study area and the eddy covariance (EC) system installed at study site.

All pieces of equipment were supported with batteries connected with solar panels. A Net radiometer (CNR4-L, KIPP and ZENON) was placed at 2.3 m above the ground on the same pole with the EC system in the south direction to avoid the shading effect. For soil heat flux (G) measurement, two soil heat flux plates (HFT-3.1, TEBS, Seattle, WA, USA) were placed at a depth of 0.08 m. One plate was installed in wet soil between the plants and the other one was installed along the pathway. To calculate the change in heat storage (ΔS), two thermocouples were installed in the soil layer above each plate at a depth of 0.02 and 0.06 m, respectively. The installation and raw data calculation from these plates were performed following the instructions of Campbell Scientific, Inc. [21]. The calculation of soil heat flux was done using the soil properties, including the soil water content, soil heat capacity, and bulk density of the soil from the soil samples collected during the field visits, following the procedure recommended by Tanny, Haijun and Cohen (2006) [22]. For estimation by the SR method, two fine-wire thermocouples (type T), with a diameter of 50 μm (COCO-002, Omega Eng., Irlam, Manchester, UK), were placed at a height of 1.8 m above the ground in predominant wind direction (northwest). The raw data signals from both systems, eddy covariance and surface renewal, were sampled at a high frequency of 10 Hz because the fine-wire thermocouples cannot handle a higher sampling frequency, e.g., 20 Hz. Raw signals were stored on a datalogger (CR3000 from Campbell Scientific). All the recorded data were later analyzed to calculate the turbulence fluxes produced by the eddy covariance system, e.g., frictional velocity. Raw data of latent heat flux measured from the EC system were corrected for coordinate system rotation [23], sensor separation by applying the frequency response correction [24], and path averaging.

On the other hand, the sensible heat flux measured by the EC system was corrected for path averaging and coordinate rotation system. The sonic temperature was also converted to the thermodynamic temperature using high-frequency readings of water vapor concentration obtained through the open-path gas analyzer. Regular maintenance of the instruments was performed during the whole experimental duration. The net radiometer was cleared of dust that accumulates on its domes and its position was maintained horizontally. The sonic anemometer was checked regularly and kept safe from spider webs. Finally, the thermocouples were checked regularly as they are very vulnerable; broken thermocouples were replaced with new ones, fortunately only once during the experiment.

#### *2.2. Footprint Analysis*

Footprint analysis was conducted for estimating the relative contribution of the upwind surface to the fluxes measured by the EC method [13]. In many agricultural practices, surfaces are limited in their area or surrounded by some trees or buildings. Therefore, estimation of the footprint for turbulent fluxes is crucial for proper and reliable execution of EC measurements. The following were input variables for the footprint analysis: measurement height (*za*), displacement height (d), mean wind speed (m·s<sup>−</sup>1), Obukhov length (L), standard deviation of horizontal wind speed (m·s−1), friction velocity (u\*), and wind direction (◦) [25–28]. The footprint model used for the estimation of the distance from which 90% of the measured flux originated, or the ratio of this distance to measurement height, is expressed as Equation (1) [29]:

$$\frac{\mathbf{x}}{z\_a} = \frac{2 \times 9.491}{z\_a} \mathbf{x}\_{\text{peak}} \tag{1}$$

where *x* is the horizontal distance along the fetch from the EC system, *za* is the measurement height, and *xpeak* is the peak location of the footprint distribution function, expressed as Equation (2):

$$\propto\_{peak} = \frac{Dz\_u^P |L|}{2k^2} \tag{2}$$

Here, *D* and *P* are similarity parameters, and *zu* is calculated as Equation (3):

$$z\_{\mathfrak{u}} = (z\_{\mathfrak{a}} - d) . \frac{z\_{\mathfrak{a}} - d}{z\_{\mathfrak{a}} - (d + z\_{\mathfrak{a}})} \left[ \ln \frac{z\_{\mathfrak{a}} - d}{z\_{\mathfrak{o}}} - 1 + \frac{z\_{\mathfrak{o}}}{z\_{\mathfrak{a}} - d} \right] \tag{3}$$

where *zo* is surface roughness length.
