*3.4. Latent Heat Flux*

Latent heat flux was extracted as a residual of the energy balance closure using the estimated *HSR*, including the *Rn* and *G* measured separately. A linear regression analysis was performed between the half-hourly estimations of *LESR* and *LEEC* under unstable conditions, and only positive estimations of *LE* were compared during the analysis because only positive *LE* corresponds to evapotranspiration, which mainly arises under unstable conditions [40].

The *HSR* estimated by the SR method yielded a good estimate of the *LESR* using a time-lag of 0.5 s for every half-hourly dataset. The results were in good agreement with relatively high *R<sup>2</sup>* = 0.93 as shown in Figure 7. The performance of the SR method for estimating *LESR* was evaluated using statistical tools including *RMSE* and *RE*. The best result of *LESR* was obtained at a height of 1.8 m above the ground, with slope of regression of 1.21. The statistical errors including *RMSE* and *RE* were obtained as 32.99 W·m−<sup>2</sup> and 5.67%, respectively. These results represent the performance of the SR method for the estimation of *LESR*. The *RMSE* values were greater between the linear regressions of *LESR* vs. *LEEC* as compared to those of *HSR* vs. *HEC*. This was observed due to the fact that the errors were related to the measurements of *Rn* and *G* in both the SR method and the EC system (Table 2).

**Figure 7.** Half-hourly estimated *LESR* vs. *LEEC* under unstable conditions.

A diurnal comparison was made of *LE* with the SR estimations and the measurements by the EC system at time-lag of 0.5 s and a measurement height of 1.8 m above the ground under unstable conditions. For the comparison, two different days were selected: one with a clear sky (day of year 125, 2019) and the other with variable clouds (day of year 101, 2019). The diurnal variation of *LESR* and *LEEC* was observed with respect to the net radiation throughout the day, mainly in the daytime, usually from 8:00 to 16:00. The diurnal variation of *LEEC* and *LESR* was observed throughout the day with respect to *Rn*, for on a clear day,

*Rn* was relatively high, with a maximum value of more than 700 W·m<sup>−</sup>2, and the variation of *LESR* and *LEEC* was in relatively strong agreement, mainly in the mid-day (Figure 8a).


**Table 2.** Experiment instruments and installation.

**Figure 8.** Variation of the *Rn*, *LEEC*, and *LESR.*

On the other hand, the diurnal variation was in good agreement in the day with variable clouds and the estimations were directly influenced by the amount of *Rn* (Figure 8b). Overall, good correlation was observed throughout the day between the measurements of the EC system and the SR estimations.

#### **4. Conclusions**

The performance of the classical surface renewal method was examined in a tea plantation located in Danyang, P.R China. The conventional SR method was applied for the estimation of sensible heat flux using high-frequency air temperature measurement by fine-wire thermocouples, under unstable conditions only, and the results were compared against the measurements of the EC system. Analysis of both these methods showed that the estimated *HSR* corresponded well with *HEC* with *<sup>R</sup><sup>2</sup>* = 0.80, *RMSE* = 27.87 W·m−2, and *RE* = 9.02%, the slope of regression forced through the origin was (α = 0.68), and this slope was used for calibrating the uncalibrated sensible heat flux estimated through the SR

method. The estimated *LESR* was in strong agreement with the latent heat flux measured by the eddy covariance system, with a relatively high coefficient of regression. Based on the results, the surface renewal method can provide simple and relatively inexpensive estimations of *H* and *LE* above tea plantations and, hence, evapotranspiration, which can help in improving the per capita production of tea plants with better irrigation application. In the future, this study can help in adopting this method for obtaining low-cost information about crop water requirements; furthermore, the SR method can be used independently in case the eddy covariance system is not available—for instance, in fields where the fetch requirement is very limited, and application of the EC system is not easy at the corner of the field. On the other hand, the SR method can be installed in a more appropriate way to obtain complete information of wind direction and other climatic factors, which can help growers to manage available irrigation resources at a relatively low cost. The results of this study were in good agreement with some previous studies performed for different crops and in different climatic conditions [5,11,17,18].

**Author Contributions:** Investigation, J.W. and N.A.B.; funding acquisition and supervision, Y.H.; writing—original draft, J.W. and N.A.B.; writing—review and editing, I.A.L., Q.J. and A.S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Key R&D program of Zhenjiang (NY2018007), China, and the Jiangsu Postdoctoral Science Foundations (2016M600376 and 1601032C) and Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD-2018-87).

**Acknowledgments:** We thank Luo Enyou for technical assistance during the experimental activities in the tea fields. We also thank the referees and editors who helped to improve the manuscript quality.

**Conflicts of Interest:** The authors declare no conflict of interest.
