Sensible And Latent Heat Flux Estimation In Tea Fields Using Surface Renewal And Flux Variance Methods

Irrigation water is imperative for agricultural production,and increasing water use efficiency is of prime importance to save water.It is necessary to accurately estimate evapotranspiration（ET）for irrigation scheduling and more efficient use of available water resources.In China,Tea is one of the most drinkable beverages.To increase tea production,proper irrigation management should be achieved through the best techniques for ET estimation.ET can be estimated using different methods,including eddy covariance（EC）,bowen ratio（BR）and lysimeters.However,most of these methods use expensive instrumentation with strict requirements of fetch and high accuracy,complicated operation and data processing.To overcome above problems,previous researches recommend some methods like surface renewal（SR）and flux variance（FV）to calculate sensible heat flux（H）and latent heat flux（LE）and then to obtain ET estimation combined with net radiation（Rn）and soil heat flux（G）.SR and FV methods are much cheaper and ease of use,since both require only high-frequency air temperature measurement with low-cost fine-wire thermocouples.A tea field located in Danyang,Jiangsu Province was selected for 1-year experiment,which included different seasons and weather conditions.Sensible and latent heat fluxes were estimated with both methods and the results were analyzed with comparison of EC method.The further study with FV method was emphasized,considering the effects of fetch length and air temperature measurement height on the estimation accuracy of sensible and latent heat fluxes.Major research work and findings are as follows:（1）Estimation of sensible and latent heat fluxes using Surface Renewal methodAn experiment was conducted in a tea field located at（32.026177 ^oN,119.674201 ^oE）.High frequency（¹0 Hz）air temperature measurement with fine-wire thermocouples（?50μm）,was used for the estimation of sensible heat flux,latent heat flux was extracted as a residual of the energy balance equation using additional measurements of net radiation and soil heat flux.Results were compared against the eddy covariance system during the unstable condition only and days with high precipitation were excluded from the further analysis.Half-hourly data sets of the sensible heat flux(H_SR)of surface renewal and(H_EC)eddy covariance system were regressed and results were in good agreement with R²=0.80,RMSE=27.87 W?m^-2,RE 9.02%and slope of regression 0.68,this slope was used for the calibration of the uncalibrated sensible heat flux estimated by surface renewal method.On the other hand,the half-hourly datasets of the latent heat flux(LE_SR)was regressed against the(LE_EC)measured by the eddy covariance,results showed good agreement with relatively high R²=0.93,RMSE=32.99 W?m^-2 and RE=5.67%.Hence,the SR method can provide relatively low-cost estimation of the sensible heat flux,hence the evapotranspiration.The main drawback of this method,is the need of calibration against the EC system.However,development of the SR method continues,especially for making it more reliable without the need for calibration.（2）Fetch effect on Flux Variance estimation of sensible and latent heat fluxesPrecise estimation of the surface-atmosphere exchange is a major challenge in the field of micrometeorology.Previous literature suggested,the eddy covariance（EC）as the most reliable method for the measurements of surface fluxes.Nevertheless,the EC system is quite expensive and complex,hence other simpler methods are sought.One of these methods is Flux variance,which can estimate the sensible heat flux(H_FV)using high frequency（¹0 Hz）air temperature measurement by a fine-wire thermocouple.Additional measurements of the net radiation and soil heat flux allow the derivation of latent heat flux(LE_FV)as the residual of the energy balance equation.In this study,the performance of the Flux variance method was evaluated,and the results were compared against eddy covariance measurements.The specific goal of present study was to evaluate the performance of FV method for the estimation of surface fluxes along a variable fetch.Experiment was carried out in a tea field;an EC system measured latent and sensible heat fluxes installed in the same study site,and five fine-wire thermocouples were installed towards the wind dominant direction at different distances（fetch）of（TC1=170 m,TC2=165 m,TC3=160 m,TC4=155 m and TC5=150 m）from the field edge.The footprint analysis was employed to examine the effect of air temperature measurement position on the ratio between 90%footprint and measurement height.Results showed a good agreement between the H_FV and H_EC,with all coefficients of determination（R²）larger than 0.6;the sensor at 170 m（TC1）,nearest to the EC system,had highest R²=0.86,RMSE=25 W?m^-2 and RE=9.25%.The estimation of LE_FV at TC1 was also in best agreement with(LE_EC)eddy covariance,with the highest R²=0.90,RMSE=25.11 W?m^-2 and lowest RE=4.73%.The FV similarity constant varied along the fetch within the range of 2.2–2.4.Hence,results proved that the variable fetch can influence the performance of the FV method for the estimation of surface fluxes.（3）Effect of air temperature measurement height on Flux Variance estimation of sensible heat fluxesFlux variance method is considered as a simple method for estimating the sensible heat flux using high-frequency air temperature measured through a fine-wire thermocouple.The specific goal of this study was to evaluate the performance of the FV method at different measurement heights.Experiment was conducted in a Tea field,five fine-wire thermocouples were placed at five different measurement heights（h1=1 m,h2=1.5 m,h3=2 m,h4=2.5 m,h5=3 m）above the soil surface.In addition,reference measurements of the sensible and latent heat fluxes were measured by an eddy covariance system.The data collection was performed over six-year-old tea plants during Sep-Nov 2018,where only the half-hourly datasets under unstable condition were investigated.Best performance of the FV method was observed at measurement height of h2=1.5 m for the estimation of sensible heat flux(H_FV)with R²=0.83,RMSE=28.55 W?m^-2 and RE=10.55%.Best result of the latent heat flux(LE_FV)was obtained at the same measurement height,with R²=0.88,RMSE=25.82 W?m^-2,and RE=7.20%.Results proved the fact that performance of the FV method was influenced by the variable measurement height.The FV method performed well for the estimation of surface fluxes within the inertial sub-layer as compared to the roughness sub-layer and proved that the MOST,（uniform surface,the relation between the fluxes and variances of the atmospheric scalars）is more valid in the inertial sub-layer.Hence,the FV method can perform well for the estimation of evapotranspiration with better placement of the sensors.（4）Long-term estimation of sensible and latent heat fluxes with Flux Variance methodEvapotranspiration（ET）is essential for precise irrigation and water resources management.Previous literature suggested that eddy covariance system can measure direct evapotranspiration in agricultural fields.However,the eddy covariance method remains difficult for routine use,due to it’s high-cost,operational complexity,and relatively multifaceted raw data processing.An alternative method is the flux variance which can estimate the sensible heat flux using high-frequency air temperature measurement by fine-wire thermocouples,at relatively low-cost and with less complexity.Additional measurements of the net radiation and soil heat flux permit the extraction of latent heat flux through the energy balance closure equation.This study examined the performance of the FV method and results were compared against direct eddy covariance measurements.Data was collected from September 2018 to July 2019 covering different seasonal variations.Only the data under unstable conditions were used for the analysis and days with rainfall were omitted.Results showed that the estimated sensible heat flux was in good agreement with that of eddy covariance system in the two different seasons of winter 2018 and summer 2019.Best result of the estimated sensible heat flux was observed in the summer with R²=0.83,including the statistical errors of RMSE=34.97 W?m^-2 and RE=8.20%.The FV extracted latent heat flux was in good agreement with that measured by EC for both seasons.Best result was obtained in the summer with R²=0.92,RMSE=23.12 W?m^-2,and RE=6.37%.Overall estimations of the flux variance method were in good agreement with the eddy covariance system.