Optimization Of Evapotranspiration Models And Improvement Of Bowen Ratio Energy Balance Technology For Tea Plants In Southern Jiangsu Province

In the actual farmland production,accurate simulation of the evolution of crop evapotranspiration（ET_c）plays a great role in the formulation of reasonable irrigation system and the improvement of agricultural water use efficiency.In the field environment,crop types and physiological characteristics of crop growth under planting conditions are different.Also,the underlying surface conditions and micro-meteorological environment are greatly different,the existing ET_c model and its parameters still have great uncertainties in application.In addition,a flexible and accurate method to determine ET_c is urgently needed in practical production.Therefore,this study took tea plants in field environment as the research object,and adopted the research method which combined field experiment observation and model simulation to measure the changes of micro meteorological factors,crop growth parameters and water consumption regulation of tea plants in the tea field.Based on Penman-Monteith（PM-r_c）model,Priestley-Taylor（PT-α）and crop coefficient（S-k_c）model,the parameters of the PM-r_c,PT-αand S-k_c model were calculated,and the accuracy of the modified model was verified.The relationship between the meteorological conditions of tea plants at different growth stages and the response of ET_c and meteorological factors at different growth stages was analyzed under field planting environment.The Bowen ratio energy balance（BREB）observation technique was discussed based on the dry and wet bulb thermometer principle.The applicability of the improved BREB method in tea field was evaluated based on vorticity correlation observation method.This research aims in providing a theoretical basis for accurate prediction of ET_c in tea field.The main conclusions of this thesis are as follows:（1）Based on the measured ET_c by BREB method,the sub-model coefficients a and b of KP canopy resistance parameters of PM-r_c model were determined to be 0.87 and 0.45,respectively.The average value of coefficientαin PT-αmodel is 1.04,andαhas a periodic change regulation in a year.The accuracy of ET_c in PT-αmodel can be improved obviously by using the monthly average value ofα.The crop coefficient k_c of tea plant was 0.83,1.19 and 1.06,respectively,at the beginning,middle and end of growth stage,showing periodic changes in the year.（2）PM-r_c,PT-αand S-k_c models can be used to accurately simulate the daily scale ET_c.Overall,S-k_c model overestimated ET_c（R²=0.88）,while PM-r_cand PT-αmodels underestimated ET_c.According to different statistical indexes（MAE,RMSE and NSE）,the precision of the three optimized models was discussed.From December to February,the PM-r_c model had the smallest prediction error for ET_c,but the errors of three models were large during this period.From March to June and October to November,PT-αmodel had a better prediction on ET_c,RMSE and MAE were lower than the other two models,while S-k_c model was second only to PT-αmodel in prediction accuracy of ET_c during this period.From July to September,PT-αand S-k_c models could also accurately predict ET_c,with R² higher than 0.95.（3）The overall variation trend of net radiation R_n and soil heat flux G was consistent,which was higher from June to September.The maximum value of R_n appeared in July,which was 241 W m^-2.The maximum value of G was 41W m^-2,appearing in May.The annual mean values of R_n and G were 102 and11.3 W m^-2,respectively.The average annual precipitation P is 1053 mm.Soil volumetric water content VWC varied from 0.13 to 0.39 cm³cm^-3.Air temperature T_a and pressure difference of saturated water vapor VPD showed a single peak,and the peak appeared in August,with the same changes throughout the year.The lowest wind speed appeared in July and August,but the wind speed law was not obvious.（4）The correlation coefficient between meteorological factors and ET_c was low in the beginning growth stage of tea plant,and then the correlation gradually increased.The overall ET_c had the strongest response to meteorological factors in the middle growth stage,and then decreased gradually in the late growth stage.There was a significant correlation between ET_c and T_a,VPD and VWC during the whole growth stage.（5）Regression analysis between meteorological factors and ET_c of tea plant was determined.Among them,net radiation R_n and temperature T_a were the main influencing factors of ET_c,temperature T_a and solar net radiation R_n were positively correlated with ET_c.The saturated water vapor pressure difference VPD,soil volumetric water content VWC and precipitation P were positively correlated with ET_c.Wind speed u was negatively correlated with ET_c.During the whole growth period of tea plant,the influence degree of meteorological factors on ET_c drive of tea plant was:R_n>T_a>VWC>P>VPD>u.（6）The change process of latent heat flux LET and sensible heat flux H observed by eddy covariance system and thermocouple improved BREB technique（BR-FW）at the daily scale were in good agreement.