苏南丘陵地区茶树蒸散发估算模型的适用性评估

根据波文比能量观测系统在2017—2020年间的ET_c观测数据，分别对FAO-56作物系数模型(S-k_c)与Priestley-Taylor(PT-α)模型进行参数率定及修正，分析了茶树ET_c在各生育期内对气象因子的响应特性，并评估了修正后的S-k_c与PT-α模型对于苏南丘陵地区茶园的应用效果.研究表明：S-k_c模型的作物系数k_c在茶树生长初期为0.83、中期为1.19、后期为1.06,PT-α模型系数α年均值为1.09;气温、水汽压差及土壤体积含水率对ET_c的影响在0.05的水平下具有统计学意义，且各气象因子对ET_c的相关性均表现为在茶树生长中期高度相关，生长后期偏低；以波文比能量观测系统的ET_c观测数据作为参照，修正后的S-k_c模型高估了茶树ET_c,PT-α模型低估了ET_c,但PT-α模型的误差(R²...

Applicability evaluation of tea plant evapotranspiration models in hilly area of southern Jiangsu Province

Based on the ET_c data measured by Bowen ratio energy balance method from 2017 to 2020, the parameters of crop coefficient(S-k_c)model and Priestley-Taylor(PT-α)model were detemined and modified respectively. The response characteristics of ET_c to meteorological factors in each growth period were analyzed. And the applicability of the modified models to simulate ET_c in tea plants in southern Jiangsu was evaluated. Results show that crop coefficient k_c of S-k_c model is 0.83, 1.19 and 1.06 at the early, middle and late growth periods, respectively, and the annual mean value of PT-α model coefficient α is 1.09. The meteorological factors T_a, VPD and VWC are significantly correlated with ET_c. The overall meteorological factors and ET_c are highly correlated in the middle growth period and less correlated in the late growth period. The S-k_c model overestimates ET_c measured by Bowen ratio energy balance method as a reference, and PT-α model underestimates ET_c. While the error of PT-α model(R²=0.88)is lower than that of S-k_c model(R²=0.91). The precision of the PT-α model is higher in the rapid growth period(MAE=0.72 mm/d, RMSE=0.99 mm/d)and the late growth period(MAE=0.35 mm/d, RMSE=0.23 mm/d), and the precision of S-k_c model is higher in the middle growth period(MAE=0.36 mm/d, RMSE=0.48 mm/d).The results of this study indicate the variation characteristics and methods of ET_c in whole growth. It is of great reference value to the scientific production of tea trees in hilly areas of southern China.