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Calibration and validation of three evapotranspiration models in a tea field in the humid region of south-east China
Irrigation and Drainage ( IF 1.6 ) Pub Date : 2022-05-25 , DOI: 10.1002/ird.2728
Chuan Zhang 1 , Lanlan Li 1 , Haofang Yan 2, 3 , Mingxiong Ou 1 , Muhammad Akhlaq 1 , Wencheng Zhang 1 , Song Huang 2
Affiliation  

Evapotranspiration (ETc) is the most important part of agricultural water consumption. Accurate determination of the ETc of tea trees is important in the water management of tea fields. In this study, three models, the Penman–Monteith (PM), Priestley–Taylor (PT) and crop coefficient (KC) models, were applied and calibrated using meteorological data of 2017 in a tea field. The calibrated models were validated using the Bowen ratio energy balance (BREB) method with the data of 2018 and 2019 in the tea field. The canopy resistance of the PM model was calibrated by the inverse method with the BREB-measured ETc using the Katerji and Perrier (KP) submodel with R2 equal to 0.80. The annual mean value of the coefficient in the PT model (α = 1.03) was determined based on the BREB results and meteorological data. In addition, the crop coefficients of tea trees based on the measured ETc and reference evapotranspiration (ET0) were comprehensively evaluated, with values of 0.86, 1.19 and 0.96 at the three growth stages, showing a cyclical evolution within a year. The PT model performed best, with a root mean square error (RMSE) equal to 0.82 mm day−1 and a Nash–Sutcliffe efficiency (NSE) equal to 0.90. The PM model underestimated ETc with RMSE equal to 0.79 mm day−1 and NSE equal to 0.84, while the KC method overestimated ETc.

中文翻译:

东南湿润地区茶田三种蒸散模型的标定与验证

蒸散量(ET c)是农业用水量中最重要的部分。茶树ETc的准确测定对茶园水分管理具有重要意义。在这项研究中,使用 2017 年茶田的气象数据应用和校准了 Penman–Monteith (PM)、Priestley–Taylor (PT) 和作物系数 (KC) 三个模型。使用博文比能量平衡 (BREB) 方法以及 2018 年和 2019 年茶田的数据对校准模型进行了验证。使用 Katerji 和 Perrier (KP) 子模型和R 2 ,使用 BREB 测量的 ET c通过逆方法校准 PM 模型的冠层阻力等于 0.80。PT模型中系数的年均值(α=  1.03)是根据BREB结果和气象数据确定的。此外,根据实测ET c和参考蒸散量(ET 0 )综合评价茶树的作物系数,三个生长阶段的数值分别为0.86、1.19和0.96,呈现一年内的周期性演变。PT 模型表现最佳,均方根误差 (RMSE) 等于 0.82 mm day −1且 Nash–Sutcliffe 效率 (NSE) 等于 0.90。PM 模型低估了 ET c,RMSE 等于 0.79 mm day -1,NSE 等于 0.84,而 KC 方法高估了 ET c.
更新日期:2022-05-25
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