Wu Yingnan, Li Qiaozhen, Zhong Xiuli, Liu Xiaoying
Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing, China.
Front Plant Sci. 2024 Nov 7;15:1470409. doi: 10.3389/fpls.2024.1470409. eCollection 2024.
Accurate estimation of farmland evapotranspiration (ET) is crucial for agricultural production. The accuracy of the widely used Penman-Monteith (PM) equation for estimating crop ET depends on the quality of input data and their ability to accurately model the canopy resistance ( ). In this study, we evaluated the PM equation in estimating winter wheat ET using nine models, with both original and recalibrated parameters, including the Farias (FA), Monteith (MT), Garcίa-Santos (GA), Idso (IS), Jarvis (JA), Katerji-Perrier (KP), Stannard (ST), Todorovic (TD), and Coupled surface resistance (CO) models. We used long-term measurements (2018 to 2023) from the Bowen ratio energy balance method at both daily and seasonal scales. Parameterization was performed using data from the 2020-2021 growing season, while the remaining 4 years were used for verification. The results showed that the FA, KP, and ST models performed better in estimating daily ET with original parameters, achieving a root mean square error (RMSE) of 1.07-1.16 mm d and a mean bias error (MBE) of -0.59-0.02 mm d. After parameterization, the performance of acceptable models based on RMSE (ranging from 1.07 to 1.22 mm d, averaged 1.16 mm d) ranked as follows on the daily scale: FA > CO > KP > ST > IS > GA > JA > MT. The models were more accurate in simulating ET on a seasonal scale than on the daily scale. Before calibration, the acceptable FA, KP, and MT models overestimated seasonal ET with the MBE ranging from 2.83 to 75.32 mm and RMSE from 29.79 to 82.38 mm. After correction, the suitable models based on RMSE values decreased by FA > CO > KP > IS > ST > GA > JA on the seasonal scale, which ranged from 29.79 to 76.35 mm. The performance of the revised models improved on both daily and seasonal scales, with RMSE reductions of 29.03% and 68.18%, respectively. Considering both the accuracy and calculation complexity, the FA and KP models were recommended to be used in the PM equation to estimate daily and seasonal ET in semiarid regions. The CO, GA, ST, IS, and JA models can also be used as alternatives, depending on the availability of meteorological parameters.
准确估算农田蒸散量(ET)对农业生产至关重要。广泛使用的用于估算作物ET的彭曼-蒙特斯(PM)方程的准确性取决于输入数据的质量及其准确模拟冠层阻力( )的能力。在本研究中,我们使用了9种模型(包括法里亚斯(FA)、蒙特斯(MT)、加西亚-桑托斯(GA)、伊德索(IS)、贾维斯(JA)、卡特吉-佩里尔(KP)、斯坦纳德(ST)、托多罗维奇(TD)和耦合表面阻力(CO)模型)评估了PM方程在估算冬小麦ET方面的性能,这些模型既有原始参数,也有重新校准后的参数。我们使用了2018年至2023年基于波文比能量平衡法的长期测量数据,测量尺度包括日尺度和季节尺度。参数化使用的是2020 - 2021年生长季的数据,而其余4年的数据用于验证。结果表明,FA、KP和ST模型在使用原始参数估算日ET时表现较好,均方根误差(RMSE)为1.07 - 1.16 mm/d,平均偏差误差(MBE)为 - 0.59 - 0.02 mm/d。参数化后,基于RMSE(范围为1.07至1.22 mm/d,平均为1.16 mm/d)的可接受模型在日尺度上的性能排名如下:FA > CO > KP > ST > IS > GA > JA > MT。这些模型在季节尺度上模拟ET比在日尺度上更准确。在校准前,可接受的FA、KP和MT模型高估了季节ET,MBE范围为2.83至75.32 mm,RMSE范围为29.79至82.38 mm。校正后,基于RMSE值的合适模型在季节尺度上排名为FA > CO > KP > IS > ST > GA > JA,RMSE范围为29.79至76.35 mm。修订后模型在日尺度和季节尺度上的性能均有所提高,RMSE分别降低了29.03%和68.18%。综合考虑准确性和计算复杂性,建议在PM方程中使用FA和KP模型来估算半干旱地区的日ET和季节ET。CO、GA、ST、IS和JA模型也可作为替代方案,具体取决于气象参数的可用性。