Comparison of 13 models of reference evapotranspiration with large weighing lysimeter measurements in a humid alpine meadow, northeastern Qinghai-Tibetan Plateau
Accurate estimates of evapotranspiration (ET) are of great importance for water balance and energy exchange processes, as ET constitutes the key component of the terrestrial water cycle. Although many applicable reference evapotranspiration (ET0) models have been developed to estimate the ET, these are largely focused on low altitude regions, with little attention to alpine meadow. In this paper, we evaluate the performance of 13 ET0 models by comparison with large weigh lysimeter measurements. Specifically, we use three combination models, seven radiation-based models and three temperature-based models driven with data from 8 June 2017 to 18 September 2018 in a humid alpine meadow, northeastern Qinghai-Tibetan Plateau. The daily ET was also obtained by large weighing lysimeters located in an alpine Kobresia meadow. Results show that the performances of the 13 ET0 models, ranked on the basis of their RMSE (root mean square error), decreased in the order: DeBruin-Keijman>Priestley-Taylor> 1963 Penman> FAO-24 Penman>Hargreaves>Hargreaves2>Hargreaves1>IRMAK1>FAO-56Penman-Monteith>Makkink>Makkink (1967)>Makkink (1957)>IRMAK2. Overall, the radiation-based models performed best, with RMSEs ranging from1.03 to 1.47 mm d−1 and averaging 1.09 mm d−1, followed by the combination models (RMSE from 1.19 to 1.36 mm d−1 and averaging 1.26 mm d−1) and temperature models (RMSE from 1.28 to 1.32 mm d−1 and averaging 1.29 mm d−1). The best radiation-based model (DeBruin-Keijman) was more accurate than the best combination model (1963 Penman) and temperature model (Hargreaves) by 16.67% and 25.49%, respectively. The better performance of the radiation-based models over the other two types may be attributed to their inclusion of the dominant factors affecting ET, such as net radiation (Rn). All models tended to underestimate measured ET during periods of larger evaporative demand (i.e. growing season) and overestimate measured ET during lower evaporative demand (i.e. non-growing season). Our results could help in the selection of a suitable ET model for alpine ecosystems, thereby benefitting water irrigation management.