Models and measurements of seven years of evapotranspiration on a high elevation site on the Central Tibetan Plateau

• 来源期刊: 山地科学学报（英文版）
• 年，卷（期）: 2020,（12）
• 所属期刊栏目: Mountain Environment
• 页码范围: 3039-3053
• 页数: 15页
• 语种: 英文

摘要

Evapotrantaspiration is a crucial part of the hydrological cycle but few ground observatories for the Tibetan Plateau exist. In this study, we present lysimeter measurements from the growing season during seven years at a remote field location on the Tibetan Plateau. The measurements show rates between 2.5 and 3 mm?d-1 during the warmer months from June to August, dropping to 2 to 2.5 mm?d-1 in September. This results in a total volume of evapotranspiration of approximately 300 mm?yr-1 for the months from June to September. The inter-daily variability is however large, and comparison to meteorological variables suggest that this is largely driven by radiation and humidity. Data for a single season from a nearby flux tower allows us to compare the two common measurement methods for evapotranspiration in the field, showing an overall good agreement between the approaches. We also tested commonly applied models used to estimate evapotranspiration rates, namely the FAO-Penman-Monteith (PM) and the Priestly-Taylor (PT) model,which both make use of radiation data as well as the simpler Hargreaves-Samani (HS) and Rohwer (R)models which only need air temperature and wind speed as input. The most data intensive model (PM)has the lowest root mean square error (RMSE)(1.36 mm?d-1) and the mean bias error (MBE) (-0.05 mm?d-1) and reproduces the daily variability generally well. The much simpler HS model performs slightly worse (1.38 and 0.35 mm?d-1), but fails to reproduce the variability, due to its lack of information of local radiation and humidity data. Our results are in line with large scale estimates of evapotranspiration for the cold and arid region, provide a first long time series of in-situ measurements from a high elevation site and suggest that both the PM and HS models are appropriate when no direct measurements are available.