Estimating Regional Evapotranspiration Using a Satellite-Based Wind Speed Avoiding Priestley–Taylor Approach

Wind speed (u) is a significant constraint in the evapotranspiration modeling over the highly heterogeneous regional surface due to its high temporal-spatial variation. In this study, a satellite-based Wind Speed Avoiding Priestley–Taylor (WAPT) algorithm was proposed to estimate the regional actual evapotranspiration by employing a u-independent theoretical trapezoidal space to determine the pixel Priestley–Taylor (PT) parameter Φ. The WAPT model was comprehensively evaluated with hydro-meteorological observations in the arid Heihe River Basin in northwestern China. The results show that the WAPT model can provide reliable latent heat flux estimations with the root-mean-square error (RMSE) of 46.0 W/m2 across 2013–2018 for 5 long-term observation stations and the RMSE of 49.6 W/m2 in the growing season in 2012 for 21 stations with intensive observations. The estimation by WAPT has a higher precision in the vegetation growing season than in the non-growing season. The estimation by WAPT has a closer agreement with the ground observations for vegetation-covered surfaces (e.g., corn and wetland) than that for dry sites (e.g., Gobi, desert, and desert steppe).

Assessing the Effects of Spatial Scales on Regional Evapotranspiration Estimation by the SEBAL Model and Multiple Satellite Datasets: A Case Study in the Agro-Pastoral Ecotone, Northwestern China

Evapotranspiration (ET) estimation is important for understanding energy exchanges and water cycles. Remote sensing (RS) is the main method used to obtain ET data over large scales. However, owing to surface heterogeneities and different model algorithms, ET estimated from RS products with different spatial resolutions can cause significant uncertainties, whose causes need to be thoroughly analyzed. In this study, the Surface Energy Balance Algorithm for Land (SEBAL) model was selected to explore spatial resolution influences on ET simulations. Three satellite datasets (Landsat Thematic Mapper (TM), Moderate Resolution Imaging Spectroradiometer (MODIS), and Advanced Very High-Resolution Radiometer (AVHRR)) were selected to independently estimate ET in SEBAL model to identify the influence of the spatial scale on ET estimation, and analyze the effects and causes of scale aggregation. Results indicated that: (1) the spatial distributions of ET estimated from the three satellite datasets were similar, with the MODIS-based ET having the largest uncertainty; and (2) aggregating input parameters had limited changes in the net radiation and soil heat fluxes. However, errors in the sensible heat and latent heat fluxes were relatively larger, which were caused by changes in the selection of hot and cold pixels and the NDVI and surface albedo parameters during scale aggregation. The scale errors caused by the model mechanisms were larger than those caused by the land use/cover pattern in the SEBAL model. Overall, this study highlights the impact of spatial scale on ET and provides a better understanding of the scale aggregation effect on ET estimation by RS.

Estimation and Analysis of Regional Evapotranspiration in the eastern province of China with Remote Sensing data

<p>Evapotranspiration(ET) is a critical component of the land surface energy balance system and hydrologic processes. Analysis of spatiotemporal variations and influencing factors of ET is of great importance to evaluate the growing environment for crops and to effectively use water resources, a critical base for production in research region. The traditional methods are based on point measurement, while the remote sensing provides extensive surface information. The development of remote sensing has promoted the study of regional ET.SEBAL model is based on Surface Energy Balance Algorithm for Land and its physical meaning is clear. This model was developed to show the spatial variability of surface evapotranspiration. SEBAL model was capable of being applied to large regional areas in conjunction with Moderate-resolution Imaging Spectroradiometer (MODIS) data products.According to the shortcomings of the traditional method of calculating ET, based on SEBAL model, the daily regional evapotranspiration of Anhui Province was estimated with 1km spatial resolution by using MODIS products and a few of meteorological data(temperature, wind speed) collected in meteorological stations distributed over the study area.Because of lacking observed data from the lysimeter, the results of P-M were compared with the estimation results based on SEBAL model in this research.The comparison of the evapotranspiration estimated with MODIS products and field observation showed that the former results were lower than the latter results on the whole, and demonstrated that there existed certain trend in correlation between the two results, the average relative error was different at different land surface.The ET computation method based on Remote Sensing proves that this model has strong practicality in Anhui, and it will show great potential in this field with more optimizing the model parameters.</p>