Evaluation of spatial downscaling for satellite retrieval of evapotranspiration from the nonparametric approach in an arid area

Abstract

Evapotranspiration (ET) data is critical for monitoring the limited hydrological resources in arid areas. At present, the spatial resolution of ET derived by the thermal infrared images from satellite data is coarse (always more than 500 m). The low-resolution data cannot meet the needs of the high-precision mapping of ET. Therefore, it is important to undertake a downscaling procedure to improve the spatial resolution of ET. This paper selects the oasis region and surrounding deserts of Zhangye City of China as study area and compares with two downscaling procedures that include input and output downscaling procedure. The ET is estimated with the Remote Sensing-Non Parametric (RS-NP) model. The two downscaling procedures use Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) to improve the spatial resolution of ET from 1-km to 100 m. Compared with the result derived from the output downscaling procedure, the high-resolution ET derived from the input downscaling procedure has a slightly better performance with R2 of 0.92 and RMSE of 41.8 W/m2, respectively. Neglectingthe downscaling of land surface temperature and broadband reflectance (BBR) result in larger errors of ET estimation with bias values of 73.0 W/m2 and 23.7 W/m2, respectively. Those values account for almost 1/3 and 1/10 of ET values, respectively. In non-vegetated areas, those proportions increase further around 90.6 % and 21.3 %, respectively. Furthermore, the influence of the neglect of the downscaling of the near-infrared reflectance on the ET estimation dominates that of BBR with a proportion of 42 %. The input downscaling procedure is suitable for generating the high-precision map of ET, especially in vegetated areas and during northern hemisphere summer months. Our study is helpful to obtain ET maps in fine spatial resolutions and contribute to the comprehensive understanding of the importance of the downscaling of each kind of input for reliable ET estimations.