Estimating Evapotranspiration over Heterogeneous Surface with Sentinel-2 and Sentinel-3 Data: A Case Study in Heihe River Basin

Ting Lian,Zhiqing Peng,Huiyuan Liu,Hailong Zhang,Xiaozhou Xin,Shanshan Yu,Fugen Li

doi:10.3390/rs14061349

Abstract

Evapotranspiration (ET) is an important part of surface–atmosphere interactions, connecting the transfer of matter and energy. Land surface heterogeneity is a natural attribute of the Earth’s surface and is an inevitable problem in calculating ET with coarse resolution remote sensing data, which results in significant error in the ET estimation. This study aims to explore the effect and applicability of the evaporative fraction and area fraction (EFAF) method for correcting 1 km coarse resolution ET. In this study we use the input parameter upscaling (IPUS) algorithm to estimate energy fluxes and the EFAF method to correct ET estimates. Five ground stations in the midstream and downstream regions of the Heihe River Basin (HRB) were used to validate the latent heat flux (LE) calculated by the IPUS algorithm and EFAF method. The evaluation results show that the performance of the EFAF method is superior to that of the IPUS algorithm, with the coefficient of determination (R2) increasing, the root mean square error (RMSE) decreasing, and the mean bias error (MBE) decreasing by 17 W/m2 on average. In general, the EFAF method is suitable for correcting the deviation in LE estimated based on Sentinel data caused by land surface heterogeneity and can be applied to obtain accurate estimates of ET.

Highlights

The box plot and examples of these three pixels prove that the changes in latent heat flux (LE) are reasonable, showing that the evaporative fraction and area fraction (EFAF) method is suitable for correcting the error of LE estimated with 1 km resolution Sentinel data caused by land surface heterogeneity
Because the evaporation fraction (EF) of the sub-pixels in the mixed pixel are replaced by the EFs of the searched nearest pure pixels, it is necessary to calculate the average EFs of the pure pixel before correction for different land types when analyzing the sensitivity of the land cover map
Sentinel-2 and Sentinel-3 data provided the parameters required by the input parameter upscaling (IPUS) algorithm to estimate LE

Summary

Introduction

Evapotranspiration (ET) connects the fluxes of water with energy and is a critical component of hydrological and energy balance models [1]. Access to reliable estimates of ET is important to many applications, including in the fields of climatology, meteorology, and agronomy [2]. As a key indicator of crop growth, ET can be used to calculate the amount of water that is consumed by crops, so it holds vast potential for agricultural irrigation [3–6]. Climate change can cause changes in temperature and wind speed, which will change the processes of the water cycle and energy balance. The ET estimation models may be broadly classified as [8]: (1) fully physically models [9–11], including the surface energy balance system (SEBA) proposed by Su [12], Shuttleworth and Wallace model [13], two-source model (TSM) [14], and Penman–Monteith algorithms [15–17];

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