Abstract

Evapotranspiration (ET) is one of the important components of the global hydrologic cycle, energy exchange, and carbon cycle. However, basin scale actual ET (hereafter ETa) is difficult to estimate accurately. We present an evaluation of four actual ET products (hereafter ETp) in seven sub-basins in the Tibetan Plateau. The actual ET calculated by the water balance method (hereafter ETref) was used as the reference for correction of the different ETp. The ETref and ETp show obvious seasonal cycles, but the ETp overestimated or underestimated the ET of the sub-basins in the Tibetan Plateau. A simple and effective method was proposed to correct the basin-scale ETp. The method was referred to as ratio bias correction, and it can effectively remove nearly all biases of the ETp. The proposed method is simpler and more effective in correcting the four ETp compared with the gamma distribution bias correction method. The reliability of the ETp is significantly increased after the ratio bias correction. The ratio bias correction method was used to correct the ETp in the seven sub-basins in the Tibetan Plateau, and regional ET was significantly improved. The results may help improve estimation of the ET of the Tibetan Plateau and thereby contribute to a better understanding of the hydrologic cycle of the plateau.

Highlights

  • Evapotranspiration (ET) represents the total evaporation and transpiration of plants from terrestrial and oceanic surfaces to the atmosphere [1]

  • Several global ETp have been developed to estimate the distribution of ETa, including remote sensing-based methods, land surface models, surface energy balance, and reanalysis products [2,3,4,5,6]

  • We propose a simple and efficient method, the ratio bias correction method, to correct four ETp in seven sub-basins on the Tibetan Plateau

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Summary

Introduction

Evapotranspiration (ET) represents the total evaporation and transpiration of plants from terrestrial and oceanic surfaces to the atmosphere [1]. ETp significantly contributed to our knowledge of hydrological components [7]. These methods are limited by sparse measurement stations, as well as some uncertainties [8], especially with regard to surface energy balance models. The surface energy balance model, based on satellite images and remote sensing data, is a powerful and accurate method for calculating ET [8,9,10,11,12,13,14]. Accurate measurements depend on the reliability of the input data, especially the remote sensing data at basin scale.

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