Evaluation of Multiple Methods for the Production of Continuous Evapotranspiration Estimates from TIR Remote Sensing

Emilie Delogu,Jérôme Demarty,Gilles Boulet,Aubin Alliès,Albert Olioso

doi:10.3390/rs13061086

Abstract

Continuous daily estimates of evapotranspiration (ET) spatially distributed at plot scale are required to monitor the water loss and manage crop irrigation needs. Remote sensing approaches in the thermal infrared (TIR) domain are relevant to assess actual ET and soil moisture status but due to lengthy return intervals and cloud cover, data acquisition is not continuous over time. This study aims to assess the performances of 6 commonly used as well as two new reference quantities including rainfall as an index of soil moisture availability to reconstruct seasonal ET from sparse estimates and as a function of the revisit frequency. In a first step, instantaneous in situ eddy-covariance flux tower data collected over multiple ecosystems and climatic areas were used as a proxy for perfect retrievals on satellite overpass dates. In a second step, instantaneous estimations at the time of satellite overpass were produced using the Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) energy balance model in order to evaluate the errors concurrent to the use of an energy balance model simulating the instantaneous IRT products from the local surface temperature. Significant variability in the performances from site to site was observed particularly for long revisit frequencies over 8 days, suggesting that the revisit frequency necessary to achieve accurate estimates of ET via temporal upscaling needs to be fewer than 8 days whatever the reference quantity used. For shorter return interval, small differences among the interpolation techniques and reference quantities were found. At the seasonal scale, very simple methods using reference quantities such as the global radiation or clear sky radiation appeared relevant and robust against long revisit frequencies. For infra-seasonal studies targeting stress detection and irrigation management, taking the amount of precipitation into account seemed necessary, especially to avoid the underestimation of ET over cloudy days during a long period without data acquisitions.

Highlights

We investigated in detail the different steps affecting the quality of the reconstruction: Step 1: the estimation of ET at the time of remote sensing measurements, either from in-situ eddy covariance or retrieved at the same locations with the Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) energy balance model from surface temperature measurements
The aim is to perform a review of the errors concurrent (i) to the chosen reference quantity and method and ii) to the use of the SPARSE energy balance model for simulating the instantaneous evapotranspiration products from the local surface temperatures
In a third step we evaluated the reconstructed time series of daily ET derived from surface temperature at the time of RS measurements

Summary

Introduction

Evapotranspiration (ET) is an important component of the water cycle and its estimation is required to monitor the water loss and manage crop irrigation needs to ensure the efficient use of water in agricultural environments [1]. Spatially distributed and continuous daily estimates of ET at plot scale are needed. These requirements cannot be met by existing in situ flux measurements. Remote sensing approaches are necessary to monitor ET over space and time. Since evapotranspiration is the most efficient way to dissipate energy from the surface, there is a strong coupling between water availability and surface temperature under water stress conditions.

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Conclusion