Author(s): Bich Tran; Marloes Mul; Solomon Seyoum; Johannes Van Der Kwast; Remko Uijlenhoet; Graham Jewitt

Linked Author(s): Bich Tran

Keywords: Remote sensing; Evapotranspiration; Uncertainty; Accuracy; Data quality

Abstract: Evapotranspiration (ET), a key variable in both water and energy cycles. It is is very challenging to measure or estimate in large regions. Among many approaches to estimate ET indirectly (e.g. through hydrological modelling), models that are based on satellite remote sensing data (RS) are increasingly being used. However, the RS-based models inherit uncertainty from many sources, such as the model’s algorithm and parameters, input satellite data, and processing techniques. It is challenging to assess this uncertainty due to limitations of validation data, high volume and high dimensionality of RS data. Many studies have evaluated uncertainty in RS-based estimation of ET using different methods and reference data. The suitability of methods and reference data subsequently affect the validity of these evaluations. Therefore, it is necessary to have an overview of different evaluation methods and their uses. This study aimed to systematically review original research papers that assessed uncertainty or accuracy of RS-ET model or data products. We categorized these papers and quantified based on (i) spatial and temporal scale of ET estimation, (ii) types of uncertainty, and (iii) methods used to assess uncertainty. Studies have been geographically concentrated in North Asia, North America, and Europe. Most studies used the validation method, which quantifies the discrepancy between pixel-based ET estimation with an in-situ estimation. Although a standardized validation approach for satellite-based ET estimates is not yet ready, most validation studies employed Eddy Covariance (EC) flux towers for reference estimation at field-scale. In regions where in-situ measurements are limited, many studies use the residual of the water balance as reference. However, few studies considered uncertainty in the reference estimation and mismatch of spatial and temporal scales. For monitoring agricultural fields, most RS-ET methods have been reported with high accuracy. When applying these methods to larger extent, additional assessments are required to better inform data users of the quality of RS-ET estimation. These include cross-validation, sensitivity, and uncertainty analyses. Overall, this review showed the progress in evapotranspiration estimation using satellite data in terms of uncertainty assessment.

DOI: https://doi.org/10.3850/IAHR-39WC2521711920221782

Year: 2022