Improving Blue Evapotranspiration and Irrigated Areas Retrieval in Europe and Africa

The estimation of blue evapotranspiration (ETb), due to irrigated water, is crucial to improve water management, especially in regions where water resources are scarce. Large scale irrigated areas and ETb were previously obtained based on the differences between remote sensing derived ET and values simulated from the Global Land Data Assimilation System (GLDAS). In this paper we improve on the previous method by enhancing the classification scheme so that it represents regions with common hydrometeorological conditions. Bias curves are then identified per class and used to adjust the remote sensing products. Different classifiers are compared and evaluated based on their bias curves and variability. The results show that the k-means classifier is better suited to identify the bias curves per class, capturing the dynamic range of these curves and minimizing their variability within each corresponding class. The irrigated or non-irrigated areas resulting from the retrieved ETb values in the European and African continents correspond by, respectively, 65% and 76% when compared to the blue Water Footprint values given in the literature. These results suggest that the enhanced method could serve as an operational remote sensing method to identify irrigated areas on a global scale.