1.0 Introduction
Actual evapotranspiration (ETa) is the second-largest process and flow in the terrestrial water budget after precipitation (PCP). ETa is also an essential component of plant growth and, therefore, the carbon cycle. Available water resources are becoming, or are already scarce, in many basins worldwide (Degefu et al. , 2018). The acceleration of the water cycle from a climate change perspective will further influence water availability not only for human consumption but also our food sources (Rockström, Falkenmark, Lannerstad, & Karlberg, 2012). For this purpose, accurate estimates of ETa are required for several management tasks, including, but not limited to, water accounting, water footprint, basin-wide water balances, irrigation, crop management and monitoring of climate change and its impact on crop production. These activities require ETa at varying extents and spatio-temporal resolutions.
Remote sensing from satellites is perhaps the only feasible means for quantifying and monitoring ETa for wide-areas (Glenn, Huete, Nagler, & Hirschboeck, Brown, 2007). Several remote sensing approaches exist to estimate ETa which include, surface energy balance methods (e.g. Bastiaanssen, Menenti, Feddes, & Holtslag, 1998; Su, 2002; Allen, Tasumi, & Trezza, 2007), Penman-Monteith methods (FAO, 2020a) and more empirical vegetation indices based methods (Glenn, Huete, Nagler, & Nelson, 2008; Nagler, Glenn, Nguyen, Scott, & Doody, 2013). Currently, there are two operational open-access remote sensing-based ETa products based on remote sensing data at the continental and global scale: MOD16 (Mu, Zhao, & Running, 2011), generated at 250m every 8-days, and LSA-SAF MSG ETa (Ghilain, Arboleda, & Gellens-Meulenberghs, 2011), generated at approximately 3km daily.
Validation of these remote sensing products is an essential step in understanding their applicability. Validation is essential to understand and characterise uncertainty. This uncertainty can guide if the ETa product is suitable as input into different water management activities along with the associated risk when making a decision based on the product. Many studies exist that attempt to validate large remote sensing-based ETa datasets. Most studies are focused on one or two validation methods at one scale. The most common validation methods are either point or pixel scale against ground-truth data, like eddy covariance measurements (e.g., Mu, Zhao & Running , 2011), or spatial inter-comparison of a product over regions, land classes, biomes (e.g., Mueller et al. , 2011). Some authors validate multiple products against each other for spatial and temporal patterns and against ground-truth data (e.g., Hu, Jia & Menenti, 2015; Nouriet al. , 2016). Recently, Weerasinghe, Van Griensven, Bastiaanssen, Mul, & Jia, (2019) compared multiple ETa products at the basin scale to the long term water balance utilising other global models on precipitation and run-off while Liu et al. , (2016) evaluation of basin-scale evapotranspiration estimates against the water balance method. However, these validation efforts often fail to evaluate the product at multi-scale, from pixel to basin or region.
The best-practice validation strategies of big remote sensing datasets have been proposed by (Zeng et al., 2019; 2015). They recommend multi-stage validation activities that include combinations of direct validation, physical validation and cross-comparisons. In practice, many developers of remote sensing products include all or at least a combination of these activities during their validation. To name a few, these include the MODIS MODLAND product (Morisette, Privette, & Justice, 2002; Morisette, Privette, Justice, & Running, 1998); Copernicus Global Land Service products Dry Matter Productivity (Swinnen, Van Hoolst, & Toté, 2015); and ASTER land surface temperature (Schneider, Ghent, Prata, Corlett, & Remedios, 2012).
In regions such as Africa, where little observational data is available, validation should utilise all available avenues for ascertaining product quality, with a multi-step and -phase validation strategy that includes direct validation (with ground measurements), physical consistency check and cross-comparisons. As such, the limitations due to the sparseness of available data are reduced, and the product quality is understood from a multi-scale perspective, by using validation best-practice and combining multiple validation techniques.
The latest available database of continental products, released in 2019, for Africa and the Middle East, is now available on The Food and Agricultural Organization (FAO) portal to monitor Water Productivity through Open access of Remotely sensed derived data (WaPOR) (https://wapor.apps.fao.org/home/WAPOR_2/2). It provides the highest available spatial resolution for an operational open-access actual evapotranspiration and interception (ETIa-WPR) product at the continental scale. This paper presents a multi-scale validation of the version 2 (V2.0) ETIa-WPR. The results from each validation procedure were analysed individually and then as a whole to determine trends and draw conclusions of the product quality.