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.