METRIC and WaPOR Estimates of Evapotranspiration over the Lake Urmia Basin: Comparative Analysis and Composite Assessment

Abstract

Evapotranspiration is one of the main components of water and energy balance. In this study, we compare two ET products, suitable for regional analysis at high spatial resolution: The recent WaPOR product developed by FAO and METRIC algorithm. WaPOR is based on ETLook, which is a two-source model and relies on microwave images. WaPOR is unique as it has no limitation under cloudy days, but METRIC is limited by clouds. METRIC and WaPOR are more sensitive to land surface temperature and soil moisture, respectively. Using two years (2010 and 2014) of data over Lake Urmia basin, we show that in most areas, ET from METRIC is higher than WaPOR and the difference has an ascending trend with the elevation. The ET of lysimeter station is fairly consistent with METRIC based on a single observation. Our analysis using NDVI and land use maps suggests that the histogram of ET from WaPOR might be more realistic than METRIC, but not its amount. The fraction of ET to precipitation in rainfed agriculture areas shows that WaPOR is more accurate than METRIC, mainly because in the absence of other water resources such as ground water annual ET cannot exceed annual precipitation. In contrast, METRIC produces a more realistic estimate than WaPOR over irrigated farms. The results suggest that the two products can complement each other.

Spatiotemporal Assessment of Irrigation Performance of the Kou Valley Irrigation Scheme in Burkina Faso Using Satellite Remote Sensing-Derived Indicators

“…Moreover, in FAO-WaPOR, gaps and anomalies are filled using a smoothing method, which can contribute to errors. Despite the underestimation observed in 2013, which can be related to these systematic errors within FAO-WaPOR [44,73], and, to some extent, to the quality of Landsat 7 ETM+ images, PySEBAL seemed to satisfactorily estimate ETa values across the KVIS.…”

Satellite‐Based Monitoring of Irrigation Water Use: Assessing Measurement Errors and Their Implications for Agricultural Water Management Policy

“…Accuracy of actual ET estimation or crop coefficients from multispectral satellite imagery, for example, has been shown to be reduced due to limited spatial resolution of satellite data products relative to agricultural field sizes (Fisher et al, 2017; Vogels et al, 2019), gaps in the frequency of image acquisition caused by cloud cover (Senay et al, 2016), uncertainties in the measurement via satellites of key inputs to energy balance models such as surface temperatures or net radiation (Fisher et al, 2008), difficulties in adequately parametrizing effects of soil moisture (Purdy et al, 2018), or advection processes (Aragon et al, 2018) on ET fluxes, along with operator errors or biases introduced when implementing ET estimation algorithms (e.g., in the selection of hot/cold pixels when constraining surface energy balance models— Long & Singh, 2013). Moreover, for a given location and time, large differences often are found in the absolute values of actual ET estimated using different energy balance algorithms and models (Biggs et al, 2016; Ershadi et al, 2014; Gonzalez‐Dugo et al, 2009; Javadian et al, 2019; Medellin‐Azuara et al, 2019), with little consensus in the scientific literature about the best‐performing model types (Zhang et al, 2016). Together with limited availability of in situ ET observation data for validating satellite estimates, this creates challenges for water managers considering use of remotely sensed ET data in irrigation water use estimation and monitoring.…”

Assessing Gauge Undercatch Correction in Arctic Basins in Light of GRACE Observations

“…Moderate Resolution Imaging Spectroradiometer ET showed large gaps over the studied basins; thus, the upper and lower bound of ET estimates are determined from GLDAS and WGHM and used to show uncertainty range in the final estimate. Other ET products (e.g., Javadian et al 2019) could also be used, but here we use those that are popular for large scale analysis. Most cold-season water budget studies do not consider sublimation, but here it is considered because Behrangi et al (2018) found that sublimation can account for as much as 7% of the total water budget over some high-latitude regions.…”