Articles | Volume 21, issue 12
Hydrol. Earth Syst. Sci., 21, 6135–6151, 2017
Hydrol. Earth Syst. Sci., 21, 6135–6151, 2017

Research article 05 Dec 2017

Research article | 05 Dec 2017

Performance of the METRIC model in estimating evapotranspiration fluxes over an irrigated field in Saudi Arabia using Landsat-8 images

Rangaswamy Madugundu1, Khalid A. Al-Gaadi1,2, ElKamil Tola1, Abdalhaleem A. Hassaballa1, and Virupakshagouda C. Patil1 Rangaswamy Madugundu et al.
  • 1Precision Agriculture Research Chair, King Saud University, Riyadh, 11451, Saudi Arabia
  • 2Department of Agricultural Engineering, College of Food and Agriculture Sciences, King Saud University, Riyadh, 11451, Saudi Arabia

Abstract. Accurate estimation of evapotranspiration (ET) is essential for hydrological modeling and efficient crop water management in hyper-arid climates. In this study, we applied the METRIC algorithm on Landsat-8 images, acquired from June to October 2013, for the mapping of ET of a 50 ha center-pivot irrigated alfalfa field in the eastern region of Saudi Arabia. The METRIC-estimated energy balance components and ET were evaluated against the data provided by an eddy covariance (EC) flux tower installed in the field. Results indicated that the METRIC algorithm provided accurate ET estimates over the study area, with RMSE values of 0.13 and 4.15 mm d−1. The METRIC algorithm was observed to perform better in full canopy conditions compared to partial canopy conditions. On average, the METRIC algorithm overestimated the hourly ET by 6.6 % in comparison to the EC measurements; however, the daily ET was underestimated by 4.2 %.

Short summary
In view of the pressing need to assess the productivity of agricultural fields in Saudi Arabia, this study was undertaken in an attempt to apply the METRIC model with Landsat-8 imagery for the determination of spatial and temporal variability in ET aiming at optimizing the quantification of crop water requirement and the formulation of efficient irrigation schedules. This paper will be of great interest to readers in the areas of agriculture (in general), water management and remote sensing.