Evapotranspiration and Water Productivity Estimation Using SEBAL Algorithm and Comparison With Lysimeter Data

The world has finite water resources, which are under increasing stress as the human population and water demand per capita both increase. These problems are not new but are now becoming more widespread and their impacts more devastating. This has provided additional impetus for the search for solutions to problems arising from the mismatch between demand and supply in terms of water quantity, quality and timing. Increasing water productivity has been identified as one of the global challenges that require urgent attention. Agricultural water productivity (WP) between water and food politicians is so important on watershed scale.This concept is a measure of performance expressed as the ratio of dry biomass to actual evapotranspiration in watershed. Remote sensing techniques which used mostly in research on last decade make its use more necessary. This research was conducted on farms which are located on lower part of Qazvin irrigation network. Evapotranspiration and dry biomass were determined using MODIS images in SEBAL algorithm. In this study, five cloudless images were selected which coincided to lysimeter data. Then ENVI model and ILWIS software were used in SEBAL execution of images. Results obtained from of SEBAL algorithm with five images was compared with lysimeter data in each of five days (R2=0.80). This correlation indicates good agreement between SEBAL estimated WP directly derived from MODIS images and lysimeter data. SEBAL estimated WP in Qazvin plain w/o crop consideration was ranged from 0.12 to 1.3 kg/m3. This value for wheat as an indicator in Qazvin plain was 0.76 kg/m3 by SEBAL and 0.9 kg/m3 by lysimeter.