Agricultural water productivity in Qazvin plain by MODIS and AVHRR images and Lysimeter data

Agricultural water productivity is an important concept for water and food managers on large scale, and caused to developing remote sensing technique on several last decades. This research was done on Qazvin irrigation network and was estimated evapotranspiration and dry biomass by using SEBAL algorithm on four MODIS and AVHRR cloudless images. Preprocessing and processing on images were done by ENVI and ILWIS models. The estimations of SEBAL were compared with lysimeter data which comparison results on MODIS and AVHRR showed correlation coefficient 0.92 and 0.81, respectively. Finally, SEBAL produced better evapotranspiration and water productivity estimations when MODIS has been used. Average of wheat water productivity amount measured 0.9 kg/m3 by lysimtere and this amount were estimated 0.76 kg/m3 by MODIS and 1.03 kg/m3 by AVHRR images.