Application of Remote Sensing in the Evaluation of water productivity of irrigation and Drainage Networks, Case Study: Mirza koochak khan agro- Industrial Company

In the present research، irrigation management and water productivity on irrigation and drainage networks of Mirza koochak khan agro Industrial Company is evaluated by vegetation index and soil surface moisture maps resulted from SEBAL algorithm and TERRA-MODIS satellite images. In the first stage، reflection coefficient of ground surface، ground radiation coefficient، vegetation indexes such as NDVI، SAVI، GVI and BGR were determined by data preprocessing obtained from satellite images during growth period for 2 years of 1384 and 1385. Then cultivation area and density were estimated. Using the SEBAL algorithm، elements of energy balance on ground surface and Real evapotranspiration were computed and assumed as the water consumption and relative supply of water. Biological production of sugarcane obtained using the average daily solar radiation and fraction of photosynthetic absorbed radiation is determined in form of BGR index and assumed as a symbol of production. Water productivity is resulted from the ration of biological production to real evapotranspiration. Process of seasonal variation is gained for biological production، vegetation index and evapotranspiration. Studying of water supply and demand presents no lack of water in this network and the fraction of overflow is used for salt leaching in soil profile. Average water productivity for biological production in this network for two years of 1384 and 1385 is 4. 24 and 5. 32 kg/m3. In addition، relative water supply for these two years are 1. 67 and 1. 73 respectively. Results of this study، suggests the application of this method for water productivity evaluation in large scale irrigation and drainage networks.