Application of Remote Sensing in the Evaluation of Water Productivity of Irrigation and Drainage Networks, Case Study- Mirza Koochakkhan Agro-Industrial Company

Abstract

To assess and propose the best irrigation schedule for Mirzakoochakkhan sugarcane agro-industrial irrigation networks by vegetation indices, using vegetation and soil surface moisture maps which were produced by SEBAL Algorithm and TERRA-MODIS satellite images. In the first stage, reflection coefficient of ground surface, ground radiation coefficient, vegetation indices such as NDVI, SA VI, GVI and BGR were determined by data preprocessing obtained from sa tellite images during growth period for 2 years of 2005 - 2006 and 2006 - 2007. 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 water supply. 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 ratio 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 2005-2006 and 2006-2007 is 5. 21 and 6. 16 kg/m3. In addition, relative water supplies for these two years are 1. 67 and 1. 73 respectively. Results of this study, suggest the application of this method for water productivity evaluation in large scale irrigation and ainage networks.