Application of Satellite Processing Images in Calculating the Water Requirement of Arable Plants (Case Study:The Part of Northern Land of the Khuzestan Province)

The agriculture is the sector that uses most of fresh water resources. Since the water resources are always subjected to severe depletion, the agriculture sector requires using the water with high efficiency and more effective ways One of the procedures leading to improvement of water management productivity and ultimately to increase of water efficiency is the accurate estimation of the evapo-transpiration or estimation of water use efficiency of the crops. The remote sensing by giving an estimation of the degree of evapotranspiration (with little use of ground data) has a high potential for modification of cultivation patterns and management of water resources This research aims to determine the actual evapo-transpiration (need of water) of maize, which is an indigenous plant in the northern Khuzestan province, using the image processing of Landsat 8 in four passes include: 13 Aug, 14 Sep, 16 Oct and 17 Nov 2013 and also using the required metrological data based on Surface Energy Balance Algorithm for Land (SEBAL). The results showed that the amounts of needed water estimated by SEBAL model for maize in the initial growth stage, development stage, middle stage and the end stage are 5.04, 8.23, 5.55, and 1.46 mm per day respectively. The values from remote sensing were compared for values assessed by FAO- Penman-Monteith and evaporation pan methods and it was observed that MAE and RMSE are 0.45 and 0.18 mm per day compared to FAO- Penman - Montieth method. In sum, the results indicated that the SEBAL model is able to give answers with high accuracy and in short time and can be used as a beneficial and efficient tool in organizing water resources and meeting the plant water needs.