Irrigation Scheduling to Increase Water Productivity Using AquaCrop Model

Introduction Khuzestan plain as one of the fertile regions in Iran is suffering from some problems such as soil salinity and water deficit. The most important irrigated crop in Khuzestan is wheat and its average yield in the southern parts of Khuzestan reaches 2 to 3 t ha-1,. Irrigation management and optimal conditions, however, should be provided to reduce both water and salinity stresses in the crop yield in the region. To introduce the best irrigation schedule for wheat in the study area, we applied the AquaCrop model to simulate the irrigation scheduling for the crop. The aims were to (1) calibrate and validate the model, (2) determine the appropriate irrigation scheduling for wheat to improve water productivity and increase grain yield, and (3) also evaluate the performance of the model.       Methodology      To achieve the aims of the research, the Elhai region was selected in almost the provincial center with the coordinates of 31° 38' N and 48° 37' E. The AquaCrop model was, then, used for simulating grain yield and water productivity. This model required daily climate data, phonological and agronomic data, soil characteristics, irrigation water, and groundwater data to be able to simulate the plant and soil parameters. A field experiment was conducted in the Elhai area for collecting the data as was mentioned above (as model inputs) during the wheat growth season (2014-2015). Two farms with different soil characteristics were selected for this purpose. However, in order to calibrate and validate the model, more data was needed. Therefore, two other field experiments were carried out in the site of Veys. Consequently, one farm was used for calibration and three farms were, in turn, used for the validation of the model. Sampling from soil profile (1.2 m) was carried out in the growing season. Water and ground water samples were, then, taken in each irrigation event. In order to be able to assess the irrigation scheduling scenarios accurately, it was necessary to consider a wide range of events, times and amounts of water in simulating scenarios. In this case, ten scenarios were run for simulating the grain yield and water productivity for a 12-year period (2003-2014) in farm 1 of Elhai (Table 1).