Impact of Evaluation of Different Irrigation Methods with Sensor System on Water Consumptive Use and Water Use Efficiency for Maize Yield

The sensor system is one of the modern and important methods of irrigation management in arid and semi-arid areas, which is water as the limiting factor for crop production. The study was applied for 2016 and 2017 seasons out in Al-Yousifya, 15 km Southwest of Baghdad. A study was conducted to evaluate coefficient uniformity, uniformity distribution and application efficiency for furrow, surface drip and subsurface drip irrigation methods and it was (98, 97 and 89)% and (97, 96 and 88)% for 2016 and 2017 seasons;respectively. And control the volumetric moisture content according to the rhizosphere depth for depths of 10, 20 and 30 cm by means of the sensor system. The results indicated that the height consumptive water use of furrow 707.91 and 689.69 mm·season-1 and the lowest for subsurface drip with emitter deep at 20 cm 313.93 and 293.50 mm·season-1 for 2016 and 2017 seasons;respectively. As well, the highest value of water use efficiency for subsurface in drip irrigation at a depth of 20 cm, was 2.71 and 2.99 kg·m-3 and the lowest value for furrow irrigation was 1.12 and 1.20 kg·m-3 for the 2016 and 2017 seasons;respectively.

Modeling of Different Irrigation Methods for Maize Using AquaCrop Model: Case Study

Modeling of irrigation methods is one of the most important techniques that contribute to the future of modern agriculture. This will conserve water as water scarcity is a major threat for agriculture. In this study, AquaCrop model was used to model different irrigation methods of maize in field trails in Al-Yousifya, 15 km Southwest of Baghdad. Field experiments were conducted for two seasons during 2016 and 2017 using five irrigation methods including furrow, surface drip and subsurface drip with three patterns of emitter depth (10, 20 and 30 cm) irrigation. AquaCrop simulations of biomass, grain yield, harvest index and water productivity were validated using different statistical parameters under the natural conditions obtained in the study area. For 2016 and 2017 seasons, results of R2 were 0.98 and 0.99, 0.99 and 0.99, 0.99 and 0.97, and 0.8 and 0.73 for biomass, grain yield, harvest index and water productivity, respectively. The study has conducted that simulation using AquaCrop is considered very efficient tool for modeling of different irrigation applications for maize production under the existing conditions in the central region of Iraq.