Abstract
Intelligent irrigation technologies have been developed in recent years to apply irrigation to turf and landscape plants. These technologies are an evapotranspiration (ET)-based irrigation controller, which calculates ET for local microclimate. Then, the controller creates a program for loading and communicating automatically with drip or sprinkler system controllers. The main objective of this study was to evaluate the effectiveness of the new ET sensors in ability to irrigate agricultural crops and to conserve water use for crop in arid climatic conditions. This paper presents the case for water conservation using intelligent irrigation system (IIS) application technology. The IIS for automating irrigation scheduling was implemented and tested with sprinkle and drip irrigation systems to irrigate wheat and tomato crops. Another irrigation scheduling system was also installed and operated as another treatment, which is based on weather data that retrieved from an automatic weather station. This irrigation control system was running in parallel to the former system ( IIS) to be control experiments for comparison purposes. However, this article discusses the implementation of IIS, its installation, testing and calibration of various components. The experiments conducted for one growing season 2009-2010 and the results were represented and discussed herein. Data from all plots were analyzed, which were including soil water status, water consumption, and crop yield. The initial results indicate that up to 25% water saving by intelligent irrigation compared to control method, while maintaining competing yield. Results show that the crop evapotranspiration values for control experiments were higher than that of ET-System in consistent trend during whole growth season. The analysis points out that the values of the two treatments were somewhat close to each other's only in the initial development stages. Generally, the ET-System, with some modification was precise in controlling irrigation water and has been proven to be a good mean to determine the water requirements for crops and to schedule irrigation automatically.