Automated irrigation systems for wheat and tomato crops in arid regions

Automated irrigation systems (AISs) are critical for the sustainability of irrigated farming systems, considering the present water crisis in Saudi Arabia. This study investigated whether electronic controllers in irrigation systems effectively save water. The study also assessed the effect of these controllers on crop yield using drip and sprinkler irrigation systems in severely arid climate conditions. Evapotranspiration (ET) controllers were installed in experimental fields of wheat (Triticum aestivum) and tomato (Solanum lycopersicum Mill.) crops for 2 successive seasons. The results revealed that the water use efficiency (WUE) and irrigation water use efficiency (IWUE) were typically higher in the AIS than in the conventional irrigation control system (CIS). Under the AIS treatment, the WUE and IWUE values were 1.64 and 1.37 k·gm-3 for wheat, and 7.50 and 6.50 kg·m-3 for tomato crops; under the CIS treatment the values were 1.47 and 1.21 kg·m-3 for wheat and 5.72 and 4.70 kg·m-3 for tomatoes, respectively. Therefore, the AIS provided significant advantages in both water savings and crop yields by utilising up to 26% less water than the CIS, and simultaneously generating higher total yields. The automated irrigation system technique may be a valuable tool for conserving water and scheduling irrigation for wheat and tomato crops, and may be extendable to other similar agricultural crops.Keywords: autonomous control, evapotranspiration controller, water conservation, sprinkler and drip irrigation, water-use efficiency, arid region

Modeling sprinkler irrigation infiltration based on a fuzzy-logic approach

In this study, the irrigation water infiltration rate (IR) is defined by input variables in linguistic terms using a fuzzy-logic approach. A fuzzy-logic model was developed using data collected from published data. The model was trained with three fuzzy membership functions: triangular (‘trimf’), trapezoid (‘trapmf’), and pi (‘pimf’). The fuzzy system considered the number of irrigation events, applied water depth, polyacrylamide application rate, water application time, water electrical conductivity, soil surface slope, and soil texture components as input variables. The inputs were classified in terms of low, medium, and high levels. The output variable (i.e., IR) was rated in terms of five levels: very low, low, medium, high, and very high. Using statistical analysis, the values of IR resulting from the developed fuzzy-logic model were compared with the observations from the experiments. The results confirm that the agreement between the observations and predictive results was acceptable, except for fuzzy ‘trimf’. The coefficient of determination provided the greatest value when using the ‘trapmf’ and ‘pimf’, with the value estimated for the ‘pimf’ slightly higher than that of ‘trapmf’. Based on the results that were obtained, irrigation managers can use the fuzzy-logic approach to modify their field practices during the growing season to improve on-farm water management

Evaluating two irrigation controllers under subsurface drip irrigated tomato crop

Smart systems could be used to improve irrigation scheduling and save water under Saudi Arabia’s present water crisis scenario. This study investigated two types of evapotranspiration-based smart irrigation controllers, SmartLine and Hunter Pro-C2, as promising tools for scheduling irrigation and quantifying plants’ water requirements to achieve water savings. The effectiveness of these technologies in reducing the amount of irrigation water was compared with the conventional irrigation scheduling method as a control treatment. The two smart irrigation sensors were used for subsurface irrigation of a tomato crop (cv. Nema) in an arid region. The results showed that the smart controllers significantly reduced the amount of applied water and increased the crop yield. In general, the Hunter Pro-C2 system saved the highest amount of water and produced the highest crop yield, resulting in the highest water irrigation efficiency compared with the SmartLine controller and the traditional irrigation schedule. It can be concluded that the application of advanced scheduling irrigation techniques such as the Hunter controller under arid conditions can realise economic benefits by saving large amounts of irrigation water

Evaluating two irrigation controllers under subsurface drip irrigated tomato crop

Smart systems could be used to improve irrigation scheduling and save water under Saudi Arabia’s present water crisis scenario. This study investigated two types of evapotranspiration-based smart irrigation controllers, SmartLine and Hunter Pro-C2, as promising tools for scheduling irrigation and quantifying plants’ water requirements to achieve water savings. The effectiveness of these technologies in reducing the amount of irrigation water was compared with the conventional irrigation scheduling method as a control treatment. The two smart irrigation sensors were used for subsurface irrigation of a tomato crop (cv. Nema) in an arid region. The results showed that the smart controllers significantly reduced the amount of applied water and increased the crop yield. In general, the Hunter Pro-C2 system saved the highest amount of water and produced the highest crop yield, resulting in the highest water irrigation efficiency compared with the SmartLine controller and the traditional irrigation schedule. It can be concluded that the application of advanced scheduling irrigation techniques such as the Hunter controller under arid conditions can realise economic benefits by saving large amounts of irrigation water