Development of an automatic test bench to assess sprinkler irrigation uniformity in different wind conditions

Abstract

In sprinkler irrigation the water distribution uniformity in field conditions is not always a known factor, mainly due to the many variables involved, especially the wind. The main objective of this study was to design, install and test an automatic sprinkler bench to measure the irrigation uniformity of solid set systems for multiple wind conditions in real time. The system developed measures the different wind speeds and directions while simultaneously recording the rainfall distribution automatically. Consequently, the system requires little manual intervention, thus reducing the operating costs. All the information generated is stored in a database, obtaining multiple results of irrigation uniformity for each stable wind regime. As a second step, uniformities in different situations (layouts and wind directions) were studied. In addition, this study shows the potential for assessing the influence of different variables 2 on irrigation uniformity for several sets of sprinklers. As an example of possible applications, 12150 results of uniformity coefficients for conventional impact rotary head sprinklers with hexagonal nozzles in windy conditions were generated. These data were used to establish comparisons between different sprinklers. To do this, a multiple linear regression methodology was applied in order to analyse the influence of the different contour variables on the irrigation uniformity. The test bench presented along with the methodology to simulate and generate multiple scenarios constitutes a powerful tool for designers, farmers and technicians both for the improvement of existing installations and for future designs. The generation of a large amount of irrigation uniformity results for sprinkler irrigation in different wind conditions will lead to a large database with the potential to be able to determine the irrigation uniformity in all common scenarios.

Trends and Challenges in Irrigation Scheduling in the Semi-Arid Area of Spain

“…The hydraulic features of the on-farm irrigation system must also be considered to establish the irrigation programming. These features depend on the type of system (surface, sprinkler, or trickle) and its design (layout) and hydrant operation (sectoring) [63,89].…”

The Influence of Sinusoidal Oscillating Water Flow on Sprinkler and Impact Kinetic Energy Intensities of Laterally-Moving Sprinkler Irrigation Systems

“…Furthermore, the influence of wind on the sprinkler intensity uniformity of sprinkler irrigation systems composed of multiple sprinklers and represented by laterally-moving sprinkler irrigation systems is not significant. This was due to the superposition of the distribution of sprinkler intensity of multiple sprinklers, which reduces the influence of wind on the sprinkler intensity uniformity of sprinkler irrigation systems [30,[46][47][48][49][50][51][52]. At present, the relevant research is concerned with using constant water pressure to carry out experiments.…”

Developing the non‐dimensional framework for water distribution formulation to evaluate sprinkler irrigation*

“…Irrigation efficiency is an important consideration when selecting a suitable irrigation method in arid and semi-arid regions (Zhao et al, 2012). Many attempts have been made by researchers in analysing the impact of sprinkler irrigation performance on yield production (Naghedifar et al, 2018;Nasseri, 2019), evaluating application efficiency (Koumanov et al, 1997;Silva, 2017) and irrigation uniformity (Bellido et al, 2018), uncertainty analysis (Saretta et al, 2018), estimation of evaporation and runoff (Al-Ghobari et al, 2018;Silva, 2017), reducing energy requirements (Zapata et al, 2018), headloss modelling (Beilicci and Visescu, 2016) and improvement of wateruse efficiency and accuracy to applying the target irrigation depth (Sobenko et al, 2018). In contrast, recent studies have shown that uniformity is the major component in evaluating sprinkler irrigation (Tian et al, 2017;Yan and Jin, 2004;Zhang et al, 2016).…”