Agro-productive impact of an experimental model for estimating pressure and flow rates in the micro- irrigation system of the 14 July organoponic farm

Water is the lifeblood of farming, but delivering it correctly is a delicate balancing act. In modern agriculture, the goal is often to apply just the right amount of moisture to every single plant, avoiding both the waste of flooding and the stress of drought. This is particularly challenging in systems where water travels through long pipes with many small outlets, known as emitters, designed to drip or spray water directly onto crops. As water moves through these pipes, friction slows it down, and the pressure drops, meaning plants at the beginning of the line might get a heavy dose while those at the end receive very little. If the pressure is too low, the water doesn't reach the roots effectively; if it is too high, the system wastes energy and water. Farmers need a way to predict exactly how much pressure and flow will reach each plant so they can adjust the system before the crops suffer. Without this knowledge, a farm might look green on the surface while its productivity quietly declines due to uneven watering.

At the "14 July" organoponic farm in Ciego de Ávila, Cuba, researchers set out to solve this problem using a new approach. They tested a mathematical model, which is essentially a set of rules that simulates how water behaves inside the pipes, to see if it could help them manage the farm's micro-irrigation system more effectively. The farm grows a variety of vegetables, including lettuce, Swiss chard, green beans, and cucumbers, in raised beds covered by a network of pipes and sprinklers. The team compared two ways of running the farm: the standard method, where they checked the system based on initial measurements and general experience, and a new method where they used their model to predict and control the pressure and flow at every single sprinkler. They also paid close attention to the weather, using rainfall data to decide when to turn the pumps on and off, aiming to save energy and water whenever nature provided a helping hand.

The results of this experiment were clear and measurable. When the farm operated under the new model, the water distribution became significantly more even. The researchers found that the uniformity of the water application, a measure of how consistently every plant received water, jumped from a good level to an excellent one. The variation in the amount of water coming out of each sprinkler dropped dramatically, meaning that the plants at the end of the pipe received nearly the same amount of water as those at the start. This consistency translated directly into better harvests. The crops grown under the new management strategy produced noticeably more food: lettuce yields increased by nearly one-fifth, Swiss chard by over one-fifth, green beans by a similar margin, and cucumbers by nearly a quarter. The model allowed the farmers to diagnose problems in the pipes, such as clogged or broken sprinklers, and fix them before they could hurt the crops.

Beyond the crops themselves, the study highlighted how much water and energy could be saved by listening to the sky. The researchers tracked the daily rainfall over several years and found that the rain often provided enough water for the crops, especially for Swiss chard, which required no additional irrigation at all during certain periods. By using the model to schedule watering only when the rain had not provided enough moisture, the farm reduced the number of times they had to run their pumps. This not only conserved a substantial volume of water but also cut down on the electricity needed to push that water through the pipes. The study concludes that this mathematical tool is a practical way for farmers to understand the hidden physics of their irrigation systems, leading to healthier plants, higher yields, and a more efficient use of the precious resources of water and energy.