Research Project: “Study and Investigation of Evaporation and Wind Drift Losses in Sprinkler Irrigation Systems” was conducted under an agreement between the University of Kurdistan and the Center for International Scientific Studies and Collaborations, led by Dr. Isa Maroufpour.
Losses due to evaporation and wind drift (WDEL) are key factors in reducing the efficiency of sprinkler irrigation systems. Under certain conditions, up to half of the irrigation water may evaporate or be blown outside the target area before reaching the ground surface. This research aimed to develop a novel equation for estimating WDEL based on dimensional analysis and Buckingham’s π theorem, considering a wide range of technical and meteorological variables. Furthermore, this equation is applicable to various types of sprinklers and different climatic conditions.
To this end, laboratory data collected from previous studies in northeastern Spain and northwestern Iran were used. The dataset included 153 WDEL observations under diverse conditions of operating pressure, nozzle diameter, irrigation duration, day/night irrigation, nozzle height above the soil surface, and weather variations. Experiments were conducted on fixed classic systems and moving lateral pipes, using impact, gear-driven, and rotating plate sprinklers.
The final equation consisted of four technical variables (main nozzle diameter, auxiliary nozzle diameter, operating pressure, and nozzle height) and four meteorological variables (air temperature, relative humidity, wind speed, and solar radiation). This equation provided greater accuracy in estimating losses compared to existing relationships in the scientific literature. To validate the model, 70% of the data were used for calibration and 30% for validation. Applying the equation to all available data yielded a coefficient of determination (R²) of 0.81 and a root mean square error (RMSE) of 3.49%. The results indicate that this proposed relationship represents a significant advancement over previous equations in terms of input variable range and predictive capa
