LAUSR

Abstract Simulation models of sprinkler irrigation are a valuable tool to improve the irrigation water management at plot scale. Ballistic theory has been commonly used to simulate drop dynamics in sprinkler irrigation models. A number of experiments on sprinkler irrigation performed in previous studies in the Ebro Valley Spain were analyzed and integrated in a data base. The evaluations were performed on six sprinkler types with different nozzle sizes, operating pressures under different meteorological conditions and spacings. The data base includes 40 isolated and 167 solid-set experiments that were processed with a self-calibrated model to calibrate and validate the ballistic parameters. The ballistic model used in this research was improved with respect to a previous model, moreover some novelties were added. These modifications were done in the phases of: the numerical solution, a wind drift and evaporation losses model, simulations considering slope in the terrain, drop generation (using regular and random methods), the size of the terrain cells where the drops are simulated and considering two drop size distributions, upper limit lognormal and Weibull. The results indicated larger and significant differences of Christiansen´s Uniformity Coefficient measured and simulated when considering a constant wind velocity (9%) and no differences when the wind velocity is defined for intervals equal to or less than 30 min (6%). Regarding the effect of the slope in the terrain, differences between both uniformity coefficients are relevant (11%) when the wind velocity is larger than 4 m s−1. Both drop size distributions were similar in accuracy however, the upper limit lognormal was more suitable to simulate a sprinkler especially designed to operate under low pressure. The predictive ability of the model once calibrated and validated was satisfactory (99% and 75%, respectively). The new model improves the accuracy with respect to previous research and minimizes the computing time for the calibration and validation processes using the cluster Trueno-CSIC.