Control theory has been showing progress in its evolving exercise in precision agriculture for the search for optimized irrigation schemes regarding water saving. Nevertheless, implementations have been limited to on-off and PID (proportional-integral-derivative) controllers, with the more sophisticated variations being fuzzy controllers. To improve this, a robust model-based irrigation controller using a discrete sliding mode approach is taken. The work presented in this paper aims to evaluate whether the proposed controller improves irrigation performance in a pecan crop subject to uncertainties, disturbances, and delays. The paper describes the development and implementation of a discrete sliding mode controller, including system identification, model validation, stability analysis, controller parameter selection, and system response analysis. The proposed approach is evaluated, in terms of water consumption and irrigation accuracy, with two widely used watering schemes: open-loop time-based control and closed-loop on-off control. Experimental results indicate that the controller reaches water savings of 48% and 10% when compared with the time-based and on-off methods, respectively, while irrigation accuracy is kept within the range of 1% of volumetric water content.