A number of challenges must be faced when using soil moisture sensors, such as accounting for soil heterogeneity in measurements or dealing with sensor faults. As a consequence, it is difficult to obtain reliable estimations of the water status in the root zone and using sensor data for irrigation planning is not straightforward. In this work, a method is proposed to interpret soil water content measurements that is based on the use of a model to correct and complement sensor data, in particular in the case of a non uniform water distribution. This approach relies on the assumption that porosity is the main driver of heterogeneity in hydraulic properties at small scales, which allows to factor out the spatial variations of the sensor's signal. With practical applications in mind, a simple model and an efficient calibration procedure are developed, in particular considering the online application of the method to complement sensor data in real time. The capabilities of the model are illustrated with data from experiments on the growth of lettuces in greenhouses with reclaimed wastewater irrigation. Requiring only a short calibration period, the model is successfully validated and is proven to be a valuable tool to correct for sensor malfunctions. Moreover, the proposed method is shown to allow the meaningful estimation of the water status of the soil crop system, in particular when measurements of sensors positioned close to each other showed important differences.