Leakage is the main source of water loss in water distribution networks (WDNs). Therefore, leak detection and localization technology is a major concern for water utilities to save water and meet the ever-growing water demand. This study presents two methodologies for leak localization in District Metered Areas (DMAs): (1) a model-based method using the hydraulic model, flow and pressure measurements, as well as leak flow; (2) a data-driven method that relies on graph-based interpolation. The performance of the model-based method is proved to be negatively affected by model errors and limited sensors. To solve these two problems, on the one hand, flows and residuals between observed and model-simulated data in the non-leak situation are used to develop a residual model to calculate offset values for model output correction. On the other hand, graph-based interpolation is introduced to create ‘virtual’ sensor measurements in the presence of a limited number of sensors. The data-driven method proposed in this work uses graph-based interpolation to estimate the head signals at the nodes without sensors and subsequently create pressure maps. Leak localization is achieved by comparing pressure maps in the non-leak and leak situations. In this process, this methodology does not require a well-calibrated model and leak flow information. Both two methodologies are tested on fire hydrant leak tests in DMAs in the United Kingdom. Results obtained by using the model-based method illustrate the positive impact of model output correction on localization results and the performance of this method under different conditions such as different times of the leak and different sizes of leak flow. The data-driven method performs fairly well in DMAs with a higher spatial density of sensors. Furthermore, the results of both two methods are compared to demonstrate the suitability of the methods in different cases.