This study shows the results of global inversion of electrical resistivity tomography (ERT) and induced polarization (IP) data for detecting leachate accumulation in urban landfills. The global approach can handle spatial variability more effectively, which is crucial for leachate detection in landfills since its accumulation is highly variable both laterally and in-depth. Additionally, uncertainty assessment is enabled, providing a quantitative tool for estimating the reliability of geophysical reconstruction. Our approach, based on the very fast simulated annealing (VFSA) algorithm, is applied to a slope urban waste landfill located in Central Italy, where leachate accumulation can trigger instability phenomena. The inverted models identified the landfill layering, as well as capturing the spatial variability in leachate distribution, aligning well with levels observed in two wells. Uncertainty analysis revealed low reliability at the edges and bottom of the model due to reduced sensitivity. Therefore, VFSA inversion can contribute to improving the effectiveness of leachate detection, highlighting the importance of a future time-lapse inversion, as leachate distribution can vary seasonally.