The frequency of extreme hydrological events has been steadily increasing globally and is expected to worsen in the future. Hence, event-scale global hydrologic modeling capacity is essential for historical analysis, as well as future projections, including under a changing climate. Xanthos is a global hydrologic model that simulates streamflow characteristics at a monthly timescale. However, the primary source of this limitation is the monthly runoff scheme embedded in the model, which significantly limits its use for extreme event simulation and analysis, including floods. This study aims to extend Xanthos to enable daily time step simulation by introducing a new event-scale runoff generation module from the Probability Distributed Models (PDMs) family. We calibrate and validate the enhanced Xanthos model with the PDM runoff module at a number of large basins across the globe where sufficient daily streamflow observations are available. Key input data sets for calibration and validation of the new daily time step scheme include the WATCH-WFDEI (WATer and global CHange Forcing Data Methodology Applied to ERA-Interim Data) daily climate forcing data from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), as well as daily observed streamflow data from the Global Runoff Data Centre (GRDC). We also perform parameter sensitivity analysis. When completed, this enhanced version of Xanthos will support global-scale flood simulation and analysis of flooding under the impacts of climate change and human activities.