Design flood estimation plays a vital role in infrastructure planning, flood risk management, and emergency response across Australia, where rainfall runoff modelling is essential for simulating hydrological processes under design storm conditions. This paper presents a comparative review of four widely used event-based conceptual models: RORB, WBNM, URBS, and RAFTS, highlighting their shared reliance on nonlinear loss and routing structures, while noting key differences in routing techniques, simulation capabilities, and recent enhancements. Guided by the Australian Rainfall and Runoff (ARR) 2019 guidelines, recent developments have focused on integrating stochastic design approaches, particularly through Monte Carlo simulation, with models like URBS and RORB incorporating probabilistic methods to improve uncertainty quantification. However, challenges persist, especially in ungauged catchments where the absence of calibration data and issues such as equifinality and conceptual ambiguity hinder parameter regionalization and model reliability. The review emphasizes the need for standardized benchmarking datasets and coordinated intermodal performance assessments to support objective model selection, and advocates for tools like the Regional Flood Frequency Estimation (RFFE) system to enhance predictions in data-scarce regions. Looking forward, incorporating climate change impacts, advancing uncertainty analysis, and applying artificial intelligence are critical to evolving Australia’s flood modelling framework into a more robust, consistent, and future-ready system