This paper presents a multi-criteria risk-based approach for managing urban flood hazards by using a combination of conventional measures and contemporary Sustainable Drainage Systems (SuDS). A multi-objective optimisation model coupled with a simulation model of UDS in the SWMM software is developed with the three objectives of minimising total costs, the risk of flooding and pollution discharged into receiving waters. K-means clustering technique is used to group the optimal solutions. A few optimal solutions and individual SuDS solutions are then ranked together by using the compromise programming (CP) method. The methodology is demonstrated by its application on a case study of the Golestan city UDS in Iran. The results obtained show there are indirect correlations between non-dominated solutions that minimise the risk of either flooding or pollution. The results also show the selected optimal solutions can provide cost-effective strategies that reduce both flood and pollution risks by at least 27% and 50%, respectively.