This paper proposes a framework for designing resilient and robust urban drainage systems by integrating resilience principles while addressing deep uncertainty in network blockage. The study develops a multi-objective simulation-optimization model with decision variables for the type and implementation area of nature-based flood control measures. The framework pursues three key objectives: maximizing flood resilience, minimizing flood damage, and minimizing flood management costs. Hydraulic blockage uncertainty is modeled through identification of influential blockage factors and application of fuzzy logic, with an information gap decision theory (IGDT) approach employed to select robust solutions against channel blockage uncertainties. The framework's effectiveness is evaluated through application to the eastern sub-catchment of Tehran's stormwater drainage system. Sensitivity analysis reveals that both peak flood discharge and its timing exhibit significant sensitivity to channel blockage uncertainty. The optimization-simulation model generates 50 non-dominated scenarios, from which the most robust solution—maintaining satisfactory performance across the widest range of uncertainty—is selected. Results demonstrate that the robust management scenario achieves a 37% improvement in resilience at a cost of only $0.84 million, while simultaneously reducing potential flood damage by 20% under blockage conditions.