Durban is the biggest city of the KwaZulu-Natal province located at the East coast of South-Africa. In South Africa nation wide millions of Rands of damage occur along with tens of casualties as a result of urban flooding. These floods are usually the result of heavy rainfall. In Durban other factors that may contribute to floods are blockage or siltation of the drainage system. The blockage of the rainage system is a result of bad waste management. The continuously rising sea level in combination with a blocked urban drainage system could pose a serious threat. This results in the following main goal of this project: obtain insight in the effects of combined sea storm and high rain/river events on stakeholders and existing transport systems, for regular and more severe events. The scope of the project is the area of Durban from the port up until the Umgeni Business park and from the coast until the hill ridge. This report contains four parts. Part I: Analysis, Part II: Elaboration on Modelling Approach, Part III: Acquiring Results and Part IV: Solutions. In the first part are analysed: stakeholders, the transport network, the storm water network and hydraulic and hydrological aspects. In the stakeholder analysis several stakeholders are identified that either have a significant interest, or significant power to influence any decisions that will have to be made regarding floods. From the traffic analysis the most important roads and bottlenecks were identified. The only interesting network is the road network, since other infrastructure is not used by many people. The stormwater network analysis showed that in several locations such as the Central Business District (CBD) the tide penetrates far into the network and several outfalls are completely underwater during spring tide. This shows the possible vulnerability of the network to a high water level from the sea. The analysis also showed that external factors such as blockage of the manholes by waste could also affect the functionality of the system. The hydraulic & hydrological parameters that were analysed were rainfall and river discharge from the land side and the water level from the sea side. In the second part different maps are created which together reveal the most critical areas with respect to flooding. The most critical areas with respect to stakeholders and the traffic network were identified and mapped. Also the drainage model PCSWMM, which has been used to model the urban drainage system of the study area has been described. In the third part the stakeholder and transport map are combined with a flood map resulting from PCSWMM. The flood scenarios, which are used as input for PCSWMM are based on the likeliness of the combination of occurrence of the sea and land based hydraulic parameters. By the combination of these maps, the consequences of the floods have been evaluated. Because of inaccuracies in the flood map for some regions the focus was laid upon the Central Business District. The consequences of the floods are divided in capital, social and economic costs. Several main roads could get flooded in the CBD which will require the traffic to use other main roads. The exit- and entry ramps of these other roads however are not designed for such an increase in intensity and therefore congestion will arise at these locations. This will cause severe travel time delay and will result in economic costs. With respect to stakeholders, property owners and small businesses will be most affected in some parts whereas in other parts of the area insurance companies will be most affected because of the houses of middle or upper class residents and also business who are all insured for damages caused by floods. The last part contains four proposed solution strategies which can be used as a starting point in treating floods. Floods can be seen as a risk which consists of the combination of probability and consequences. Therefore four general risk treating strategies are used: Accept, Avoid, Mitigate and Transfer. Four global solutions to deal with floods are constructed each based on these different strategy. The four strategies were evaluated using a Multi Criteria analysis. This showed that all strategies are better than the 0-hypothesis (Accept) but none of the strategies proved to be the most suitable. Finally some recommendations are given for further research and to improve the PCSWMM model.