The study deals with flood management strategies for flood resilient short- and long-term planning and development of the Adyar basin, comprising Chennai Metropolitan Area (CMA) in Tamil Nadu, India. The basin gets frequent flooding during the North-East monsoon season (mid-October to mid-December) due to recurrent depressions and cyclones. The basin with the highly urbanized CMA is expected to urbanize at a considerable rate in the future. In that regard, there is a need to preserve the existing water bodies that are locally referred to as tanks from getting urbanized. They offer retention storage for the flood waters and the channels originating from them join to form the Adyar River. Therefore, it is highly imperative to quantify their role in flood moderation and probe into their efficiency as source control measures under various future scenarios of urbanization and climate change. From a short-term flood management perspective, setting up an accurate and computationally efficient flood forecasting framework is of prime importance. In order to generate flood inundation maps for the urban areas, the high spatial resolution elevation data from the latest technologies like LiDAR is coarsened or averaged so that simulation can be done in a reasonable time. However, while doing so minute urban features such as buildings, streets, highways, minor canals, etc. will be lost. Hence, there is a need to develop a computationally efficient hydraulic model that that runs at coarser level while still representing the small features within the numerical grid. A state-of-the-art sub-grid local inertial algorithm is developed to represent the minute topographical features, but simulation can be done in relatively less time compared to the existing hydraulic models. The developed algorithm can improve the accuracy of coarse grid models up to ~17% in flood extent mapping and is thousands of times faster than full 2D models. From a long-term perspective, an urbanization-hydrologic-hydraulic modeling framework is used to simulate floods for various historical and plausible future flood management scenarios considering the tanks in the upper part of the catchment. An ANN model is developed to predict the urban sprawl by 2050. An existing hydrologic model is used to generate runoff from the basin for various scenarios. It is shown that the preservation of tanks and dredging strategies can moderate riverine flooding of Chennai city to a great extent. Disappearance of tanks can cause a 1 in 50-year flood to inundate the city similar to a 1 in 100-year flood.