Floods are highly destructive natural disasters. Climate change and urbanization greatly impact their severity and frequency. Understanding flood causes in urban areas is essential due to significant economic and social impacts. Hydrological data and satellite imagery are critical for assessing and managing flood effects. This study uses satellite images, climate anomalies, reservoir data, and cyclonic activity to examine the 2015 and 2023 floods in Chennai, Kanchipuram, and Thiruvallur districts, Tamil Nadu. Synthetic-aperture radar (SAR) satellite data were used to delineate flood extents, and this information was integrated with reservoir data to understand the hydrological dynamics of floods. The classification and regression tree (CART) model delineates flood zones in Chennai, Kanchipuram, and Thiruvallur during the flood years. The study region is highly susceptible to climatic events such as monsoons and cyclones, leading to recurrent flooding. The region’s reservoirs discharged floodwaters exceeding 35,000 cubic meters per second in 2015 and 15,000 cubic meters per second in 2023. Further, the study examines the roles of the Indian Ocean Dipole (IOD), which reached its peak values of 0.33 and 3.96 (positive IOD), and El Niño in causing floods here. The complex network of waterways and large reservoirs poses challenges for flood management. This research offers valuable insights for improving the region’s flood preparedness, response strategies, and overall disaster management.

This research examines the significance of restoring efficient water management systems in India’s semiarid environment, with special emphasis on the role of traditional irrigation structures, such as tanks, in collecting and storing limited water resources. Assessing the benefits of any restoration program, especially when socioeconomic and environmental benefits are involved, is challenging. In the context of tank rehabilitation, a cost-benefit analysis will be conducted regarding economic and ecological returns in the post-desiltation phase. Since the restoration process requires a significant investment, assessing the project’s viability during the planning stage is better. The present study proposes a novel method to indirectly analyse the cost-benefit of the tank restoration process by correlating run-off and storage capacity of tanks before the planning phase. The Ambuliyar sub-basin, which covers an area of 930 square kilometres in Tamil Nadu, India, comprising 181 tanks (water bodies) of varying sizes and shapes, was taken for this study. This study employed the Soil Conservation Service Curve Number (SCS-CN) method, incorporating factors such as soil type, land cover, land use practices, and advanced remote sensing and Geographic Information System (GIS) tools to simulate surface run-off. Run-off volume and tank capacity were compared for all seasons at the micro-watershed level. The results demonstrated that the run-off volume in each micro-watershed significantly exceeded the tank capacity across all seasons. Even during the summer, the run-off volumes in the micro-watershed were considerably higher than the tank capacity. The findings suggest tank restoration can effectively store run-off and significantly fulfil agricultural and other essential needs throughout the year, thereby improving the local rural economy. This study also highlights the need for periodic maintenance and rehabilitation of these tank systems to retain their functionality.