We developed a new computer modeling system that connects an ocean model with a river model to better understand how water moves between land and sea. This system can be used to study many coastal processes, including floods caused by both storms and river runoff. It improves how river water is added to the ocean by spreading it across multiple points, making simulations more stable and realistic. Because the river model does not include water temperature, we use machine learning to estimate river temperatures using weather and water data. We applied the system to a case in Saco Bay, Maine, where a storm and heavy river flow happened at the same time. The results show that the system can accurately represent how coastal and river waters interact. Although this example focused on flooding, the model can also be used for other situations, such as water quality studies or storm surge forecasting. In the future, it can be expanded to include waves and weather models, making it a flexible tool for studying coastal environments.