Date of Publication :28th February 2023

Abstract: Floods are one of the common natural disasters that affect all life. This is due to the rapid renewal of fresh water, which acts outside their natural limits and causes widespread destruction of life and infrastructure. Flooding in an area depends on many factors, including average rainfall, rainfall, proximity to bodies of water, and vegetation. This project's goal is to build a database dependent on the factors and analyses the data using a variety of models: Each classification model's accuracy was tested using a combination of regression model, support vector machines, decision trees, and random forests. The results can be used efficiently by climatic organizations and teams for disaster response inform actions in flood-prone region. In this project, we try to test their success in detecting floods and simulating water flow in a given area

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