المجلة الدولية للعلوم والتقنية

Flooding, and then Collapse of valley of Derna two dams caused by Hurricane Daniel while passing along the Eastern Coast of Libya, were a new catastrophe witnessed by Libyans on September 11, 2023. As the largest natural disaster in Libya, and thus far the deadliest climate event in the world in 2023, the flood resulted in thousands of fatalities, destruction of properties, damage to infrastructure, total destruction of whole neighborhoods, and the displacement of tens of thousands of residents. To confront the challenges associated with flood risks, simulating rainfall and floodwater flow using Agent Based Modeling (ABM) has become increasingly common in recent years due to its simulation capabilities in mitigating natural phenomena such as flood impacts. This paper presents the use of a model that simulates the hydrology in valley of Derna in order to manage rainfall flooding risks. The paper showcases the benefit of integrating remote sensing, geographic information systems, and artificial intelligence in the field of hydrology. The practical application of the simulation system demonstrates the distinctive ability of ABM in tracing water paths and predicting flood occurrences. Lack of data and model complexity are among the challenges that flood modeling must overcome. The paper discusses the prospects for development and progress in water flow modeling using an advanced technique, and integrates models to enhance flood risk management and reduce the societal impact of floods. Keywords: Valley of Derna Flood, Agent Based Modelling, ABM, Hurricane Daniel, Natural Disaster.