Management of Surface and Flood Water Collection in Tehran Metropolis Using Artificial Intelligence

Urban areas worldwide face escalating challenges in managing surface water and floods, a predicament exacerbated by rapid urbanization and climate change. Tehran, the dynamic metropolis of Iran, uniquely contends with topographical intricacies and swift urban development. This article explores the transformative role of Artificial Intelligence (AI) in addressing surface water and flood risks in Tehran. In Tehran, complex topography and rapid urban expansion amplify vulnerabilities in flood management. Inadequate drainage infrastructure and the prevalence of impermeable surfaces heighten the city's susceptibility to flooding. To counter these challenges, innovative solutions leveraging AI technologies are imperative. AI emerges as a powerful tool in revolutionizing flood management in Tehran. Early Warning Systems, powered by AI algorithms, enable real-time data analysis, flood prediction, and timely alerts. The scope of AI extends to real-time monitoring, predictive modeling, and infrastructure optimization, collectively bolstering Tehran's resilience to floods. The city's unique topography and climate necessitate customized AI solutions. Machine learning algorithms, fine-tuned with local data, create precise predictive models tailored to Tehran's distinct conditions. Informed by AI insights, smart urban planning optimizes resource allocation for infrastructure development, enhancing the city's overall flood resilience. A comprehensive case study evaluates the practicalimplementation of AI in Tehran's flood management. The study delves into the effectiveness of AI-driven early warning systems, real-time monitoring, and predictive modeling, providing valuable insights into their impact on mitigating flood risks. While AI holds promise, challenges such as data accuracy, model interpretability, and publicacceptance demand ongoing scrutiny. Continuous research, stakeholder collaboration, and a commitment to adaptive strategies are pivotal for sustaining the success of AI-driven flood management in Tehran. In conclusion, the integration of Artificial Intelligence signifies a paradigm shift in Tehran's approach to surface water and floodmanagement. The case study exemplifies the tangible benefits of AI technologies, showcasing their potential to reshape flood management strategies in complex urban environments. As Tehran evolves, embracing AI becomes indispensable for crafting a city capable of adeptly navigating the evolving challenges of water management in the۲۱st century.

Keywords:

Artificial Intelligence , Flood Management , Tehran , Surface Water , Urbanization , Early Warning Systems