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<p>Urban flooding, intensified by climate change and urbanization, poses significant threats to public safety and economic growth, with annual costs exceeding $100&#xa0;billion. This research addresses this pressing issue by introducing a transformative approach to urban flooding forecasting through advanced artificial intelligence. Central to our innovation is a segmented deep learning model that effectively captures the diverse characteristics of urban environments, facilitating more accurate flood predictions. Its fine-tuning capabilities enable the model to adapt to real-time data and dynamic urban conditions, resulting in significantly enhanced predictive performance. This advancement not only surpasses the accuracy of traditional forecasting methods but also offers substantial potential for real-time applications, supporting city planners and emergency responders in proactive flood management.</p>

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Revolutionizing urban flooding predictions: a segmented deep learning model with fine-tuning update capabilities

  • 期刊论文

  • 发表日期：

    2026年2月12日

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  • Wen Zhu,
  • Siyi Wang,
  • Hexiang Yan,
  • Jiaying Wang,
  • Kunlun Xin,
  • Yunlong Xiao,
  • Tao Tao

摘要

Urban flooding, intensified by climate change and urbanization, poses significant threats to public safety and economic growth, with annual costs exceeding $100 billion. This research addresses this pressing issue by introducing a transformative approach to urban flooding forecasting through advanced artificial intelligence. Central to our innovation is a segmented deep learning model that effectively captures the diverse characteristics of urban environments, facilitating more accurate flood predictions. Its fine-tuning capabilities enable the model to adapt to real-time data and dynamic urban conditions, resulting in significantly enhanced predictive performance. This advancement not only surpasses the accuracy of traditional forecasting methods but also offers substantial potential for real-time applications, supporting city planners and emergency responders in proactive flood management.