Scholarlink

<p>Dhaka, one of the world’s fastest-growing megacities, faces severe urban flood risks driven by rapid urbanization, inadequate drainage infrastructure, and climate change–induced extreme weather. This study develops an integrated urban flood forecasting system for a densely built-up area of Dhaka using the MIKE + hydrodynamic model. The system links hydrological and hydraulic modules to simulate the complex interactions among surface runoff (pluvial), river overflow (fluvial), drainage networks, and overland flow. Real-time data from rainfall, river gauge, and pump stations are incorporated to improve forecasting precision. Sensitivity analysis identified ten influential parameters, optimized during model calibration. Historical flood events from 2019–2022 were used for calibration and validation, yielding high performance with Nash–Sutcliffe Efficiency (NSE) above 0.70, R<sup>2</sup> above 0.80 and Mean Absolute Error (MAE) below 0.1&#xa0;m. The model’s robustness was further verified using major flood events in 2020 2021, 2022, 2024 and 2025 validated against flood marks and community reports and observed data. This advanced forecasting framework offers reliable early warnings and scenario simulations, strengthening decision-making and emergency response for flood-prone urban areas in Dhaka.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Flood forecasting in a highly developed urban area: a synergistic approach to pluvial and fluvial flooding using MIKE + 

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月8日

查看全文
  • Md. Shahadat Hossain,
  • Noshin Saiyara,
  • Tarun Kanti Magumdar,
  • Liton Chandra Mazumder,
  • Shafiqul Islam,
  • Md. Sazzad Hossain,
  • Sarder Udoy Raihan,
  • Mohammad Arifuzzaman Bhuyan,
  • Shakil Ahmed,
  • Kashif Mahmud,
  • Syed Matiul Ahsan

摘要

Dhaka, one of the world’s fastest-growing megacities, faces severe urban flood risks driven by rapid urbanization, inadequate drainage infrastructure, and climate change–induced extreme weather. This study develops an integrated urban flood forecasting system for a densely built-up area of Dhaka using the MIKE + hydrodynamic model. The system links hydrological and hydraulic modules to simulate the complex interactions among surface runoff (pluvial), river overflow (fluvial), drainage networks, and overland flow. Real-time data from rainfall, river gauge, and pump stations are incorporated to improve forecasting precision. Sensitivity analysis identified ten influential parameters, optimized during model calibration. Historical flood events from 2019–2022 were used for calibration and validation, yielding high performance with Nash–Sutcliffe Efficiency (NSE) above 0.70, R2 above 0.80 and Mean Absolute Error (MAE) below 0.1 m. The model’s robustness was further verified using major flood events in 2020 2021, 2022, 2024 and 2025 validated against flood marks and community reports and observed data. This advanced forecasting framework offers reliable early warnings and scenario simulations, strengthening decision-making and emergency response for flood-prone urban areas in Dhaka.