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<p>Riverine floods are a recurring and increasingly severe problem in Southeast Asia, often resulting in the submersion of large urban areas for extended periods. As a result, urban mobility is severely disrupted, significantly affecting the daily activities of residents. Integrating behavioral changes during floods into travel demand forecasting is essential for assessing flood adaptation measures in the transportation sector. However, no detailed analysis has been conducted on the impacts of urban flooding on daily activities and travel behavior, and no examples are available on how to incorporate these impacts into travel demand forecasts. This study proposes the development of an activity-based traffic demand forecasting model that explicitly incorporates behavioral changes in individual activity patterns during floods. The model is designed to reflect the disruptions caused by riverine floods and their impact on daily travel behaviors, road closures, and reduced accessibility, which are often overlooked in traditional forecasting methods. Then, the model evaluates adaptation measures in the transportation sector (such as the elevation of arterial roads), supporting strategic planning for resilient urban mobility during floods.</p>

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Exploring the effects of riverine flooding on traffic demand forecasting using activity-based modeling in Ubon Ratchathani, Thailand

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月19日

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  • Noriyasu Tsumita,
  • Rattanaporn Kaewkluengklom,
  • Sideney Schreiner,
  • Sittha Jaensirisak,
  • Atsushi Fukuda

摘要

Riverine floods are a recurring and increasingly severe problem in Southeast Asia, often resulting in the submersion of large urban areas for extended periods. As a result, urban mobility is severely disrupted, significantly affecting the daily activities of residents. Integrating behavioral changes during floods into travel demand forecasting is essential for assessing flood adaptation measures in the transportation sector. However, no detailed analysis has been conducted on the impacts of urban flooding on daily activities and travel behavior, and no examples are available on how to incorporate these impacts into travel demand forecasts. This study proposes the development of an activity-based traffic demand forecasting model that explicitly incorporates behavioral changes in individual activity patterns during floods. The model is designed to reflect the disruptions caused by riverine floods and their impact on daily travel behaviors, road closures, and reduced accessibility, which are often overlooked in traditional forecasting methods. Then, the model evaluates adaptation measures in the transportation sector (such as the elevation of arterial roads), supporting strategic planning for resilient urban mobility during floods.