A method for mapping flood hazard along roads.

Area of Science:

• Hydrology
• Environmental Science
• Geographic Information Science

Background:

• Road flooding poses significant risks to transportation infrastructure and public safety.
• Accurate flood hazard assessment is crucial for effective road planning and maintenance.
• Existing methods often lack the spatial resolution or data integration needed for detailed road flood risk mapping.

Purpose of the Study:

• To develop and validate a novel method for estimating and mapping flood hazard probability along road networks.
• To identify key physical catchment descriptors (PCDs) that significantly predict road flooding.
• To provide insights into the influence of landscape characteristics on road-related flood hazards.

Main Methods:

• Utilized a Geographic Information System (GIS) to derive candidate physical catchment descriptors (PCDs).
• Employed statistical modeling to identify PCDs that significantly predict road flooding.
• Applied the method to a case study area in western Sweden with a history of severe road flooding.

Main Results:

• Identified topography, soil type, and land use as crucial categories of PCDs for predicting road flooding.
• Key predictive drivers included topographical wetness index, catchment road density, soil properties (gravel substrate), and local channel slope.
• The developed method demonstrated utility in estimating flood hazard probability for critical road sections.

Conclusions:

• The proposed method offers a straightforward and consistent approach to estimating road flood hazards.
• Findings highlight the importance of specific landscape characteristics in determining flood risk along roadways.
• The method can inform future roadway planning and the maintenance of existing infrastructure, particularly in ungauged basins.