A method for mapping flood hazard along roads

• This paper introduces a method to estimate road flooding hazards in the planning of future roadways.
• Three categories of PCDs are useful for flood prediction: topography, soil type, land use.
• The main drivers are a soil wetness index, road density, soil properties, channel slope.
• The drivers are strong indicators for predicting flood probability in ungauged basins.

A method was developed for estimating and mapping flood hazard probability along roads using road and catchment characteristics as physical catchment descriptors (PCDs). The method uses a Geographic Information System (GIS) to derive candidate PCDs and then identifies those PCDs that significantly predict road flooding using a statistical modelling approach. The method thus allows flood hazards to be estimated and also provides insights into the relative roles of landscape characteristics in determining road-related flood hazards. The method was applied to an area in western Sweden where severe road flooding had occurred during an intense rain event as a case study to demonstrate its utility. The results suggest that for this case study area three categories of PCDs are useful for prediction of critical spots prone to flooding along roads: i) topography, ii) soil type, and iii) land use. The main drivers among the PCDs considered were a topographical wetness index, road density in the catchment, soil properties in the catchment (mainly the amount of gravel substrate) and local channel slope at the site of a road-stream intersection. These can be proposed as strong indicators for predicting the flood probability in ungauged river basins in this region, but some care is needed in generalising the case study results other potential factors are also likely to influence the flood hazard probability. Overall, the method proposed represents a straightforward and consistent way to estimate flooding hazards to inform both the planning of future roadways and the maintenance of existing roadways.