Impact of high-resolution settlement data on flood exposure: a comparative analysis of flood hazard and exposure in the Gin River Basin, Sri Lanka

Abstract

Located in a humid tropical monsoon region, Gin River Basin is frequently exposed to adverse flood impacts. Flood exposure assessments extending beyond traditional hazard assessments are crucial to understand these impacts. We examined flood hazard and exposure dynamics during three flood events in the basin, simulating flood hazard using the rainfall–runoff inundation model. Model parameters, including Manning’s roughness coefficients and soil depth were tuned through a trial-and-error approach using daily rainfall data. Two datasets with different spatial resolutions (∼300 m and 30 m) were used to identify exposed areas. Despite differences in hazard characteristics, the impact on human settlements remained similar, with household damages of 43.72% in 2017, 52.74% in 2016, and 76.65% in 2003. Coarser (∼300 m) land-use maps failed to capture smaller settlements in heavily damaged mid- and upstream areas, whereas high-resolution settlement maps identified them, predominantly located in agricultural and shrubland areas. These areas accounted for 69.3% of exposure midstream, 19.8% downstream, and 10.9% upstream, correlating with the heavy damage reported midstream. This highlights the importance of high-resolution settlement data for accurate flood exposure assessments, even in data-scarce basins. Socio-economic factors, disaster preparedness, and government support should be integrated into detailed flood risk assessments to develop effective mitigation measures.

Keywords

• Floods
• hazard
• exposure
• Gin River
• high-resolution settlement data