Integration of climate-informed flood hazard modeling and community perceptions for adaptive flood risk management in the Maha Oya river basin, Sri Lanka

Abstract

The Maha Oya River Basin (MORB) in Sri Lanka experiences recurring floods threatening more than one million residents. However, flood management has traditionally emphasized physical hazard assessment, with limited integration of climate projections and community risk perceptions. This study develops a climate-informed flood hazard modelling framework and examines how exposure to hazard maps influences community risk perception, trust, and adaptive intent. Historical rainfall observations from four stations were quality-controlled, and bias-corrected CNRM-CM6-1-HR projections under SSP1-2.6 and SSP5-8.5 characterised future extreme rainfall. Gumbel frequency analysis and intensity-duration-frequency relationships generated 50-year design storms for historical and near-, mid-, and far-future periods, with the mid-future period selected as the critical period for both SSP1-2.6 and SSP5-8.5. HEC-HMS 4.13 and 2D HEC-RAS 6.6 generated flood hazard maps, achieving an accuracy of 0.92 and bias score of 0.99 during calibration against the May 2016 flood, and 0.83 and 1.42 during validation against the November 2025 flood. Simulated inundated area was 41.72 km² historically, rising to 51.26 km² (+22.86%) under SSP1-2.6 and 46.00 km² (+10.25%) under SSP5-8.5. Six flood-prone GN divisions in Pannala and Divulapitiya were identified, and 40 households within mapped inundation zones were purposively surveyed, giving a 97.6% response rate. Following exposure to the hazard maps, 87.5% of respondents reported improved understanding of flood risk, 85% reported increased concern about future flooding, and 97.5% expressed willingness to adopt adaptation measures. These findings highlight the potential value of integrating climate-informed hydrological and hydrodynamic modelling with participatory risk communication to improve risk awareness and support adaptive flood-risk management in the MORB.