Flood risk analysis using analytic hierarchy process approach and GIS in Tagum City, Philippines

Abstract

Natural disasters are all expected to worsen and happen more frequently because of global warming. Cities containing a large portion of the human population were particularly vulnerable to the effects of climate change. Creating future climate projections can lessen the impact of these adverse occurrences. In this study, rainfall and temperature projections from Coupled Model Intercomparison Project Phase 6 (CMIP6) were used to predict the future climate data of Tagum City. To project precipitation and temperature from 2020 up to 2100, an ensemble of 31 Global Climate Models (GCMs) under two Shared Socioeconomic Pathways (SSPs) (SSP2-4.5 and SSP5-8.5) were utilized. The ACCESS-CM2 model corresponded satisfactorily with the PAGASA weather station's observed rainfall dataset. The resulting flood risk map shows that, in the current scenario, 7.1% of the city’s land area belongs to the ‘very low’ flood risk category, 22.3% belongs to the ‘low’ category, 22% belong to the ‘medium’ category, 37.5% belong to the ‘high’ category, and 11.1% belong to the ‘very high’ category. It also shows that 13 of the 23 barangays belong to the ‘high’ and ‘very high’ flood risk categories for current and future scenarios. These barangays would be the ones to require the most immediate attention from decision-makers to develop strategies for future occurrences of flood within the city of Tagum.