Assessing Economic Benefit of Climate Adaptation for Urban Flooding in the Colombo Metropolitan Area, Sri Lanka
Andi Besse Rimba1*, Ichiro Sato1, Naho Yoden2, Akiko Matsumura2, Daiju Narita3 and Daikichi Ogawada2

1 JICA Ogata Research Institute, Japan
2 Nippon Koei Co., Ltd, Japan
3 Graduate School of Arts and Sciences, University of Tokyo, Japan


Abstract

Flooding presents a growing challenge for rapidly urbanizing regions under intensifying climate change. This study assesses the economic benefits of climate adaptation through urban flood control in the Colombo Metropolitan Area, Sri Lanka. Using flood projections derived from five Shared Socioeconomic Pathway scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-6.0 and SSP5-8.5), we integrate hydrodynamic modeling with high&#8209-resolution satellite imagery (10 m and 0.5 m) to map exposure and vulnerability of buildings across the Kalu Oya and Mudun Ela basins. Economic damage is estimated using structure-specific depth-damage functions for four building categories and compared under three protection levels: no measures, partial protection (1/25-year), and full protection (1/50-year). We found that full protection can reduce flood-related economic damage by approximately 40 - 71%, equivalent to avoiding losses of LKR 5 million to 5 billion , depending on the building type and scenario. The most significant benefits from full protection are gained wooden and unreinforced masonry (URM) houses. In contrast, commercial buildings and houses with concrete frames show smaller benefits (approximately 30-50%). Future climate scenarios affect risk, but structural vulnerability and protection level mainly determine how well we can adapt. These findings provide actionable evidence for urban planners and policymakers to prioritize cost&#8209-effective, risk&#8209-informed flood adaptation strategies in rapidly urbanizing coastal metropolitan areas.

Keywords: Shared Socioeconomic Pathways (SSPs), Climate Modeling, Cost-Benefit Analysis, Disaster Risk Reduction, High-Resolution Satellite Imagery

Topic: Topic D: Geospatial Data Integration

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