Nature-based solutions for flood risk reduction : a probabilistic modeling framework

• Main Authors: Lallemant, David, Hamel, Perrine, Balbi, Mariano, Lim, Tian Ning, Schmitt, Rafael, Win, Shelly
• Other Authors: Asian School of the Environment
• Format: Article
• Language: English
• Published: 2022
• Subjects: Science::Geology; Flood Maps; Nature-Based Solutions; Satellite Remote Sensing; Flooding
• Online Access: https://hdl.handle.net/10356/155408
• Institution: Nanyang Technological University

Flooding is the most frequent and damaging natural hazard globally. While nature-based solutions can reduce flood risk, they are not part of mainstream risk management. We develop a probabilistic risk analysis framework to quantify these benefits that (1) accounts for frequent small events and rarer large events, (2) can be applied to large basins and data-scarce contexts, and (3) quantifies economic benefits and reduction in people affected. Measuring benefits in terms of avoided losses enables the integration of nature-based solutions in standard cost-benefit analysis of protective infrastructure. Results for the Chindwin River basin in Myanmar highlight the potential consequences of deforestation on long-term flood risk. We find that loss reduction is driven by small but frequent storms, suggesting that current practice relying on large storms may underestimate the benefits of nature-based solutions. By providing average annual losses, the framework helps mainstream nature-based solutions in infrastructure planning or insurance practice.