Assessing the effects of using high-quality data and high-resolution models in valuing flood protection services of mangroves

• Published in: PloS one Vol. 14; no. 8; p. e0220941
• Main Authors: Menéndez, Pelayo, Losada, Iñigo J, Torres-Ortega, Saúl, Toimil, Alexandra, Beck, Michael W
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 20.08.2019; Public Library of Science (PLoS)
• Subjects: Biology and Life Sciences; Climate Change; Computer and Information Sciences; Conservation of Natural Resources - methods; Cyclonic Storms - statistics & numerical data; Data Accuracy; Databases, Factual - statistics & numerical data; Datasets as Topic; Decision making; Earth Sciences; Ecology and Environmental Sciences; Environmental aspects; Flood control; Floodplain management; Floods - prevention & control; Influence; Mangroves (Plants); Methods; Models, Statistical; Philippines; Research and Analysis Methods; Risk Assessment; Wetlands; Philippines
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0220941

The rate of change on coastlines is accelerating from climate change and coastal development. Coastal flooding is a particularly pressing and increasing problem, which affects hundreds of millions of people and damages trillions of US$ in property. Scientists, practitioners and managers must be able to quickly assess flood risk and identify appropriate adaptation and risk reduction measures often with limited data and tools, particularly in developing countries. To inform these decision-making processes, we identify how sensitive flood risk and adaptation analyses are to changes in the resolution of data and models. We further do these comparisons in the context of assess the benefits of an ecosystem-based approach for risk reduction. There is growing interest in these ecosystem-based approaches as cost effective measures for adaptation and risk reduction. We assess flood risks from tropical cyclones and the flood risk reduction benefits provided by mangroves in Pagbilao (the Philippines). Then, we also compare risks and risk reduction (benefits) using different quality data and models, to identify where to invest in in new modeling and data acquisition to improve decision-making. We find that coastal flood risk valuation improves by using high resolution topography and long time series of data on tropical cyclones, while flood reduction benefits of mangroves are better valued by using consistent databases and models along the whole process rather than investing in single measures.