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

大洪水 沿海洪水 背景(考古学) 气候变化 环境资源管理 洪水(心理学) 生态系统服务 红树林 环境科学 估价(财务) 风险分析(工程) 业务 地理 生态系统 生态学 生物 心理学 考古 心理治疗师 海平面上升 财务
作者
Pelayo Menéndez,Íñigo J. Losada,Saúl Torres-Ortega,Alexandra Toimil,Michael W. Beck
出处
期刊:PLOS ONE [Public Library of Science]
卷期号:14 (8): e0220941-e0220941 被引量:11
标识
DOI:10.1371/journal.pone.0220941
摘要

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.

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