Valuing the risk reduction of coastal ecosystems in data poor environments: an application in Quintana Roo, Mexico

Coastal risks are increasing from both economic growth and climate change. Understanding such risks is critical to assessing adaptation needs and finding cost effective solutions for coastal sustainability. Interest is growing in the role that nature-based measures can play in adapting to climate change. Here we apply and advance a framework to value the risk reduction potential of coastal ecosystems, with an application in a large scale domain, the coast of Quintana Roo, México, relevant for coastal policy and management, but with limited data. We build from simple to use open-source tools. We first assess the hazards using stochastic simulation of historical tropical storms and inferring two scenarios of future climate change for the next 20 years, which include the effect of sea level rise and changes in frequency and intensity of storms. For each storm, we obtain wave and surge fields using parametrical models, corrected with pre-computed static wind surge numerical simulations. We then assess losses on capital stock and hotels and calculate total people flooded, after accounting for the effect of coastal ecosystems in reducing coastal hazards. We inferred the location of major barrier reefs and dune systems using available satellite imagery, and sections of bathymetry and elevation data. We also digitalized the surface of beaches and location of coastal structures from satellite imagery. In a poor data environment, where there is not bathymetry data for the whole of the region, we inferred representative coastal profiles of coral reef and dune sections and validated at available sections with measured data. Because we account for the effect of reefs, dunes and mangroves in coastal profiles every 200 m of shoreline, we are able to estimate the value of such ecosystems by comparing with benchmark simulations when we take them out of the propagation and flood model. Although limited in accuracy in comparison to more complex modeling, this approach is able to provide quantitative relative comparisons of the values of ecosystems for reducing climate risk. It also gives us quantitative and monetary values of assets protected by ecosystems under different event frequencies (Figure), and very importantly, enables us to explore the effects of future scenarios of degradation, restoration or development in a robust way.