Assessing the consequences of sea-level rise in the coastal zone of Quintana Roo, México: the costs of inaction

Abstract

The Mexican State of Quintana Roo, located in the Caribbean, is an area of high environmental and socio-economic value. Its low elevation and long coastline render the State physically and economically highly vulnerable to accelerated sea-level rise. The purpose of this study is to undertake an initial assessment of the potential land loss and costs that might eventuate by flooding due to sea-level rise (SLR). Given the spread of impacts caused by SLR, a variety of measures are presented to capture these diverse effects. A three pronged approach is adopted which combines areas affected by SLR with impacts identified in the population, the economy, and the environmental systems. Tourism is the primary source of income and growth in the state of Quintana Roo, consequently the economic impact of SLR is measured through the affect on different sectors of the economy which is exclusively conducted in the coastal zone, while the environmental impact is approximated by the estimated loss of mangroves, and the impact on population is proxied by means of the number of people that could be directly affected by flooding. Based on current estimates of SLR, we utilise a minimum inundation level of 1 m and a maximum inundation level of 5 m. The inundation analysis is based on results from a Geographical Information System that identifies locations and the socioeconomic sectors that are most at risk from accelerated sea-level rise. Given the uncertainty of projected future development paths, conservative but plausible assumptions are used to provide a variety of estimates of the costs of SLR. Our results show that, for the most conservative scenario to 2100, at least 27 % of mangroves in the State would be lost with an upper bound of 94 % (with an associated economic loss of $405.325 million), over one million people would be flooded, and impacts on the economy would imply large losses over $400 million. Less conservative, more likely scenarios depict a greater, non-linear impact. These provide first order estimates of the costs and consequences of inaction and the importance of preventive measures.