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Rio de Janeiro, Brazil

Germani Y.F.,Nav Oceanografia Ambiental Ltda | De Figueiredo S.A.,Grande Rio University | Calliari L.J.,Grande Rio University | Tagliani C.R.A.,Grande Rio University
Journal of Integrated Coastal Zone Management | Year: 2015

In the current scenario of global climate change, in which some of the observed effects are: the mean sea level rise, and an increased frequency and intensity of extreme events, coastal regions around the world should in general become more vulnerable. In this context, the Rio Grande do Sul coastline, due to its intrinsic morphodynamic characteristics, such as, a low lying coastal gradient combined with a high degree of exposure to ocean dynamics, places several associated ecosystems, such as beach, dunes, marshes, fields, wetlands and washouts in a vulnerable position to changes in sea level. Model simulations of coastal response to sea level rise for the Rio Grande do Sul pointed out Cassino beach sector as being the most affected with the largest shoreline recession along the entire coast. Aiming for adequate planning of these areas under global climate change scenarios, and in order to determine the possible loss of habitats in case of a rise of mean sea level in the long term (2100), present day shoreline was digitalized at the foredune toe limit using in ArcGis, and coastal environments were initially classified using IDRISI program. In this environment, the percentages for each habitat loss were calculated for three possible coastline scenarios, designed for 2100. It was noticed that all environments would display some lost area, even at the best case scenario. In this scenario where the projected shoreline is located at 561m inland form the present day shoreline with 70% probability of being exceeded by 2100, more than half of the dune area would be lost, followed by a smaller fraction of fields. It can also be observed that in this scenario the urban area had the highest percentage loss. For the intermediate scenario where the projected shoreline is located at 695m inland from the present day shoreline with 50 % probability of being exceeded, dunes represent the largest loss in habitat, sharing space, with surrounding green fields and to a lesser extent, to forests. Yet for the worst case scenario where the projected shoreline is located at 1032m inland from the present day shoreline with10 % probability of being exceeded, there was a reversal in habitat loss with respect to the intermediate scenario. In this scenario, green fields and coastal dunes approached 50 % and 35 % loss in habitat, respectively, representing the largest impacted areas. It should be highlighted that the fresh water creeks, called washouts, in the best case scenario had its entire area lost. However, in the long term they probably should re-establish its course if topography allows. On the one hand, considering any of the simulated scenarios, as the shoreline retreats the salt marsh area would become closer to the foredune areas. On the other hand, even though not simulated here, there is also the possibility that with sea-level rise it could be inundated through the connecting channel to Patos Lagoon resulting in an increased habitat area. Coastal vulnerability was evaluated through the use of Coastal Vulnerability Index (CVI) for the present and future scenarios for 2100. Looking at coastal vulnerability in general, calculated CVI values for the study area were 14.4 and 51.03, designed for the present and for the year 2100, respectively. The results indicate that a region currently characterized as a moderately vulnerable, should become highly vulnerable in the future due to the rising of mean sea level as projected. This change would take place basically influenced by two of the index variables: shoreline erosion/accretion rates; and relative sea-level change, considered here as the controlling variables for coastal vulnerability under climate change in this area. Thus, the information obtained is critical to properly plan, land use and adaptation of this coastal region under the current scenario for global climate change, as well as enable future studies on habitat management.

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