Impacts from sea-level rise are among the most crucial impacts of climate change. Global sea levels have been rising in the past century, and will almost certainly accelerate through the 21st century and beyond due to global warming (Nicholls, 2010).
The mean rate of sea-level rise from 1993 to 2009 measured by satellites has been 3.3 +/-0.4 mm per year (Ablain et al., 2009). The estimates for future sea level rises by 2100 diverge, yet have generally increased in projected rises since the publication of the Fourth Assessment Report of the IPCC in 2007. Such newer estimates now range from approx. 30 to approx. 200cm, depending on the assumed future developments that in turn drive climate change.
Regional processes such as sediment accumulation or drainage and groundwater withdrawal can respectively offset or exacerbate these rates.
The main impact of sea-level rise is submergence of land, i.e. "land loss", and increased flooding in coastal areas. Such direct biophysical impacts can cause a variety of socioeconomic impacts, which are considered to be overwhelmingly negative (Nicholls, 2007). This map focuses on potential agricultural production losses due to submergence of land.
Sugarcane is one of the most important crops for Brazil and plays a central role in the food supply of the local population. The map shows the sugarcane production loss, which would be affected by a theoretical global mean sea-level rise of one meter.
The map displays a scenario for existing conditions. i.e. it is assumed that no adaptation measures to protect land from future sea-level rise will be made during the time it takes to reach an 2m sea-level rise. Furthermore, no current protective coastal infrastructures already in place are considered, such as dikes. The information presented in the map also embodies uncertainty within itself.
Note:
The data that is mapped is calculated through preprocessing, intersecting, and aggregating elevation data, harvest area data, and yield data from the datasets indicated below. The methodology of deriving "Harvested Area and Yields of 175 crops (M3-Crops Data)" is described in Monfreda et al. (2008). The common areas of the polygons emerging from the intersection were recalculated and multiplied by the ratio of sugarcane area harvested per grid cell of the area harvested data. Results of harvest area (total, and 2m above sea level and below) were aggregated to administration unit level 2 (i.e. 2 levels below country level), followed by the calculation of the ratio of harvest area 1m above sea level and below to the total harvest area.