Population and Assets Exposure to Coastal Flooding in Dar es Salaam (Tanzania): Vulnerability to Climate Extremes

Abstract

The objective of this case study analysis was to provide a more broader quantitative estimate of the potential number of people and associated economic assets in the coastal zone of Dar es Salaam (Tanzania), which could be exposed to coastal flooding due to extreme water levels through the 21st century. The assessment was performed using an elevation-based geographic information systems (GIS)-analysis based on physical exposure and socio-economic vulnerability under a range of sealevel rise and socio-economic scenarios. The study particularly considered a worst-case scenario assuming that even if defences (natural and/or artificial) exist, they are subjected to failure under the most extreme events. As such, it provides a first detailed quantitative context of the potential exposure, and hence worst-case impacts due to extreme sea levels under a range of possible futures. These could be used to assist coastal planners and policy makers for a better practice of decisionmaking under conditions of deep uncertainity in terms of planning for sustainable future development. The results show that about 8% of Dar es Salaam lies within the low elevation coastal zone, “LECZ” (i.e., below the 10m contour lines). This area was estimated to be inhabited by more than 143,000 people (i.e., about 5.3% of the total city population) and associated economic asset estimated to be worth at least US$168 million in 2005, of which over 30,000 people and US$35 million assets are located within the 1 in 100 year flood plain. By 2030 with no climate-induced sea-level rise, the exposure to a 1 in 100 year coastal flood event is estimated at 60,000 people and US$219 million assets (under the population growth distribution (PGD) scenario 2), and 106,000 people and US$388 million assets (under the PGD scenario 1). Under the PGD scenario 3 assuming potential future population and economic growth occur outside the city boundaries, the exposure is significantly reduced (i.e., about 30,000 people and US$35 million assets by 2030). When sea-level rise is considered, a total number of people ranging between 61,000 and 64,000 people (under the PGD scenario 2), and between 107,000 and 110,000 people (under the PGD scenario 1) across the sea-level rise scenarios are estimated to be potentially exposed to coastal flooding by 2030. Similarly, considering the sea-level rise scnearios the exposed assets are estimated between US$223 and US$236 million (under the PGD scenario 2) and between US$392 and US$404 million (under the PGD scenario 1). The exposure increases significantly with time, reaching over 210,000 people and about US$10 billion assets by 2070 under the highest sea-level rise scenario and the PGD scenario 1. These results highlight that socio-economic changes in terms of rapid population growth, urbanisation, and spatial population distribution and associated economic growth are higher than sealevel rise changes, and this will potentially play a significant role in the overall increase of population and assets exposure to coastal flooding in Dar es Salaam. This is illustrated by the population growth distribution scenarios 1 and 2, which are consistent with observed trends of the city growth and demonstrate that exposure will increase substantially from now to 2070 even if there is no change in extreme water levels. Note that these estimates do not include the actual value of ports and harbours or tourist infrastructure which are not within the scope of this analysis. Moreover, the population growth distribution scenario 1 illustrates that steering development away from low-lying areas that are not threatened (or are less vulnerable) by sea-level rise and extreme climates could be an important part of a strategic response to significantly reduce the future growth in exposure. However, enforcement of such a policy where informal settlements dominate urbanisation (as in many developing countries), will undoubtedly be a major issue. In addition, appropriate adaptation measures (e.g., protection in terms of beach/shore nourishment and dikes) could also be considered in order to keep risks at an acceptable level, but this will require appropriate capital investment and subsequent maintenance. Lastly, it should be recognised that this analysis only provides indicative results. Limitations of the analysis include lack of sufficient and good quality observational local climate data (e.g., long-term sea-level measurements), finer resolution spatial population and asset distribution and high resolution local elevation data, and detailed information about existing coastal defence systems (natural and/or artificial) and current protection levels. As such it should be seen as a first step towards analysing these issues, and needs to be followed by more detailed, city-based analysis.