ARTÍCULO
TITULO

Using Historical Responses to Shoreline Change on Australia?s Gold Coast to Estimate Costs of Coastal Adaptation to Sea Level Rise

Daniel Ware    
Andrew Buckwell    
Rodger Tomlinson    
Kerrie Foxwell-Norton and Neil Lazarow    

Resumen

Climate change impacts, sea level rise, and changes to the frequency and intensity of storms, in particular, are projected to increase the coastal land and assets exposed to coastal erosion. The selection of appropriate adaptation strategies requires an understanding of the costs and how such costs will vary by the magnitude and timing of climate change impacts. By drawing comparisons between past events and climate change projections, it is possible to use experience of the way societies have responded to changes to coastal erosion to inform the costs and selection of adaptation strategies at the coastal settlement scale. The experience of implementing a coastal protection strategy for the Gold Coast?s southern beaches between 1964 and 1999 is compiled into a database of the timing, units, and cost of coastal protection works. Records of the change to shoreline position and characteristics of local beaches are analysed through the Bruun model to determine the implied sea level rise at the time each of the projects was completed. Finally, an economic model updates the project costs for the point in the future based on the projected timing of sea level rise and calculates a net present value (NPV) for implementing a protection strategy, per km, of sandy beach shoreline against each of the four representative concentration pathways (RCP) of the Intergovernmental Panel on Climate Change (IPCC) to 2100. A key finding of our study is the significant step-up in expected costs of implementing coastal protection between RCP 2.6 and RCP 8.5?from $573,792/km to $1.7 million/km, or a factor of nearly 3, using a social discount rate of 3%. This step-up is by a factor of more than 6 at a social discount rate of 1%. This step-up in projected costs should be of particular interest to agencies responsible for funding and building coastal defences.

 Artículos similares

       
 
Xiaojuan Wang and Weilan Wang    
As there is a lack of public mark samples of Tibetan historical document image characters at present, this paper proposes an unsupervised Tibetan historical document character recognition method based on deep learning (UD-CNN). Firstly, using the Tibetan... ver más
Revista: Applied Sciences

 
Rafiu Oyelakin, Wenyu Yang and Peter Krebs    
Fitting probability distribution functions to observed data is the standard way to compute future design floods, but may not accurately reflect the projected future pattern of extreme events related to climate change. In applying the latest coupled model... ver más
Revista: Water

 
Syed Safdar Hussain and Syed Sajjad Haider Zaidi    
This study introduces a novel predictive methodology for diagnosing and predicting gear problems in DC motors. Leveraging AdaBoost with weak classifiers and regressors, the diagnostic aspect categorizes the machine?s current operational state by analyzin... ver más
Revista: Applied Sciences

 
Ye Xiao, Yupeng Hu, Jizhao Liu, Yi Xiao and Qianzhen Liu    
Ship trajectory prediction is essential for ensuring safe route planning and to have advanced warning of the dangers at sea. With the development of deep learning, most of the current research has explored advanced prediction methods based on historical ... ver más

 
Pengfei Ning, Dianjun Zhang, Xuefeng Zhang, Jianhui Zhang, Yulong Liu, Xiaoyi Jiang and Yansheng Zhang    
The Array for Real-time Geostrophic Oceanography (Argo) program provides valuable data for maritime research and rescue operations. This paper is based on Argo historical and satellite observations, and inverted sea surface and submarine drift trajectori... ver más