Rodger Tomlinson

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

Publisher: MDPI AG

Date: 26-05-2020

DOI: 10.3390/JMSE8060380

Abstract: 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.

A relationship to describe the cumulative impact of storm clusters on beach erosion

Publisher: Elsevier BV

Date: 2014

DOI: 10.1016/J.COASTALENG.2013.10.001

Breaking-Down and Parameterising Wave Energy Converter Costs Using the CapEx and Similitude Methods

Publisher: MDPI AG

Date: 09-02-2021

DOI: 10.3390/EN14040902

Abstract: Wave energy converters (WECs) can play a significant role in the transition towards a more renewable-based energy mix as stable and unlimited energy resources. Financial analysis of these projects requires WECs cost and WEC capital expenditure (CapEx) information. However, (i) cost information is often limited due to confidentiality and (ii) the wave energy field lacks flexible methods for cost breakdown and parameterisation, whereas they are needed for rapid and optimised WEC configuration and worldwide site pairing. This study takes advantage of the information provided by Wavepiston to compare different costing methods. The work assesses the Froude-Law-similarities-based “Similitude method” for cost-scaling and introduces the more flexible and generic “CapEx method” ided into three steps: (1) distinguishing WEC’s elements from the wave energy farm (WEF)’s (2) defining the parameters characterising the WECs, WEFs, and site locations and (3) estimating elements that affect WEC and WEF elements’ cost and translate them into factors using the parameters defined in step (2). After validation from Wavepiston manual estimations, the CapEx method showed that the factors could represent up to 30% of the cost. The Similitude method provided slight cost-overestimations compared to the CapEx method for low WEC up-scaling, increasing exponentially with the scaling.

Spatial Bayesian Network for predicting sea level rise induced coastal erosion in a small Pacific Island

Publisher: Elsevier BV

Date: 05-2019

DOI: 10.1016/J.JENVMAN.2019.03.008

Abstract: An integrated approach combining Bayesian Network with GIS was developed for making a probabilistic prediction of sea level rise induced coastal erosion and assessing the implications of adaptation measures. The Bayesian Network integrates extensive qualitative and quantitative information into a single probabilistic model while GIS explicitly deals with spatial data for inputting, storing, analysing and mapping. The integration of the Bayesian Network with GIS using a cell-by-cell comparison technique (aka map algebra) provides a new tool to perform the probabilistic spatial analysis. The spatial Bayesian Network was utilised for predicting coastal erosion scenarios at the case study location of Tanna Island, Vanuatu in the South Pacific. Based on the Bayesian Network model, a rate of the island shoreline change was predicted probabilistically for each shoreline segment, which was transferred into GIS for visualisation purposes. The spatial distribution of shoreline change prediction results for various sea level rise scenarios was mapped. The outcomes of this work support risk-based adaptation planning and will be further developed to enable the incorporation of high resolution coastal process models, thereby supporting localised land use planning decisions.

Estimation of beach erosion using Joint Probability analysis with a morphological model

Publisher: Elsevier BV

Date: 11-2022

DOI: 10.1016/J.OCEANENG.2022.112560

Linkage Projects - Grant ID: LP0347960

Start Date: 2003

End Date: 12-2006

Amount: $276,000.00

Funder: Australian Research Council

Linkage Projects - Grant ID: LP110200832

Start Date: 06-2012

End Date: 09-2017

Amount: $92,000.00

Funder: Australian Research Council

Linkage Infrastructure, Equipment And Facilities - Grant ID: LE170100090

Start Date: 05-2017

End Date: 05-2018

Amount: $600,000.00

Funder: Australian Research Council

Linkage Infrastructure, Equipment And Facilities - Grant ID: LE140100061

Start Date: 2014

End Date: 07-2015

Amount: $1,000,000.00

Funder: Australian Research Council