AMP Toolbox
COAST model
Steps
As mentioned in the case of the BCA Tool Kit, the benefit-cost analysis can be implemented through a COAST model, either utilising the ex ante or ex post approaches. Specifically, the ex ante analysis can be conducted during Step 2: Assembling a basic policy or Step 3: Making the policy robust, while the ex post analysis can also be undertaken in Step 5: Evaluation and policy adjustments.
Purpose
The COAST (COastal Adaptation to Sea level rise Tool) is a tool which predicts the damages from sea level rise and/or coastal flooding for different intensities of the examined phenomena and evaluates the relative benefits and costs of the proposed adaptation strategies. The main target of the COAST tool is the provision of technical information to the stakeholders involved regarding the triggered social, political, and economic impacts from the planned adaptation measures in local scale (on the local level).
Overview
The COAST tool enables the stakeholders to plan and evaluate potential adaptation actions and measures through the visualisation of the flooded areas and the estimation of the monetary effects of that flooding. The simplicity and the flexibility of this tool can be considered as significant assets, while the potential decision maker can implement BCA and easily compare alternative scenarios. The tool requires specific data for the assessment of the policy options to be examined and in combination with spatial data and model parameters calculates the expected damages annually for a defined time period, taking into consideration the likelihood of sea level rise and/or coastal flooding. The first output of the tool is an Excel spreadsheet, which presents cumulatively the calculated damages for each examined SLR scenario (including the no sea-level rise scenario) and the impacts of the various adaptation measures undertaken by the stakeholders and policy makers. Furthermore, the tool provides a map, which contains a graphical presentation of the damages and the monetary effects triggered by each specific scenario. Different criteria can be utilised so as to define and calculate the damages and effects on the local population.
Tips
Various issues should be considered before conducting a cost-benefit analysis with COAST. Specifically, it is crucial to:
As mentioned in the case of the BCA Tool Kit, the benefit-cost analysis can be implemented through a COAST model, either utilising the ex ante or ex post approaches. Specifically, the ex ante analysis can be conducted during Step 2: Assembling a basic policy or Step 3: Making the policy robust, while the ex post analysis can also be undertaken in Step 5: Evaluation and policy adjustments.
Purpose
The COAST (COastal Adaptation to Sea level rise Tool) is a tool which predicts the damages from sea level rise and/or coastal flooding for different intensities of the examined phenomena and evaluates the relative benefits and costs of the proposed adaptation strategies. The main target of the COAST tool is the provision of technical information to the stakeholders involved regarding the triggered social, political, and economic impacts from the planned adaptation measures in local scale (on the local level).
Overview
The COAST tool enables the stakeholders to plan and evaluate potential adaptation actions and measures through the visualisation of the flooded areas and the estimation of the monetary effects of that flooding. The simplicity and the flexibility of this tool can be considered as significant assets, while the potential decision maker can implement BCA and easily compare alternative scenarios. The tool requires specific data for the assessment of the policy options to be examined and in combination with spatial data and model parameters calculates the expected damages annually for a defined time period, taking into consideration the likelihood of sea level rise and/or coastal flooding. The first output of the tool is an Excel spreadsheet, which presents cumulatively the calculated damages for each examined SLR scenario (including the no sea-level rise scenario) and the impacts of the various adaptation measures undertaken by the stakeholders and policy makers. Furthermore, the tool provides a map, which contains a graphical presentation of the damages and the monetary effects triggered by each specific scenario. Different criteria can be utilised so as to define and calculate the damages and effects on the local population.
Tips
Various issues should be considered before conducting a cost-benefit analysis with COAST. Specifically, it is crucial to:
- Sefine clearly the scenario with and without the project
- Choose an appropriate time horizon
- Choose an appropriate discount rate
- Specify the appropriate unitary cost estimates
- Discuss uncertainties through sensitivity analysis of the main parameters
- Report the results in non-technical terms and always insist on their relativity in relation to the assumptions made.
Indicatively, a map with the calculated estimates, as produced by the COAST tool, is presented in the following image.
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Image 1: Presentation of results from COAST tool.
Pedigree
The COAST tool was developed by the University of Southern Maine with the foundation of US EPA and in collaboration with partners at Battelle, the Maine Geologic Survey, the University of New Hampshire and Blue Marble Geographics. The COAST tool is built on the Global Mapper software developer toolkit and promoted in partnership with Catalysis Adaptation Partners.
Synergy
The outputs of COAST tool are compatible with Google Earth and the tables of the Excel spreadsheet depict the cumulative expected damages and effects for the examined scenarios and allow a cost-benefit analysis of various adaptation actions.
Usage
Moderate - high. The COAST tool can be considered as user friendly, but it requires a specific amount of data, which must be prepared and adapted to the local environment, in order to calculate the costs and benefits precisely.
Cost
The COAST tool performs cost-benefit analysis for multiple climate change and adaptation scenarios for different time periods. As a result, the costs of the data, which must be collected and prepared, depend on the number of scenarios examined.
The COAST model requires three categories of data:
1. spatial data representing land elevation and assets to be modelled
2. model scenarios that are tied specifically to the spatial data
3. model parameters which are vital to run the model, but are not tied to specific data layers. These parameters include the specification of the exceedance curves, the base water level and the adaptation strategy.
The spatial data must comply with specific requirements. If the data do not meet these requirements an external tool such as the Global Mapper can be utilised for their appropriate modification.
Capacity
Moderate. The tool requires basic knowledge of economic theory as well as knowledge of similar empirical applications. Furthermore, as mentioned, a certain amount of data preparation specific to the local environment is crucial to effectively conduct the cost-benefit analysis.
Background requirements
Moderate. The tool needs the completion of specific data to conduct the cost-benefit analysis. Nevertheless, default values are provided from existing lists.
Participation
High. The tool helps stakeholders visualise the results of alternative policies. The stakeholders have the opportunity to combine multiple future scenarios and to assess the damages and effects of the examined adaptation actions in comparison with the no-action scenarios.
Time range
Medium. Time is required for the collection of the necessary data in order to complete the analysis. Once data are collected, the calculations are performed rather quickly.
Source of information
Coast in Action - 2012 projects from Maine and New Hampshire, 2012. Report prepared for for US EPA’s Climate Ready Estuaries Program in collaboration with Casco Bay Estuary Partnership and Piscataqua Region Estuaries Partnership by the New England Environmental Finance Center, Edmund S. Muskie School of Public Service, University of Southern Maine with support of the University of New Hampshire.