Demonstration of climate change adaptation planning
Visualisation of robustness of adaptation strategies
What do these graphs show?
The graphs illustrate a novel decision support methodology for climate change adaptation decisions called Strategy Robustness Visualisation Method (SRVM), which is tested in two demonstration cases with stakeholders. It visualises the robustness of adaptation strategies to support the decision-makers in evaluating different decision alternatives. The methodology combines modelling information created during the project with previous research and expert opinion. It is based on Multi-Criteria Decision Analysis and Robust Decision-Making methodologies, and a novel approach to scenario analysis. The role of the stakeholders is emphasised in the methodology.
Two demonstrated cases are "Energy production in Northern Europe" and "Nuclear Energy Production in France".
The goal of the demonstration cases are to 1) demonstrate the developed Strategy Robustness Visualisation Method (SRVM) and test it, 2) to bring the important climate change adaptation issues under discussion and support the case theme related decision-making and 3) to demonstrate the relevance of the modelling results in a simulated real life decision environment, where results relate to impact levels and stakeholder preferences of adaptation options.
Based on the results and the feedback obtained in the demonstration to date, it can be said that the SRVM could be useful in supporting complex adaptation decisions. Feedback from the test sessions with researchers and stakeholders was mainly positive.
What can we do with the results of this method?
The method can be used to support climate adaptation related decision-making in a local level situation (e.g. urban planning, city adaptation). It can be used to evaluate the robustness of alternative adaptation strategies and to show the key trade-offs between the strategies to decision-makers. We argue that robustness is a key criterion for use in comparing adaptation strategies and there is a need for methods for assessing it. We believe that the developed method is at least a complimentary decision support method for the decision-makers that are willing to take adaptation to the long-term future into account. The method enables a combination of adaptation and mitigation, and short, medium and long-term perspectives using different decision criteria and scenarios.
As the decision context changes (partly due to the fact that scenarios get updated due to new information), the strategies need reviewing. Especially the implemented strategies should be reviewed for checking the need for rescaling, modification, but also if novel adaptation strategies must be thought of.
How are the results obtained?
The main inputs for the method are the modelling results created by the ToPDAd consortium for the demonstration cases and the expert opinion about the performance of the strategies from the researchers and stakeholders. Also, the detailed scenarios are developed on the basis of the work of ToPDAd consortium and further developed by the researchers in co-operation with energy sector stakeholders. The expert opinion was elicited in a stakeholder workshop for the "Energy Production in Northern Europe" case and by interviews in the "Nuclear Energy Production in France" case.
As an output of the modelling and expert opinion sessions, probability distributions were calculated. The main assumption of the developed method is that the optimistic and pessimistic scenarios are enough to represent the whole range of performance due to the uncertainties involved in the scenario selection. The highest and lowest values (either lowest or highest values given by the stakeholders or 95 % confidence intervals produced by the modelling) were selected for the visualisation.
What are the broader applications?
The method is developed to support climate change adaptation related decision-making. However, it could also be used in other complex decision situations involving long timeframes, such as general investment decisions on infrastructure. The approach can be used instead or as a complement to other decision support approaches such as cost-benefit analysis (CBA).
The method allows the decision-makers to take deep uncertainties into account in related decision-making and emphasises the input of several different stakeholders and a novel approach to scenario analysis. The selection of stakeholder groups, distribution of stakeholders and their minimal amount per exercise should be decided case by case. The limitations of the method include a considerable time needed for the preparatory phase and the need of active stakeholder participation.
Jyri Hanski (VTT)
Strategy Robustness Visualisation Method (SRVM)
The Strategy Robustness Visualisation Method (SRVM) supports adaptation decisions where not only monetary decision criteria are sufficient. The methodology combines multi-criteria approach and robust decision-making. Its goal is to visualise the robustness of adaptation strategies and help to create better strategies by finding out the key trade-offs among them.
The SRVM methodology supports the development of robust strategies
The visualization of the performance of a strategy is based on radar plots. The performance is depicted with radar plots with as many axes as the number of criteria. The performance of a single strategy is shown under all the scenario combinations studied in one plot. The uncertainty is shown by plotting two similar-colour lines; one that links the min-values, and the other linking the max-values of the Key Performance Indicators under a given scenario. For each scenario such line pairs are plotted on the same radar plot, with different colour per scenario. Visually, robustness is shown by several line-pairs which are close to each other for all scenarios. The ‘closeness' is a sign of insensitivity of the strategy to the scenarios; low-regret strategy.
Visualisation of the robustness of the adaptation strategy "No planned adaptation" for the "Energy production in Northern Europe" demonstration case. Results are for the year 2050 and relative to the baseline.
Visualisation of the robustness of the adaptation strategy "Electricity storage" for the "Energy production in Northern Europe" demonstration case. Results are for the year 2050 and relative to the baseline.
Visualisation of the robustness of the adaptation strategy "Smart grid infrastructure" for the "Nuclear energy production in France" demonstration case. Results are for the year 2100 and relative to the baseline.
Visualisation of the robustness of the adaptation strategy "No planned or automatic adaptation" for the "Nuclear energy production in France" demonstration case. Results are for the year 2100 and relative to the baseline.