The review and case studies provide a number of practical lessons on the application of these tools to adaptation. They provide useful information on the range of adaptation problem types where the various approaches might be appropriate, as well as data needs, resource requirements and good practice.

It is important to stress that the different tools use various metrics, approaches and assumptions, and have potentially different applicability. No one method is right or wrong – different methods may be more or less appropriate according to the adaptation problem and objectives. Furthermore, the methods and tools are not mutually exclusive, and there are several examples where combinations of tools have been used, or where one tool has been used to scope out promising adaptation options from a long-list, which is then subject to detailed appraisal using one of the more complex methods.

Information from the review is summarised in Tables 3 and 4 below. Note that the grading of the resources and expertise required to use these tools are presented in relative terms. Depending on the size or type of adaptation, and the location in the project cycle (from scoping options to detailed implementation analysis) the resources spent on decision analysis may be relatively easy to justify in terms of avoiding misallocation and mal-adaptation.

A number of issues are relevant in considering the applicability to different adaptation problem types.

First, the choice of tools depends on the availability of benefits information. As shown below, MCA and AHP have the flexibility to work with qualitative or quantitative information (and even economic data), while other techniques require quantitative data. CBA and ROA work exclusively with economic data only. The availability of data (or the potential for providing monetary estimates of benefits) may therefore constrain the approach, or affect the application to sectors where valuation is challenging.

This also provides relevant information for the sequencing or complementarity of tools. It may be appropriate to use more qualitative scoping tools, such as MCA, early on in the process to identify promising options, followed by more detailed (economic) appraisal tools to look indetail at a smaller number of options, i.e. as one moves towards implementation.



Similarly, it may be possible to complement some of the more formal economic approaches (such as CBA) with tools that allow the consideration of qualitative information or issues that difficult to quantify (e.g. environmental or social, equity, acceptability).

Second, the nature of the climate information available may also affect the applicability of the tools. Again, tools such as MCA and AHP can work with very general climate (risk) information, whereas quantitative focused tools need more detailed model outputs to allow quantification of benefits. Tools such as RDM (and IAM) are more suitable where there is deep uncertainty (or high climate uncertainty), as compared to tools such as ROA or PA which require probabilistic climateinformation (or probabilistic like assumptions).