distribution reflecting uncertainty. This assumption is not supported by sufficient scientific evidence. Other kinds of scientific outputs (e.g., sets of plausible scenarios; models that could simulate the implications of forecasts) might more closely fill the needs of some decision makers in the water management sector. Building knowledge-action networks, as the draft SAP recommends, is advisable in part as a way to learn what would be useful. Also, Chapter 3 presents a serial flow chart as a model of innovation. We urge the authors to consider a continuous improvement model that is circular in nature.
Other important issues needing attention
In terms of coverage, the draft explicitly addresses all but two of the questions raised in the prospectus. Some are addressed in more than one place, when issues are raised in particular chapters. However, we note that Chapter 3, which addresses innovation and offers useful insights, does not draw on the research literature on innovation processes. Incorporating concepts from this literature may help to better conceptualize the operational insights and their implications and strengthen the evidentiary base for findings. Chapter 4 includes discussions of climate change issues, although the focus of the report is mainly on climate variability, which can pose different issues for modeling and for decision support. The document should clarify what it does and does not cover, distinguish clearly between discussions of climate change and of variability, and better justify the inclusion of material on climate change if the authors wish to include it. Responses to questions in the prospectus related to communication of forecasts, operationalization of tools, and evaluation should be elaborated. The discussion of evaluation, a major area of interest for the policy maker audience, is quite limited. If this is due to a lack of published materials, this should be stated.
In terms of the adequacy of evidentiary support for findings and recommendations, we note that very little evidence and analysis are available regarding decision-support efforts in the water sector, with the implications that findings must be based on the relatively weak grounding provided by case study evidence and that recommendations must be based largely on judgment. These points could be made more explicitly in the document.
Although the research priorities and general recommendations are all reasonable and generally supported by argumentation, they are stated in vague language that is hard to contradict and that does not offer clear guidance about the relative importance of different objectives or activities. The arguments raised in the document allow for persuasive arguments to be made for giving some of these ideas higher priority than others and for making some of the recommendations more pointed. For example, the recommendations for improving forecast skill could target areas ripe for improvement, such as realistic land-atmosphere interaction and cryospheric processes. The recommendation to support dense hydrologic monitoring networks is far stronger than the supporting text, which may need to be strengthened in support of this recommendation.
Chapter 2 claims several potential benefits for knowledge-action networks without providing the sources of research or illustrative examples to substantiate each claim. It should make a stronger case for wealth as a key variable affecting the use or nonuse of climate forecasts, or else revise this claim. It presents a relatively strong discussion of knowledge about “science citizenship” but does not clearly link it to the idea of using climate information in decisions. In Chapter 4, some of the key findings seem to depend on an analysis of lessons