[1] There are few methodologies for the use of climate change projections in decision making or risk assessment processes. In this paper we present an approach for climate risk assessment that links bottom-up vulnerability assessment with multiple sources of climate information. The three step process begins with modeling of the decision and identification of thresholds. Through stochastic analysis and the creation of a climate response function, climate states associated with risk are specified. Climate information such as available from multi-GCM, multirun ensembles, is tailored to estimate probabilities associated with these climate states. The process is designed to maximize the utility of climate information in the decision process and to allow the use of many climate projections to produce best estimates of future climate risks. It couples the benefits of stochastic assessment of risks with the potential insight from climate projections. The method is an attempt to make the best use of uncertain but potentially useful climate information. An example application to an urban water supply system is presented to illustrate the process.

Despite the economic stimulus provided by many dams historically, the global experience with dam building warns that traditional approaches to water infrastructure development in a rapidly changing world carry severe risks of economic and environmental failure. First, large water projects are very capital-intensive and long-lived, costing billions of dollars to plan, build, and maintain. Yet, they are vulnerable to biased economic analyses 3 , cost overruns and construction delays, and changing environmental, economic and social conditions that can diminish projected benefits 4,5 . Under a variable and changing climate, large water infrastructure even risk becoming stranded assets 6 . Second, the principles of economic efficiency inherent in cost-benefit analysis dominate project design and performance assessment, and integrating social and environmental benefits and costs into a comprehensive economic evaluation presents significant challenges 7,8 .These costs can be substantial, as evidenced by human displacement 5,9 , local species extinctions 10 , and the loss of ecosystem services such as floodplain fisheries and other amenities 11,12 .As unanticipated economic, social and environmental costs accumulate with aging water infrastructure, society is investing in restoration projects to undo some of the long-term environmental degradation, including modifying flow releases from dams 13,14 and in some cases dam removal 15 . As the global impairment of aquatic ecosystem function becomes increasingly documented and articulated 16,17 , a broader conception of sustainable water resources management that formulates environmental health as a necessary ingredient for water security and the social wellbeing it supports is urgently needed [18][19][20] . Notably, new national directives are emerging to develop and manage river ecosystems in less environmentally harmful and more sustainable ways, including in the US 21 , Europe 22,23 , and Australia 24 . Towards a more sustainable water resources management paradigmHere we ask if a more sustainable water management philosophy can be forged to guide investment in, and design of, water infrastructure while avoiding adverse, sometimes irreversible, social and

In this paper, we review the need for, use of, and demands on climate modeling to support so-called 'robust' decision frameworks, in the context of improving the contribution of climate information to effective decision making. Such frameworks seek to identify policy vulnerabilities under deep uncertainty about the future and propose strategies for minimizing regret in the event of broken assumptions. We argue that currently there is a severe underutilization of climate models as tools for supporting decision making, and that this is slowing progress in developing informed adaptation and mitigation responses to climate change. This underutilization stems from two root causes, about which there is a growing body of literature: one, a widespread, but limiting, conception that the usefulness of climate models in planning begins and ends with regional-scale predictions of multidecadal climate change; two, the general failure so far to incorporate learning from the decision and social sciences into climate-related decision support in key sectors. We further argue that addressing these root causes will require expanding the conception of climate models; not simply as prediction machines within 'predict-then-act' decision frameworks, but as scenario generators, sources of insight into complex system behavior, and aids to critical thinking within robust decision frameworks. Such a shift, however, would have implications for how users perceive and use information from climate models and, ultimately, the types of information they will demand from these models-and thus for the types of simulations and numerical experiments that will have the most value for informing decision making.

This paper presents a short history of water resources systems analysis from its beginnings in the Harvard Water Program, through its continuing evolution toward a general field of water resources systems science. Current systems analysis practice is widespread and addresses the most challenging water issues of our times, including water scarcity and drought, climate change, providing water for food and energy production, decision making amid competing objectives, and bringing economic incentives to bear on water use. The emergence of public recognition and concern for the state of water resources provides an opportune moment for the field to reorient to meet the complex, interdependent, interdisciplinary, and global nature of today's water challenges. At present, water resources systems analysis is limited by low scientific and academic visibility relative to its influence in practice and bridled by localized findings that are difficult to generalize. The evident success of water resource systems analysis in practice (which is set out in this paper) needs in future to be strengthened by substantiating the field as the science of water resources that seeks to predict the water resources variables and outcomes that are important to governments, industries, and the public the world over. Doing so promotes the scientific credibility of the field, provides understanding of the state of water resources and furnishes the basis for predicting the impacts of our water choices.

The article advances the hypothesis that the seasonal and inter-annual variability of rainfall is a significant and measurable factor in the economic development of nations.