Climate change has the potential to disrupt water resource systems by changing the timing, amounts, and quality of water supplies, and by changing flood and drought characteristics, consumptive and transmission losses, and water demands from their historical norms in as-yet unpredictable ways. Many agencies are mobilizing to assess water-resource vulnerabilities and to incorporate climate change in planning and decision making. These efforts, however, are uncovering a number of difficult methodological and computational challenges, including needs to:

- Identify key and most credible climatic changes in climate projections and then project those changes down to hydrologically relevant scales for resource modeling and other uses (credible projection and downscaling)

- Recognize, evaluate and diagnose problems with climate and hydrological model simulation through detailed spatio-temporal comparisons of observations and simulations (detection, performance evaluation and problem diagnosis)

- Recognize and distinguish between natural and human-induced hydrologically relevant hydroclimatic changes through detailed comparisons of observations and simulations (detection and attribution)

- Improve the observational basis and modeling representations of relevant climatic influences in water-resources models and computations (observations and climatic linkages)

- Model and incorporate climate-change probabilities and risks for decision making (probabilistic methods)

- Sort through and distinguish between differing management responses (feasibility and optimization methods)

These challenges are often aggravated by the large dimensions of data fields, models, and feasibility spaces, and the limited numbers of available projections, process models, observations, and relevant historical examples. This session solicits research contributions that address these needs through theoretical advances and practical applications. We encourage presentation of examples of innovative solutions for real-world water-resource systems with prospects for widespread applicability.