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Clark, Martyn P ¹

¹ NCAR

Water is a precious commodity underpinning not only the global economy, but also our quality of life. Those responsible for managing the availability and distribution of this basic necessity face a variety of challenges every year in ensuring a high-quality, always-ready resource to meet public and private demands, and to manage highly changeable flood risks and drought responses. Recognizing that climate change is exacerbating these challenges, and to help managers better plan for and respond to climate change effects on water resources, two of the major water management agencies in the USA – the Bureau of Reclamation and the U.S. Army Corps of Engineers – are collaborating with the National Center for Atmospheric Research to improve our understanding of water resource-related climate effects.

This presentation will summarize new applied research to support improved use of hydroclimate information in water resources planning and management. The climate change element of the research addresses the question: “How does the portrayal of climate change impacts depend on the selection of downscaling methods and the selection and configuration of hydrologic models?” This comprehensive analysis of methodological shortcomings provides the user community with guidance on appropriate methods for climate impact assessments. The project helps identify limitations of the current generation of statistical downscaling methods and hydrologic modeling applications and articulate key research needs to improve assessments of climate change impacts on water resources Ongoing research on developing new downscaling methods and new hydrologic modeling approaches targets improving the characterization of uncertainty in climate change assessments.

The streamflow prediction element of this effort is based on a comprehensive predictability assessment to quantify and document the major sources of skill and uncertainty in hydrologic prediction products. The design of the project centers on quantifying the impact of different sources of uncertainty on different types of forecasts (e.g., daily to weekly flow forecasts, 3 month volume forecasts), at different forecast initialization times throughout the year (e.g., forecasts initialized on October 1st versus April 1st), and in different hydroclimate regions (e.g., regions with/without substantial snow storage; regions with varying degrees of climate predictability). The project poses the question: “What are the sources of skill and uncertainty in watershed-scale streamflow predictions and how do these vary seasonally and geographically?” The idealized predictability assessment lays the groundwork for ongoing research: using state of the art weather and climate predictions and an assessment of actual forecast skill to untangle and quantify current actual levels of uncertainty in weather and climate forecasts and initial conditions, and to target the most beneficial areas for efforts to reduce uncertainty.