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In this paper we review the published, scientific literature addressing the response of nutrients, sediment, pathogens, and cyanobacterial blooms to historical and potential future changes in air temperature and precipitation. The goal is to document how different attributes of water quality are sensitive to these drivers, to characterize future risk, to inform management responses, and to identify research needs to fill gaps in our understanding. Results suggest that anticipated future changes present a risk of water quality and ecosystem degradation in many United States locations. Understanding responses is, however, complicated by inherent high spatial and temporal variability, interactions with land use and water management, and dependence on uncertain changes in hydrology in response to future climate. Effects on pollutant loading in different watershed settings generally correlate with projected changes in precipitation and runoff. In all regions, increased heavy precipitation events are likely to drive more episodic pollutant loading to water bodies. The risk of algal blooms could increase due to an expanded seasonal window of warm water temperatures and the potential for episodic increases in nutrient loading. Increased air and water temperatures are also likely to affect the survival of waterborne pathogens. Responding to these challenges requires understanding of vulnerabilities, and management strategies to reduce risk. Research Impact Statement: Climate change will have direct and cascading effects on water quality that vary in different regional and watershed settings, and could present a risk to human health and the environment. [ABSTRACT FROM AUTHOR]

Gong, Gavin, Lucien Wang, Laura Condon, Alastair Shearman, and Upmanu Lall, 2010. A Simple Framework for Incorporating Seasonal Streamflow Forecasts Into Existing Water Resource Management Practices. Journal of the American Water Resources Association (JAWRA) 46(3):574-585. DOI: 10.1111/j.1752-1688.2010.00435.x Climate-based streamflow forecasting, coupled with an adaptive reservoir operation policy, can potentially improve decisions by water suppliers and watershed stakeholders. However, water suppliers are often wary of straying too far from their current management practices, and prefer forecasts that can be incorporated into existing system modeling tools. This paper presents a simple framework for utilizing streamflow forecasts that works within an existing management structure. Climate predictors are used to develop seasonal inflow forecasts. These are used to specify operating rules that connect to the probability of future (end of season) reservoir states, rather than to the current storage, as is done now. By considering both current storage and anticipated inflow, the likelihood of meeting management goals can be improved. The upper Delaware River Basin in the northeastern United States is used to demonstrate the basic idea. Physically plausible climate-based forecasts of March-April reservoir inflow are developed. Existing simulation tools and rule curves for the system are used to convert the inflow forecasts to reservoir level forecasts. Operating policies are revised during the forecast period to release less water during forecasts of low reservoir level. Hindcast simulations demonstrate reductions of 1.6% in the number of drought emergency days, which is a key performance measure. Forecasts with different levels of skill are examined to explore their utility. [ABSTRACT FROM AUTHOR]