Shifts in land use, population, and climate have altered hydrologic systems in the United States in ways that affect water quality and ecosystem function. Water diversions, detention in reservoirs, increased channelization, and changes in rainfall and snowmelt are major causes, but there are also more subtle causes such as changes in soil temperature, atmospheric deposition, and shifting vegetation patterns. The effects on water quality are complex and interconnected, and occur at timeframes of minutes (e.g., flash floods) to decades (e.g., evolving management practices).

However, water-quality monitoring has historically focused on discrete samples collected weekly or monthly, and laboratory analyses that can take days or weeks to complete. Low-frequency data and delayed access hampers a timely response during events, limits the ability to identify specific causes or actions, and may result in poorly quantified effects on ecosystems and human health at local to regional scales.

Recent advancements in commercially available in situ sensors, data platforms, and new techniques for data analysis provide an opportunity to monitor water quality in rivers, lakes, and estuaries on the time scales in which changes occur. For example, measurements that capture the variability in freshwater systems over time help to assess how shifts in seasonal runoff, changes in precipitation intensity, and increased frequencies of disturbances (such as fire and insect outbreaks) affect the storage, production, and transport of carbon and nitrogen in watersheds. Transmitting these data in real-time also provides information that can be used for early trend detection, help identify monitoring gaps, and provide sciencebased decision support across a range of issues related to water quality, freshwater ecosystems, and human health.