Seasonality and Drivers of Low Flows Across Europe and the United States

Low river flows can negatively impact society and the riverine environment. Thus, it is useful to predict their seasonal timing and reveal their main drivers. The typical timing of low flows varies between regions, yet systematic overviews across Europe and the United States are rare. Here, we identify regional patterns of the seasonal timing of annual minimum flows, and the consistency of that timing, across 1860 European and US catchments. Catchments where low flows typically occur during late summer or winter tend to have more consistent low-flow timings. We compare the timing of annual low flows with that of potential climatic drivers. Low flows in 89% of the European and 86% of the US catchments exhibit a statistically significant (p < 0.05) overlap in timing with at least one potential climatic driver. In most catchments, low flows tend to occur during the warm season, reflecting a period of high potential evapotranspiration exceeding precipitation. In the higher elevation European Alps, Scandinavia, the Rocky Mountains, and the Upper Midwest and Plains states, low flows mostly occur during winter as a result of freezing temperatures which inhibit snowmelt. Binomial statistics also enabled us to statistically exclude individual climatic drivers for certain regions. The regional patterns of timings and drivers of low flows across Europe and the contiguous US can inform low-flow management, provide context for the evolution of low flows under climate change, and point to processes that require attention in future low-flow research.

Automated summary

This study identified regional patterns of the timing of low flows across 1860 European and US catchments, showing that low flows tend to occur during late summer or winter in more consistent patterns. In most catchments, low flows occur during the warm season, while in higher elevation regions such as the European Alps and Rocky Mountains, low flows mostly occur during winter due to freezing temperatures. Binomial statistics helped exclude individual climatic drivers for certain regions.