Assessing Continental Gradients In The Significance of Runoff and Baseflow To Turbidity Generation In Streams

Freshwater sediment pollution is a major concern worldwide due to its damaging impacts on ecological communities, availability of drinking water, and infrastructure. A substantial proportion of sediment is transported during intense precipitation events when enough capacity exists for erosion and mobilization of materials to water bodies. While the advent of high-frequency in situ water quality sensors has paved the way for better identification of sediment dynamics during storm events, developing sustainable management strategies requires insight into the temporal relationship between stormwater components and fluvial sediment concentration, and how this relationship is influenced by watershed properties (e.g. land use, soil, topography) and hydroclimatological drivers (e.g. storm intensity, antecedent conditions, precipitation duration). We address this knowledge gap by quantitatively comparing the relative significance of surface runoff and subsurface baseflow to generating in-stream turbidity during storm events for hundreds of streams across the contiguous United States. First, we developed an automated algorithm to retrieve flow, turbidity, and specific conductance time series from United States Geological Survey gages. Thereafter, we enumerated all storm events contained within the time-series and employed specific conductance-based hydrograph separation of streamflow into runoff and baseflow components. Lastly, we used a multiple-linear regression technique to assess the temporal alignment of runoff and baseflow with in-stream turbidity and applied statistical tools to determine continental gradients of watershed and hydroclimatological controls on turbidity generation. Our results revealed interesting patterns in the temporal and spatial variability in sediment-hydrology interactions, such as the seasonality of turbidity response to runoff and baseflow, increasing turbidity response to baseflow in urban watersheds, and higher predictability of turbidity response to flow in rural landscapes. These findings suggest the potential of coupling hydrograph separation methods with high-frequency water quality data to better understand material transport mechanisms to fluvial systems