Tracing sediment sources with meteoric 10Be: Linking erosion and the hydrograph

Sediment is a natural constituent of river ecosystems. Yet, in excess quantities sediment can severely degrade water quality and aquatic ecosystem health. This problem is especially common in rivers that drain agricultural landscapes (Trimble and Crosson, 2000; Montgomery, 2007). Currently, sediment is one of the leading causes of impairment in rivers of the US and globally (USEPA, 2011; Palmer et al., 2000). Despite extraordinary efforts, sediment remains one of the most difficult nonpoint-source pollutants to quantify at the watershed scale (Walling, 1983; Langland et al., 2007; Smith et al., 2011). Developing a predictive understanding of watershed sediment yield has proven especially difficult in low-relief landscapes. Challenges arise due to several common features of these landscapes, including a) source and sink areas are defined by very subtle topographic features that often cannot be detected even with relatively high resolution topography data (15 cm vertical uncertainty), b) humans have dramatically altered water and sediment routing processes, the effects of which are exceedingly difficult to capture in a conventional watershed hydrology/erosion model (Wilkinson and McElroy, 2007; Montgomery, 2007); and c) as sediment is routed through a river network it is actively exchanged between the channel and floodplain, a dynamic that is difficult to model at the channel network scale (Lauer and Parker, 2008). Thus, while models can be useful to understand sediment dynamics at the landscape scale and predict changes in sediment flux and water quality in response to management actions in a watershed, several key processes are difficult to constrain to a satisfactory degree. Direct measurement of erosion, deposition and sediment transport at key locations (edge of field, eroding/aggrading channel banks) are also useful and can help constrain the aforementioned models, but such efforts are costly and are inherently limited in spatial extent, sampling frequency, and level of detection (Day et al., in review).