Modeled stream discharge is often used to drive sediment transport models across channel networks. Because sediment transport varies non-linearly with flow rates, discharge modeled from daily total precipitation distributed evenly over 24-hrs may significantly underestimate actual bedload transport capacity. In this study, we assume bedload transport capacity determined from a hydrograph resulting from the use of hourly (1-h) precipitation is a close approximation of actual transport capacity and quantify the error introduced into a network-scale bedload transport model driven by daily precipitation at channel network locations varying from lowland pool-riffle channels to upland colluvial channels in a watershed where snow accumulation and melt can affect runoff processes. Transport capacity is determined using effective stresses and the Wilcock and Crowe (2003) equations and expressed in terms of transport capacity normalized by the bankfull value. We find that, depending on channel network location, cumulative error can range from 10 - 20% to more than two orders of magnitude. Surprisingly, variation in flow rates due to differences in hillslope and channel runoff do not seem to dictate the network locations where the largest errors in predicted bedload transport capacity occur. Rather, spatial variability of the magnitude of the effective-bankfull-excess shear stress and changes in runoff due to snow accumulation and melt exert the greatest influence. These findings have implications for flood-hazard and aquatic habitat models that rely on modeled sediment transport driven by coarse-temporal-resolution climate data.
|Title||How does precipitation variability control bedload response across a mountainous channel network in a maritime climate?|
|Authors||Jeffrey Keck, Erkan Istanbulluoglu, Jessica Lundquist, Christina Bandaragoda, Kristin Jaeger, Guillaume S. Mauger, Alex Horner-Devine|
|Publication Subtype||Journal Article|
|Series Title||Water Resources Research|
|Record Source||USGS Publications Warehouse|
|USGS Organization||Washington Water Science Center|