Bedload response to precipitation averaging across a channel network

Abstract:

In modeling sediment transport across watersheds, hydrology models are used to drive sediment transport, often using daily precipitation inputs. In this study, we ask: Is the bias introduced into the bedload model from the precipitation averaging significant relative to the orders-of-magnitude level of uncertainty typical in bedload transport modeling? We address this problem by comparing modeled bedload response to 1-hour average precipitation rates and 24-hour average precipitation rates at basin locations varying from colluvial headwater channels to low-land, pool-riffle channels in the Sauk River watershed, a mountainous basin where a large portion of annual precipitation falls as snow and melts in the spring. A non-dimensional bedload metric based on the Wilcock and Crowe 2003 bedload equation that reflects the relative magnitude of bedload transport with respect to bankfull transport is developed and used. We find that cumulative bedload transport for a single storm event computed using 1-hour precipitation can be three orders of magnitude higher than the 24-hour estimate with the largest differences occurring in headwater channels. While such large differences in bedload estimates are rare in the Sauk watershed, they are caused when lower 24-hour precipitation rates fall short to raise the streamflow above transport thresholds. This scenario tends to arise when baseflow before a storm event is low relative to the reference flow rate and the difference in the 1-hour and 24-hour maximum precipitation rates are large. This condition is particularly likely in headwater channels where the reference shear stress is relatively high and storm hydrograph recession is rapid; however, snow accumulation and melt processes can drastically alter the location in the channel network where large differences in modeled bedload occur.