Predicting the distribution of bed material accumulation using river network sediment budgets

Abstract

Assessing the spatial distribution of bed material accumulation in river networks is important for determining the impacts of erosion on downstream channel form and habitat and for planning erosion and sediment management. A model that constructs spatially distributed budgets of bed material sediment is developed to predict the locations of accumulation following land use change. For each link in the river network, GIS algorithms are used to predict bed material supply from gullies, river banks, and upstream tributaries and to compare total supply with transport capacity. The model is tested in the 29,000 km2 Murrumbidgee River catchment in southeast Australia. It correctly predicts the presence or absence of accumulation in 71% of river links, which is significantly better performance than previous models, which do not account for spatial variability in sediment supply and transport capacity. Representing transient sediment storage is important for predicting smaller accumulations. Bed material accumulation is predicted in 25% of the river network, indicating its importance as an environmental problem in Australia.

Can an indicator of river health be related to assessments from a catchment-scale sediment model?

“…It was chosen for study because of the spatial variability in its BMA and because standardised AUSRIVAS macroinvertebrate sampling has, since 1994, already been conducted throughout the catchment. Moreover, recent SedNet modelling of the catchment has also been done, including an evaluation of how well the model predicts BMA depth (Wilkinson et al, 2006). National parks, water supply reserves and forests are located in the higher relief areas ([800 m ASL) in the west of the catchment; agriculture, including grazing and cropping, takes place in the valleys, the Monaro plains to the southeast of Canberra, areas around Cooma and in the north towards Yass (Fig.…”

“…The Sediment River Network model (SedNet) is a bed material sediment budget model that captures historical changes in erosion and sediment transport processes and predicts the contemporary spatial location and extent of sand and fine gravel bed material accumulation (BMA) (particle diameter \5 mm) over large river basins of 1,000-1,000,000 km 2 following major land use change. The model was originally developed as part of the National Land and Water Resources Audit to assess suspended and bed material sediment budgets across Australia (Prosser et al, 2001a) and has since been refined for river catchment assessments (see Wilkinson et al, 2006). The model makes predictions for each 5-10 km segment (or link) in a river network between tributary confluences.…”

“…1). The present-day depth of BMA resulting from historical erosion over the last 125 years of European grazing practices is simply predicted by dividing the total volume of accumulation by channel area (Prosser et al, 2001a;Wilkinson et al, 2006). The SedNet model used in this article is a transient version that accounts for the residence time of bed material as it moves through the river network (Wilkinson et al, 2006).…”

“…The present-day depth of BMA resulting from historical erosion over the last 125 years of European grazing practices is simply predicted by dividing the total volume of accumulation by channel area (Prosser et al, 2001a;Wilkinson et al, 2006). The SedNet model used in this article is a transient version that accounts for the residence time of bed material as it moves through the river network (Wilkinson et al, 2006). The accuracy of this model has already been tested in the Murrumbidgee River catchment in southeast Australia, where it has correctly predicted the presence or absence of accumulation in 71% of river links (Wilkinson et al, 2006).…”

“…The SedNet model used in this article is a transient version that accounts for the residence time of bed material as it moves through the river network (Wilkinson et al, 2006). The accuracy of this model has already been tested in the Murrumbidgee River catchment in southeast Australia, where it has correctly predicted the presence or absence of accumulation in 71% of river links (Wilkinson et al, 2006). This article tests whether the macroinvertebrate community structure is related to the mean river-link BMA depth as predicted by SedNet.…”