Regionalizing mean annual flow and daily flow variability for basin-scale sediment and nutrient modelling
Version of Record online: 3 APR 2006
Copyright © 2006 John Wiley & Sons, Ltd.
Volume 20, Issue 13, pages 2769–2786, 30 August 2006
How to Cite
Wilkinson, S. N., Young, W. J. and DeRose, R. C. (2006), Regionalizing mean annual flow and daily flow variability for basin-scale sediment and nutrient modelling. Hydrol. Process., 20: 2769–2786. doi: 10.1002/hyp.6070
- Issue online: 26 JUL 2006
- Version of Record online: 3 APR 2006
- Manuscript Accepted: 19 MAY 2005
- Manuscript Received: 16 AUG 2004
- Land and Water Australia
- water yield;
- ungauged catchments;
- sediment transport
River discharges vary strongly through time and space, and quantifying this variability is fundamental to understanding and modelling river processes. The river basin is increasingly being used as the unit for natural resource planning and management; to facilitate this, basin-scale models of material supply and transport are being developed. For many basin-scale planning activities, detailed rainfall-runoff modelling is neither necessary nor tractable, and models that capture spatial patterns of material supply and transport averaged over decades are sufficient. Nevertheless, the data to describe the spatial variability of river discharge across large basins for use in such models are often limited, and hence models to predict river discharge at the basin scale are required. We describe models for predicting mean annual flow and a non-dimensional measure of daily flow variability for every river reach within a drainage network. The models use sparse river gauging data, modelled grid surfaces of mean annual rainfall and mean annual potential evapotranspiration, and a network accumulation algorithm. We demonstrate the parameterization and application of the models using data for the Murrumbidgee basin, in southeast Australia, and describe the use of these predictions in modelling sediment transport through the river network. The regionalizations described contain less uncertainty, and are more sensitive to observed spatial variations in runoff, than regionalizations based on catchment area and rainfall alone. Copyright © 2006 John Wiley & Sons, Ltd.