Development of ST:REAM: a reach-based stream power balance approach for predicting alluvial river channel adjustment

Chris Parker, Colin R Thorne, Nicholas J Clifford

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)


River channel sediment dynamics are important in integrated catchment management because changes in channel morphology resulting from sediment transfer have important implications for many river functions. However, application of existing approaches that account for catchment-scale sediment dynamics has been limited, largely due to the difficulty in obtaining data necessary to support them. It is within this context that this study develops a new, reach-based, stream power balance approach for predicting river channel adjustment.

The new approach, named ST:REAM (sediment transport: reach equilibrium assessment method), is based upon calculations of unit bed area stream power (ω) derived from remotely sensed slope, width and discharge datasets. ST:REAM applies a zonation algorithm to values of ω that are spaced every 50 m along the catchment network in order to divide the branches of the network up into relatively homogenous reaches. ST:REAM then compares each reach's ω value with the ω of its upstream neighbour in order to predict whether or not the reach is likely to be either erosion dominated or deposition dominated.

The paper describes the application of ST:REAM to the River Taff in South Wales, UK. This test study demonstrated that ST:REAM can be rapidly applied using remotely sensed data that are available across many river catchments and that ST:REAM correctly predicted the status of 87.5% of sites within the Taff catchment that field observations had defined as being either erosion or deposition dominated. However, there are currently a number of factors that limit the usefulness of ST:REAM, including inconsistent performance and the need for additional, resource intensive, data to be collected to both calibrate the model and aid interpretation of its results.
Original languageEnglish
Number of pages11
Early online date16 Oct 2014
Publication statusPublished - 2014


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