Linking River Channel Form and Process: Time, Space and Causality Revisited

• Published in: Earth surface processes and landforms 1997-03, Vol.22 (3), p.249-260
• Main Authors: Lane, Stuart N., Richards, Keith S.
• Format: Article
• Language: English
• Subjects: Bgi / Prodig; deterministic chaos; dynamic geomorphology; Earth sciences; Earth, ocean, space; Exact sciences and technology; Fluvial forms and processes; fluvial geomorphology; functional geomorphology; Geomorphology; Geomorphology, landform evolution; methodology; non-linear thinking; Physical geography; Surficial geology
• ISSN: 0197-9337; 1096-9837
• DOI: 10.1002/(SICI)1096-9837(199703)22:3<249::AID-ESP752>3.0.CO;2-7

Fluvial geomorphology has witnessed a continuing reduction in the time‐ and space‐scales of research, with increasing emphasis on the dynamics of small site‐specific river reaches. This shift can be regarded as part of a trend towards the understanding and explanation rather than description of how rivers change, which raises important questions regarding the relevance of such short time‐scale and small space‐scale research to understanding longer‐term aspects of landform behaviour. The methodological challenges that arise from such intensive case study research are illustrated here using a detailed investigation of a river reach. Morphological changes within this reach are shown to be driven by: (i) catchment‐scale processes associated with the interaction of discharge and sediment supply waves; and (ii) modification of these processes through morphological controls on erosion and deposition patterns and hence net channel change. The ‘morphological conditioning’ of channel response reflects the configurational aspects of channel change, and the importance of local characteristics in the understanding of system behaviour. Sensitivity to local conditions implies that short time‐scale and small space‐scale processes may be critical to channel behaviour, particularly if the system is interpreted in non‐linear terms. Although it may be possible to identify statistically averaged stable states, non‐linear system behaviour implies that system trajectories are sensitively dependent upon instantaneous system states. Thus, changes between average states can only be understood through an understanding of the sequence of configurational states through which the system evolves. © 1997 by John Wiley & Sons, Ltd.