Abstract

This thesis develops and tests a classification of ‘near-natural’ European single-thread rivers, which are free to adjust to fluvial processes. The research involves subdividing rivers along a continuum of geomorphological characteristics to assign river reaches to geomorphologically-meaningful classes according to their channel dimensions and forms, and floodplain characteristics. The classification was developed and tested through three research components. First, a preliminary classification was developed using information entirely derived from a new information system containing remotely-sensed imagery and digital terrain data: Google Earth. This research stage required the development of rules for identifying, extracting and standardising information from this source for a large sample of river reaches. 221 single-thread river reaches distributed across 75 European rivers were investigated. Analysis of the derived information resulted in the development of a classification comprising six classes of European single thread river. Second, the robustness of the classification was explored including assessments of (i) the degree to which the classes were interpretable in relation to the geomorphic features they displayed; (ii) the degree to which sub-divisions of the six classes could be identified and justified; (iii) the accuracy of some specific types of information extracted from Google Earth; and (iv) the degree to which the six classes corresponded to expected gradients in two controlling variables: stream power and bed sediment calibre. Thirdly, bar theory was applied to a sample of rivers representative of the six classes. Since bars are an important contributor to river channel form and dynamics, the correspondence of the bars in the six river classes to their expected distribution as indicated by bar theory, provided further confirmation of the robustness of the classification. The outputs of the research are (i) a fully-tested classification of European single-thread rivers; and (ii) a demonstration of how Google Earth can provide valuable information for research in fluvial geomorphology. Some additional future research stages are proposed that could turn the classification into an operational tool in the context of river assessment and management.