Abstract
An appreciation of catchment-level effects (i.e. the impacts from catchment characteristics such as morphometry, climate, geology, land cover and the drainage network) on river reaches is often seen as the gold standard in river management. Yet quantifying catchment-level effects remains a complex research area. With branches in geomorphology, hydrology, ecology and applied river management, studies are often restricted to individual sites or catchments and only frequently consider a subset of possible catchment controls, primarily anthropogenic drivers. This PhD provides a more holistic, possibly transferrable methodology and interpretation, considering multiple catchment-level effects and focusing on an often-overlooked component of the catchment: the topology of the river network.To achieve this, a broad-scale approach is adopted utilising a monitoring dataset collected for regulatory compliance (the River Habitat Survey) and adapting it for scientific enquiry. When paired with GIS-derived catchment controls and data-science techniques, this monitoring dataset enables national-level enquiry into catchment-level effects on the type and diversity of physical habitats in river reaches in England. Here, catchment-level effects are quantified via: (i) the production of a national waterbody typology combining multiple catchment-level effects using machine learning techniques; and (ii) the adaptation of flood estimation metrics to reflect network topological structure. Statistical analysis of the monitoring dataset shows that both the waterbody typology and network topology have functional applicability to physical habitats.
This PhD not only aims to provide new ways of quantifying catchment-level effects but also aims to improve our understanding of their impacts. To accomplish this, controls from multiple spatial hierarchical levels in the river system – from catchment to reach – are combined using a data-science approach to explain the controls on physical habitat type and diversity in river reaches in England. The results show that there are broad patterns in physical habitats from upland to lowland catchments, and upstream to downstream within catchments. These results are consistent with earlier analysis of the River Habitat Survey dataset. However, there remains much variation, only some of which is explained by the influence of network topology. This national-level assessment of catchment-level effects demonstrates the importance of more holistic and strategic thinking in river management. The transferable methodologies enable river managers to better spatially target areas for management or conservation within catchments and compare sites with similar catchment-level effects.
| Date of Award | 1 Jul 2020 |
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| Original language | English |
| Awarding Institution |
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| Supervisor | James Millington (Supervisor) & Michael Chadwick (Supervisor) |