Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.738780
Title: Controls on fluvial networks in upland landscapes : from hillslopes to floodplains
Author: Clubb, Fiona Jane
ISNI:       0000 0004 7223 4930
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2017
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Abstract:
Mountainous regions are ubiquitously dissected by river networks. These networks are the main drivers by which climate and tectonic signals are transmitted to the rest of the landscape, and control the response timescale of the landscape to these external forcings. Furthermore, river systems set the downslope boundary conditions for hillslope sediment transport, which controls landscape denudation. Therefore, understanding the controls on the organisation and structure of river networks in upland landscapes is an important goal in Earth surface processes research. The recent introduction of high-resolution topographic data, such as airborne lidar data, has revolutionised our ability to extract information from the topography, providing new opportunities for linking geomorphic process with landscape form. This thesis is focused on developing techniques for analysing high-resolution topographic data to quantify and understand controls on the structure of fiuvial systems in upland landscapes. Firstly, I develop and test new algorithms for objective feature extraction from lidar-derived digital elevation models (DEMs). I present a new method for identifying the upstream extent of channel processes by identifying scaling breaks in river long profiles. I then compare this new method to three existing methods of channel extraction, using field-mapped channel heads from four field sites in the US. I find that the new method presented here, along with another method of identifying channels based on valley geometry, most accurately reproduces the measured channel heads in all four field sites. I then present a new method for identifying floodplains and fiuvial terraces from DEMs based on two thresholds: local gradient, and elevation compared to the nearest channel. These thresholds are calculated statistically from the DEM using quantile-quantile plots and do not need to be set manually for each landscape in question. I test this new method against field-mapped floodplain initiation points, published flood hazard maps, and digitised terrace surfaces from eight field sites in both the US and the UK. This method provides a new tool for rapidly and objectively identifying floodplain and terrace features on a landscape scale, with applications including flood risk mapping, landscape evolution modelling, and quantification of sediment storage and routing. Finally, I apply these new algorithms to examine the density of channel networks across a range of mountainous landscapes, and explore implications for fluvial incision models. I compare the relationship between drainage density (Dd) and erosion rate (E) using both analytical solutions and numerical modelling, and find that varying the channel slope exponent (n) in detachment-limited fluvial incision models controls the relationship between Dd and E. Following on from this, I quantify Dd for five field sites throughout the US. For two of these field sites I compare Dd to cosmogenic radionuclide (CRN)-derived erosion rates, and for each site I use mean hilltop curvature as a proxy for erosion rate where CRN-derived erosion rates are not available. I find that there is a significant positive relationship between Dd, E, and hilltop curvature across four out of the five field sites. In contrast to assumptions made in many studies of fluvial incision, this positive relationship suggests that the channel slope exponent n is greater than unity for each of these landscapes, with fundamental implications for both landscape evolution and sediment transport.
Supervisor: Mudd, Simon ; Attal, Mikael Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.738780  DOI: Not available
Keywords: fluvial geomorphology ; LiDAR ; hillslopes ; topographic analysis
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