Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.726560
Title: Uncovering signatures of geomorphic process through high resolution topography
Author: Grieve, Stuart William David
ISNI:       0000 0004 6421 0998
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2016
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
Abstract:
The measurement of topography is a key aspect of geomorphology research, and the prevalence of high resolution topographic data predominantly from Light Detection And Ranging (LiDAR) in the past decade has facilitated a revolution in the quantitative study of planetary surface processes. From this increased quality of data, many techniques have been developed to quantify processes occurring at diverse spatial and temporal scales; from the flow of material down a hill-slope to the uplift and subsequent erosion of mountain ranges. Such insights have identified signatures of processes imprinted on landscapes. These include physical processes such as wildfires and landslides, biological processes such as animal burrowing and tree throw, in addition to tectonic uplift and large scale sediment transport. These signatures are observed in both the morphology of hill-slopes and their connection to the channel network, thereby allowing measures of topography to provide quantitative measures of the rates of processes shaping the Earth’s surface. This thesis is concerned with the development and application of reproducible topographic analysis techniques, to yield new insights into hill-slope sediment transport and to provide accurate metrics for quantifying hill-slope properties, including hill-slope length (LH) and relief (R). The measurement of hill-slope length can be performed through the inversion of drainage density, or the analysis of slope-area plots. However, in Chapter 3 I present a method which quantifies the length of hill-slopes through the generation of hill-slope flow paths. The flow path method is shown to be the most reliable of these methods, and is able to provide measurements of the properties of individual hill-slopes, rather than the basin or landscape averaged techniques commonly employed. The topographic predictions of the LH-R relationship of the nonlinear sediment flux law, stating that the rate of sediment transport is nonlinearly dependent on hill-slope gradient, are also tested and contrasted with the predictions of a linear sediment flux law. This provides the first purely topography based test of a sediment flux law. Through the fitting of a prediction of the nonlinear flux derived model to these measurements of hill-slope length and relief, the critical gradient of each landscape, a key parameter in the nonlinear sediment flux law, is also constrained. A nondimensional framework for erosion rate and relief, which allows the comparison of hill-slopes with differing properties in order to identify landscape transience is presented in Chapter 4. This analysis technique builds upon the work performed in Chapter 3, utilizing similar measurements of hill-slope properties, including hill-slope length and relief. The software produced alongside this chapter is shown to reproduce the results of previous studies which have employed this technique. The method is employed on a new landscape in Coweeta, North Carolina where subtle evidence of topographic decay is presented, consistent with models of Miocene topographic rejuvenation in this location. A detailed sensitivity analysis of the technique is performed, highlighting the need for careful parameterization of any analysis, to ensure meaningful results. This method is also employed to estimate an average critical gradient for each landscape, presenting more evidence building upon the evidence presented in Chapter 3 that a broad range of critical gradients exist for any given landscape. The work presented in Chapter 5 attempts to constrain the limits of the geomorphic analyses presented in the previous chapters, when they are applied to low resolution topographic data. A series of topographic datasets are generated at resolutions ranging from 1 to 30 meters upon which topographic analyses are performed. I test two common channel extraction algorithms and find that a simple geometric method, which identifies tangential curvature thresholds in the landscape, provides a more accurate representation of the channel network in low resolution topographic data than a process based method which identifies the topographic signature of channel initiation. The measurement of curvature is also evaluated, and alongside the estimation of diffusivity, is shown to be sensitive to data resolution, however landscape properties also exhibit a strong control on these measurements, where the larger scale curvature signal of Gabilan Mesa, California is more robust than the sharp ridgelines of Santa Cruz Island, California. Finally, the techniques developed in Chapter 3 to measure hill-slope length and relief are tested and are shown to be robust at grid sizes up to 30 meters, with the caveat that an accurate channel network can be constrained.
Supervisor: Mudd, Simon Sponsor: Natural Environment Research Council (NERC)
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.726560  DOI: Not available
Keywords: LiDAR ; Light Detection And Ranging ; topography ; sediment transport ; hillslope ; hill-slope
Share: