@article{GailletonMuddClubbetal.2019, author = {Gailleton, Boris and Mudd, Simon M. and Clubb, Fiona J. and Peifer, Daniel and Hurst, Martin D.}, title = {A segmentation approach for the reproducible extraction and quantification of knickpoints from river long profiles}, series = {Earth surface dynamics}, volume = {7}, journal = {Earth surface dynamics}, number = {1}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {2196-6311}, doi = {10.5194/esurf-7-211-2019}, pages = {211 -- 230}, year = {2019}, abstract = {Changes in the steepness of river profiles or abrupt vertical steps (i.e. waterfalls) are thought to be indicative of changes in erosion rates, lithology or other factors that affect landscape evolution. These changes are referred to as knickpoints or knickzones and are pervasive in bedrock river systems. Such features are thought to reveal information about landscape evolution and patterns of erosion, and therefore their locations are often reported in the geomorphic literature. It is imperative that studies reporting knickpoints and knickzones use a reproducible method of quantifying their locations, as their number and spatial distribution play an important role in interpreting tectonically active landscapes. In this contribution we introduce a reproducible knickpoint and knickzone extraction algorithm that uses river profiles transformed by integrating drainage area along channel length (the so-called integral or chi method). The profile is then statistically segmented and the differing slopes and step changes in the elevations of these segments are used to identify knickpoints, knickzones and their relative magnitudes. The output locations of identified knickpoints and knickzones compare favourably with human mapping: we test the method on Santa Cruz Island, CA, using previously reported knickzones and also test the method against a new dataset from the Quadrilatero Ferrifero in Brazil. The algorithm allows for the extraction of varying knickpoint morphologies, including stepped, positive slope-break (concave upward) and negative slope-break knickpoints. We identify parameters that most affect the resulting knickpoint and knickzone locations and provide guidance for both usage and outputs of the method to produce reproducible knickpoint datasets.}, language = {en} } @article{GoodwinMuddClubb2018, author = {Goodwin, Guillaume C. H. and Mudd, Simon M. and Clubb, Fiona J.}, title = {Unsupervised detection of salt marsh platforms}, series = {Earth surface dynamics}, volume = {6}, journal = {Earth surface dynamics}, number = {1}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {2196-6311}, doi = {10.5194/esurf-6-239-2018}, pages = {239 -- 255}, year = {2018}, abstract = {Salt marshes filter pollutants, protect coastlines against storm surges, and sequester carbon, yet are under threat from sea level rise and anthropogenic modification. The sustained existence of the salt marsh ecosystem depends on the topographic evolution of marsh platforms. Quantifying marsh platform topography is vital for improving the management of these valuable landscapes. The determination of platform boundaries currently relies on supervised classification methods requiring near-infrared data to detect vegetation, or demands labour-intensive field surveys and digitisation. We propose a novel, unsupervised method to reproducibly isolate salt marsh scarps and platforms from a digital elevation model (DEM), referred to as Topographic Identification of Platforms (TIP). Field observations and numerical models show that salt marshes mature into subhorizontal platforms delineated by subvertical scarps. Based on this premise, we identify scarps as lines of local maxima on a slope raster, then fill landmasses from the scarps upward, thus isolating mature marsh platforms. We test the TIP method using lidar-derived DEMs from six salt marshes in England with varying tidal ranges and geometries, for which topographic platforms were manually isolated from tidal flats. Agreement between manual and unsupervised classification exceeds 94\% for DEM resolutions of 1 m, with all but one site maintaining an accuracy superior to 90\% for resolutions up to 3 m. For resolutions of 1 m, platforms detected with the TIP method are comparable in surface area to digitised platforms and have similar elevation distributions. We also find that our method allows for the accurate detection of local block failures as small as 3 times the DEM resolution. Detailed inspection reveals that although tidal creeks were digitised as part of the marsh platform, unsupervised classification categorises them as part of the tidal flat, causing an increase in false negatives and overall platform perimeter. This suggests our method may benefit from combination with existing creek detection algorithms. Fallen blocks and high tidal flat portions, associated with potential pioneer zones, can also lead to differences between our method and supervised mapping. Although pioneer zones prove difficult to classify using a topographic method, we suggest that these transition areas should be considered when analysing erosion and accretion processes, particularly in the case of incipient marsh platforms. Ultimately, we have shown that unsupervised classification of marsh platforms from high-resolution topography is possible and sufficient to monitor and analyse topographic evolution.}, language = {en} } @misc{GoodwinMuddClubb2018, author = {Goodwin, Guillaume C. H. and Mudd, Simon M. and Clubb, Fiona J.}, title = {Unsupervised detection of salt marsh platforms}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {936}, issn = {1866-8372}, doi = {10.25932/publishup-45932}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-459329}, pages = {239 -- 255}, year = {2018}, abstract = {Salt marshes filter pollutants, protect coastlines against storm surges, and sequester carbon, yet are under threat from sea level rise and anthropogenic modification. The sustained existence of the salt marsh ecosystem depends on the topographic evolution of marsh platforms. Quantifying marsh platform topography is vital for improving the management of these valuable landscapes. The determination of platform boundaries currently relies on supervised classification methods requiring near-infrared data to detect vegetation, or demands labour-intensive field surveys and digitisation. We propose a novel, unsupervised method to reproducibly isolate salt marsh scarps and platforms from a digital elevation model (DEM), referred to as Topographic Identification of Platforms (TIP). Field observations and numerical models show that salt marshes mature into subhorizontal platforms delineated by subvertical scarps. Based on this premise, we identify scarps as lines of local maxima on a slope raster, then fill landmasses from the scarps upward, thus isolating mature marsh platforms. We test the TIP method using lidar-derived DEMs from six salt marshes in England with varying tidal ranges and geometries, for which topographic platforms were manually isolated from tidal flats. Agreement between manual and unsupervised classification exceeds 94\% for DEM resolutions of 1 m, with all but one site maintaining an accuracy superior to 90\% for resolutions up to 3 m. For resolutions of 1 m, platforms detected with the TIP method are comparable in surface area to digitised platforms and have similar elevation distributions. We also find that our method allows for the accurate detection of local block failures as small as 3 times the DEM resolution. Detailed inspection reveals that although tidal creeks were digitised as part of the marsh platform, unsupervised classification categorises them as part of the tidal flat, causing an increase in false negatives and overall platform perimeter. This suggests our method may benefit from combination with existing creek detection algorithms. Fallen blocks and high tidal flat portions, associated with potential pioneer zones, can also lead to differences between our method and supervised mapping. Although pioneer zones prove difficult to classify using a topographic method, we suggest that these transition areas should be considered when analysing erosion and accretion processes, particularly in the case of incipient marsh platforms. Ultimately, we have shown that unsupervised classification of marsh platforms from high-resolution topography is possible and sufficient to monitor and analyse topographic evolution.}, language = {en} } @article{GrieveHalesParkeretal.2018, author = {Grieve, Stuart W. D. and Hales, Tristram C. and Parker, Robert N. and Mudd, Simon M. and Clubb, Fiona J.}, title = {Controls on Zero-Order Basin Morphology}, series = {Journal of geophysical research : Earth surface}, volume = {123}, journal = {Journal of geophysical research : Earth surface}, number = {12}, publisher = {American Geophysical Union}, address = {Washington}, issn = {2169-9003}, doi = {10.1029/2017JF004453}, pages = {3269 -- 3291}, year = {2018}, abstract = {Zero-order basins are common features of soil-mantled landscapes, defined as unchanneled basins at the head of a drainage network. Their geometry and volume control how quickly sediment may reaccumulate after landslide evacuation and, more broadly, zero order basins govern the movement of water and sediment from hillslopes to the fluvial network. They also deliver water and sediment to the uppermost portions of the fluvial network. Despite this role as the moderator between hillslope and fluvial processes, little analysis on their morphology has been conducted at the landscape scale. We present a method to identify zero-order basins in landscapes and subsequently quantify their geometric properties using elliptical Fourier analysis. We deploy this method across the Coweeta Hydrologic Laboratory, USA. Properties such as length, relief, width, and concavity follow distinct probability distributions, which may serve as a basis for testing predictions of future landscape evolution models. Surprisingly, in a landscape with an orographic precipitation gradient and large hillslope to channel relief, we observe no correlation between elevation or spatial location and basin geometry. However, we find that two physiographic units in Coweeta have distinct zero-order basin morphologies. These are the steep, thin soiled, high-elevation Nantahala Escarpment and the lower-gradient, lower-elevation, thick soiled remainder of the basin. Our results indicate that basin slope and area negatively covary, producing the distinct forms observed between the two physiographic units, which we suggest arise through competition between spatially variable soil creep and stochastic landsliding.}, language = {en} } @article{MuddClubbGailletonetal.2018, author = {Mudd, Simon M. and Clubb, Fiona J. and Gailleton, Boris and Hurst, Martin D.}, title = {How concave are river channels?}, series = {Earth surface dynamics}, volume = {6}, journal = {Earth surface dynamics}, number = {2}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {2196-6311}, doi = {10.5194/esurf-6-505-2018}, pages = {505 -- 523}, year = {2018}, abstract = {For over a century, geomorphologists have attempted to unravel information about landscape evolution, and processes that drive it, using river profiles. Many studies have combined new topographic datasets with theoretical models of channel incision to infer erosion rates, identify rock types with different resistance to erosion, and detect potential regions of tectonic activity. The most common metric used to analyse river profile geometry is channel steepness, or k(s). However, the calculation of channel steepness requires the normalisation of channel gradient by drainage area. This normalisation requires a power law exponent that is referred to as the channel concavity index. Despite the concavity index being crucial in determining channel steepness, it is challenging to constrain. In this contribution, we compare both slope-area methods for calculating the concavity index and methods based on integrating drainage area along the length of the channel, using so-called "chi" (chi) analysis. We present a new chi-based method which directly compares chi values of tributary nodes to those on the main stem; this method allows us to constrain the concavity index in transient landscapes without assuming a linear relationship between chi and elevation. Patterns of the concavity index have been linked to the ratio of the area and slope exponents of the stream power incision model (m/n); we therefore construct simple numerical models obeying detachment-limited stream power and test the different methods against simulations with imposed m and n. We find that chi-based methods are better than slope-area methods at reproducing imposed m/n ratios when our numerical landscapes are subject to either transient uplift or spatially varying uplift and fluvial erodibility. We also test our methods on several real landscapes, including sites with both lithological and structural heterogeneity, to provide examples of the methods' performance and limitations. These methods are made available in a new software package so that other workers can explore how the concavity index varies across diverse landscapes, with the aim to improve our understanding of the physics behind bedrock channel incision.}, language = {en} } @misc{MuddClubbGailletonetal.2018, author = {Mudd, Simon M. and Clubb, Fiona J. and Gailleton, Boris and Hurst, Martin D.}, title = {How concave are river channels?}, series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, number = {718}, issn = {1866-8372}, doi = {10.25932/publishup-42699}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-426998}, pages = {19}, year = {2018}, abstract = {For over a century, geomorphologists have attempted to unravel information about landscape evolution, and processes that drive it, using river profiles. Many studies have combined new topographic datasets with theoretical models of channel incision to infer erosion rates, identify rock types with different resistance to erosion, and detect potential regions of tectonic activity. The most common metric used to analyse river profile geometry is channel steepness, or k(s). However, the calculation of channel steepness requires the normalisation of channel gradient by drainage area. This normalisation requires a power law exponent that is referred to as the channel concavity index. Despite the concavity index being crucial in determining channel steepness, it is challenging to constrain. In this contribution, we compare both slope-area methods for calculating the concavity index and methods based on integrating drainage area along the length of the channel, using so-called "chi" (chi) analysis. We present a new chi-based method which directly compares chi values of tributary nodes to those on the main stem; this method allows us to constrain the concavity index in transient landscapes without assuming a linear relationship between chi and elevation. Patterns of the concavity index have been linked to the ratio of the area and slope exponents of the stream power incision model (m/n); we therefore construct simple numerical models obeying detachment-limited stream power and test the different methods against simulations with imposed m and n. We find that chi-based methods are better than slope-area methods at reproducing imposed m/n ratios when our numerical landscapes are subject to either transient uplift or spatially varying uplift and fluvial erodibility. We also test our methods on several real landscapes, including sites with both lithological and structural heterogeneity, to provide examples of the methods' performance and limitations. These methods are made available in a new software package so that other workers can explore how the concavity index varies across diverse landscapes, with the aim to improve our understanding of the physics behind bedrock channel incision.}, language = {en} }