Importance of concavity for interpreting rates and patterns of landscape evolution from river profiles

2020 ◽  
Author(s):  
Boris Gailleton ◽  
Simon Mudd ◽  
Fiona Clubb ◽  
Martin Hurst ◽  
Stuart Grieve
Keyword(s):  
Landscape Evolution ◽  
Spatial Scales ◽  
Reference Value ◽  
High Sensitivity ◽  
Drainage Area ◽  
Relative Distribution ◽  
Sea Level Changes ◽  
Widespread Application ◽  
River Profiles ◽  
Channel Steepness

<p>The analysis of river profiles is a fundamental tool in modern quantitative geomorphology. Since the 1960's, workers have demonstrated a systematic power-law relationship between river gradient and discharge, or its proxy drainage area, predicting a steepening of rivers towards the headwaters. This relationship provides means of quantitatively describing river profiles by extracting a concavity index (<em>θ</em>), the rate at which slope decreases as a function of drainage area, and steepness index (<em>k<sub>s</sub></em>), the steepness of river reaches independent of changes in drainage area. Recent developments have provided an alternative representation of the slope-area relationship, aiming to circumvent its high sensitivity to topographic noise and to the branching nature of fluvial networks by directly integrating drainage area normalised to a concavity index into a transformed coordinate (<em>χ</em>). These parameters can be easily extracted from digital elevation models, resulting in their widespread application to detect tectonic, climatic, and autogenic signals from landscape morphology, such as active faulting, stream piracy, drainage divide migration or sea-level changes.</p><p>River profile concavity, or <em>θ</em>, is an essential metric to constrain, as it is necessary to fix a reference value <em>θ<sup>ref</sup></em> in order to compare <em>χ</em> or <em>k<sub>s</sub></em> values between different drainage basins. This exposes a key problem with the slope-area relationship: the watersheds within a study area do not necessarily all have the same optimal <em>θ</em>, potentially leading to incorrect interpretations of the relative distribution of <em>χ</em> and <em>k<sub>s</sub></em> within a landscape. This problem is enhanced over large spatial scales, such as over the width of an orogen, where the probability of <em>θ</em> heterogeneity increases drastically. However, the distortion of <em>χ</em> and <em>k<sub>s</sub></em> linked to a <em>θ<sup>ref</sup></em> being different than the local best-fit has been poorly explored: we currently do not know how much these concavity variations influence channel steepness interpretations.</p><p>In this contribution, we explore the extent of the effect of varying concavity on channel steepness using analytical and numerical methods both on landscape evolution models and real landscapes. We show that (i) relative values of <em>χ</em> and <em>k<sub>s</sub></em>, i.e location of local maxima, minima and variations, can be significantly and non-linearly impacted as a function of their <em>Δθ</em> from optimal <em>θ</em> and drainage area; (ii) we identify cases where asymmetries in <em>θ</em> can cause incorrect interpretations of changes in channel steepness (iii) present tools to quantify the extent and therefore the risk of misinterpretation.</p>

scholarly journals Constraining the Stream Power Law: a novel approach combining a Landscape Evolution Model and an inversion method

2013 ◽  
Vol 1 (1) ◽  
pp. 891-921
Author(s):  
T. Croissant ◽  
J. Braun
Keyword(s):  
Power Law ◽  
Erosion Rate ◽  
Landscape Evolution ◽  
Evolution Model ◽  
Drainage Area ◽  
Inversion Method ◽  
Stream Power ◽  
Time Step ◽  
Novel Approach ◽  
River Profiles

Abstract. In the past few decades, many studies have been dedicated to our understanding of the interactions between tectonic and erosion and, in many instances, using numerical models of landscape evolution. Among the numerous parameterizations that have been developed to predict river channel evolution, the Stream Power Law, which links erosion rate to drainage area and slope, remains the most widely used. Despite its simple formulation, its power lies in its capacity to reproduce many of the characteristic features of natural systems (the concavity of river profile, the propagation of knickpoints, etc.). However, the three main coefficients that are needed to relate erosion rate to slope and drainage area in the Stream Power Law remain poorly constrained. In this study, we present a novel approach to constrain the Stream Power Law coefficients under the detachment limited mode by combining a highly efficient Landscape Evolution Model, FastScape, which solves the Stream Power Law under arbitrary geometries and boundary conditions and an inversion algorithm, the Neighborhood Algorithm. A misfit function is built by comparing topographic data of a reference landscape supposedly at steady state and the same landscape subject to both uplift and erosion over one time step. By applying the method to a synthetic landscape, we show that different landscape characteristics can be retrieved, such as the concavity of river profiles and the steepness index. When applied on a real catchment (in the Whataroa region of the South Island in New Zealand), this approach provide well resolved constraints on the concavity of river profiles and the distribution of uplift as a function of distance to the Alpine Fault, the main active structure in the area.

scholarly journals Constraining the stream power law: a novel approach combining a landscape evolution model and an inversion method

2014 ◽  
Vol 2 (1) ◽  
pp. 155-166 ◽  
Author(s):  
T. Croissant ◽  
J. Braun
Keyword(s):  
Power Law ◽  
Erosion Rate ◽  
Landscape Evolution ◽  
Evolution Model ◽  
Drainage Area ◽  
Inversion Method ◽  
Stream Power ◽  
Time Step ◽  
Novel Approach ◽  
River Profiles

Abstract. In the past few decades, many studies have been dedicated to the understanding of the interactions between tectonics and erosion, in many instances through the use of numerical models of landscape evolution. Among the numerous parameterizations that have been developed to predict river channel evolution, the stream power law, which links erosion rate to drainage area and slope, remains the most widely used. Despite its simple formulation, its power lies in its capacity to reproduce many of the characteristic features of natural systems (the concavity of river profile, the propagation of knickpoints, etc.). However, the three main coefficients that are needed to relate erosion rate to slope and drainage area in the stream power law remain poorly constrained. In this study, we present a novel approach to constrain the stream power law coefficients under the detachment-limited mode by combining a highly efficient landscape evolution model, FastScape, which solves the stream power law under arbitrary geometries and boundary conditions and an inversion algorithm, the neighborhood algorithm. A misfit function is built by comparing topographic data of a reference landscape supposedly at steady state and the same landscape subject to both uplift and erosion over one time step. By applying the method to a synthetic landscape, we show that different landscape characteristics can be retrieved, such as the concavity of river profiles and the steepness index. When applied on a real catchment (in the Whataroa region of the South Island in New Zealand), this approach provides well-resolved constraints on the concavity of river profiles and the distribution of uplift as a function of distance to the Alpine Fault, the main active structure in the area.

scholarly journals Landscape evolution models using the stream power incision model show unrealistic behavior when <i>m</i> ∕ <i>n</i> equals 0.5

2017 ◽  
Vol 5 (4) ◽  
pp. 807-820 ◽  
Author(s):  
Jeffrey S. Kwang ◽  
Gary Parker
Keyword(s):  
Steady State ◽  
Landscape Evolution ◽  
Drainage Area ◽  
Uplift Rate ◽  
Stream Power ◽  
River Incision ◽  
Vertical Incision ◽  
Small Scales ◽  
Insight Into

Abstract. Landscape evolution models often utilize the stream power incision model to simulate river incision: E = KAmSn, where E is the vertical incision rate, K is the erodibility constant, A is the upstream drainage area, S is the channel gradient, and m and n are exponents. This simple but useful law has been employed with an imposed rock uplift rate to gain insight into steady-state landscapes. The most common choice of exponents satisfies m ∕ n = 0.5. Yet all models have limitations. Here, we show that when hillslope diffusion (which operates only on small scales) is neglected, the choice m ∕ n = 0.5 yields a curiously unrealistic result: the predicted landscape is invariant to horizontal stretching. That is, the steady-state landscape for a 10 km2 horizontal domain can be stretched so that it is identical to the corresponding landscape for a 1000 km2 domain.

scholarly journals Geomorphological indicators of large-scale climatic changes in the Eastern Bolivian lowlands

2006 ◽  
Vol 61 (2) ◽  
pp. 120-134 ◽  
Author(s):  
J. May
Keyword(s):  
South America ◽  
Large Scale ◽  
Climate Changes ◽  
Landscape Evolution ◽  
Spatial Scales ◽  
Climatic Changes ◽  
Climatic Conditions ◽  
Fluvial Erosion ◽  
Paleoclimatic Significance ◽  
Bolivian Lowlands

Abstract. This study provides an inventory of geomorphological landforms in Eastern Bolivia at different spatial scales. Landforms and associated processes are interpreted and discussed regarding landscape evolution and paleoclimatic significance. Thereby, preliminary conclusions about past climate changes and the geomorphic evolution in Eastern Bolivia can be provided. Fluvial and aeolian processes are presently restricted to a few locations in the study area. A much more active landscape has been inferred from large-scale Channel shifts and extensive paleodune Systems. Mobilization. transport and deposition of Sediments are thought to be the result of climatic conditions drier than today. However. there are also indications of formerly wetter conditions such as fluvial erosion and paleolake basins. In conclusion, the documentation and interpretation of the manifold landforms has shown to contain a considerable amount of paleoecological information, which might serve as the base for further paleoclimatic research in the central part of tropical South America.

scholarly journals Large-scale Mapping of the Galaxy by IRAS

1985 ◽  
Vol 106 ◽  
pp. 219-222
Author(s):  
T.N. Gautier ◽  
M. G. Hauser
Keyword(s):  
Large Scale ◽  
Milky Way ◽  
Spatial Scales ◽  
High Sensitivity ◽  
The Galaxy ◽  
Infrared Astronomical Satellite ◽  
Interstellar Material ◽  
Map Resolution ◽  
Astronomical Satellite ◽  
Excellent Stability

The Infrared Astronomical Satellite (IRAS), launched 1983 January 25, has been conducting a high-sensitivity, high-resolution all-sky photometric survey at wavelengths of 12, 25, 60, and 100 μm in the infrared. One of the data products from the survey will be a map of the entire Milky Way within latitude limits of 10 degrees at a resolution of 4 arcminutes. Since the IRAS detector system is DC-coupled and has demonstrated excellent stability, this map will contain reliable information on all spatial scales larger than the map resolution. The extremely high sensitivity of the IRAS instrument for the detection of interstellar material in the survey mode is illustrated here in terms of visual extinction and dust and gas column densities.

scholarly journals Highly sampled measurements in a controlled atmosphere at the Biosphere 2 Landscape Evolution Observatory

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Jorge Arevalo ◽  
Xubin Zeng ◽  
Matej Durcik ◽  
Michael Sibayan ◽  
Luke Pangle ◽  
...  
Keyword(s):  
Landscape Evolution ◽  
Spatial Scales ◽  
Bare Soil ◽  
Biosphere 2 ◽  
University Of Arizona ◽  
Relative Water ◽  
Sampled Measurements ◽  
Temporal And Spatial ◽  
The University ◽  
Temperature Water

Abstract Land-atmosphere interactions at different temporal and spatial scales are important for our understanding of the Earth system and its modeling. The Landscape Evolution Observatory (LEO) at Biosphere 2, managed by the University of Arizona, hosts three nearly identical artificial bare-soil hillslopes with dimensions of 11 × 30 m2 (1 m depth) in a controlled and highly monitored environment within three large greenhouses. These facilities provide a unique opportunity to explore these interactions. The dataset presented here is a subset of the measurements in each LEO’s hillslopes, from 1 July 2015 to 30 June 2019 every 15 minutes, consisting of temperature, water content and heat flux of the soil (at 5 cm depth) for 12 co-located points; temperature, relative humidity and wind speed above ground at 5 locations and 5 different heights ranging from 0.25 m to 9–10 m; 3D wind at 1 location; the four components of radiation at 2 locations; spatially aggregated precipitation rates, total subsurface discharge, and relative water storage; and the measurements from a weather station outside the greenhouses.

Divide mobility controls knickpoint migration on the Roan Plateau

2020 ◽  
Author(s):  
Wolfgang Schwanghart ◽  
Dirk Scherler
Keyword(s):  
Colorado River ◽  
Drainage Area ◽  
Lagrangian Model ◽  
Drainage Network ◽  
Migration Rates ◽  
Tectonic History ◽  
Area Loss ◽  
Temporal Aspects ◽  
History Of ◽  
River Profiles

&lt;p&gt;Knickpoints in longitudinal river profiles provide proxies for the climatic and tectonic history of active mountains. The analysis of river profiles commonly relies on the assumption that drainage network configurations are stable. Here we show that this assumption must made cautiously if changes in contributing area are fast relative to knickpoint migration rates. We study the Parachute Creek basin in the Roan Plateau, Colorado, United States. Low spatial variations in climate and erosional efficiency permit us to reveal and quantify drainage-area loss that occurred in one of the subbasins where observed knickpoint locations are farther upstream than predicted by a model that takes present-day drainage areas into account. We developed a Lagrangian model of knickpoint migration which enables us to study the kinematic links between drainage area loss and knickpoint migration and that provides us with constraints on the temporal aspects of area loss. Modelled onset and amount of area loss are consistent with cliff retreat rates along the margin of the Roan Plateau inferred from the incisional history of the upper Colorado River.&lt;/p&gt;

scholarly journals How concave are river channels?

2018 ◽  
Vol 6 (2) ◽  
pp. 505-523 ◽  
Author(s):  
Simon M. Mudd ◽  
Fiona J. Clubb ◽  
Boris Gailleton ◽  
Martin D. Hurst
Keyword(s):  
Numerical Models ◽  
Theoretical Models ◽  
Structural Heterogeneity ◽  
Drainage Area ◽  
Tectonic Activity ◽  
River Channels ◽  
Stream Power ◽  
Channel Incision ◽  
Rock Types ◽  
Channel Steepness

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 ks. 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” (χ) analysis. We present a new χ-based method which directly compares χ 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 χ 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 χ-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.

scholarly journals RADAR-BASED RAINFALL ESTIMATION IN BOYONG RIVER (BO-D5)

2021 ◽  
Vol 3 (1) ◽  
pp. 007-019
Author(s):  
Henggar Risa Destania ◽  
Achmad Syarifudin
Keyword(s):  
Soil Layer ◽  
Reference Value ◽  
Radar Data ◽  
Drainage Area ◽  
Current Status ◽  
Water Index ◽  
X Band ◽  
Short And Long Term ◽  
Sediment Disaster ◽  
Maximum Limit

Sediment-related disasters are terrible disasters that can catastrophically impact facilities. People must keep in mind to make sediment-related disaster information that can be predicted from rainfall and response of drainage area by using snakelike. This research produces important indices on precipitation related to debris. It shows the current status of the stage of the response of drainage area against rainfall by using a couple of short- and long-term indices. It shows the water storage volume in the soil layer with the calculation of soil water index (SWI) by using X-band MP (Multi-Parameter) rainfall radar data that has been installed at the top of Merapi Mountain (Merapi Museum). It was confirmed that from June 2018 – June 2019, with 80.28 mm SWI, maximum values do not exceed the standard reference value of SWI (120 – 160 mm) set from JMA. It means that 80.28 mm of SWI value has not yet become the maximum limit of SWI value for lahar occurrence in the Boyong drainage area (BO-D5). The maximum limit of SWI value can be generated if sediment disaster occurrences are available.

scholarly journals Quantification of Continuous Flood Hazard using Random Forrest Classification and Flood Insurance Claims at Large Spatial Scales: A Pilot Study in Southeast Texas

2020 ◽  
Author(s):  
William Mobley ◽  
Antonia Sebastian ◽  
Russell Blessing ◽  
Wesley E. Highfield ◽  
Laura Stearns ◽  
...  
Keyword(s):  
Pilot Study ◽  
Random Forest ◽  
Spatial Information ◽  
Gulf Coast ◽  
Flood Hazard ◽  
Spatial Scales ◽  
High Sensitivity ◽  
Machine Learning Techniques ◽  
Flood Insurance ◽  
Flood Hazards

Abstract. Pre-disaster planning and mitigation necessitates detailed spatial information about flood hazards and their associated risks. In the U.S., the FEMA Special Flood Hazard Area (SFHA) provides important information about areas subject to flooding during the 1 % riverine or coastal event. The binary nature of flood hazard maps obscures the distribution of property risk inside of the SFHA and the residual risk outside of the SFHA, which can undermine mitigation efforts. Machine-learning techniques provide an alternative approach to estimating flood hazards across large spatial scales at low computational expense. This study presents a pilot study for the Texas Gulf Coast Region using Random Forest Classification to predict flood probability across a 30,523 km2 area. Using a record of National Flood Insurance Program (NFIP) claims dating back to 1976 and high-resolution geospatial data, we generate a continuous flood hazard map for twelve USGS HUC-8 watersheds. Results indicate that the Random Forest model predicts flooding with a high sensitivity (AUC 0.895), especially compared to the existing FEMA regulatory floodplain. Our model identifies 649,000 structures with at least a 1 % annual chance of flooding, roughly three times more than are currently identified by FEMA as flood prone.

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