How does lithological composition vary downstream (2)

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In my last blog post, I showed how TopoToolbox can be used to plot the lithological composition as a function of distance along a river profile. This worked rather nicely with a single river. But how do you visualize these patterns if you have a catchment with multiple streams.

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How does lithological composition vary downstream?

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Matthew Morris recently asked on Twitter whether it is possibly to plot river profiles together with the lithological composition of their upstream area. I found this idea challenging and so I decided to write some code that does it.

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To slide or not to slide: HyLands gives the answer

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This blog post is written by Benjamin Campforts and Charlie Shobe

Landslides change the shape of Earth’s surface in a geologic instant, with devastating consequences for societies and infrastructure in mountainous terrain. The threat of landslides as a natural hazard and their impressive ability to sculpt topography has inspired generations of geomorphologists. Predicting landslide occurrence is challenging due to the episodic nature of landslides. Thanks to many decades of tears and sweat, in challenging field sites, inspecting old faded and crumbled areal photos or, if you are so lucky to live in the present, Google Earth, much progress has been made in the establishment of relatively accurate landslide susceptibility indices and hazard maps.

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Calculating basin-averaged ksn values

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The normalized river steepness (Ksn) is one of the most frequently used topogrpahic metrics in tectonic geomorphology. TopoToolbox has the function ksn that enables calculating this metric for each node in the river network. Often, however, researchers are rather interested in calculating basin average values of ksn rather than a ksn value for each river node. This is more tricky. Hence, here is a quick solution.

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Introduction to @DIVIDEobj

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Fig01_streams_and_divides

This blog post was written by Dirk Scherler

In this blog entry, we demonstrate the funcionalities of the new class DIVIDEobj.

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geoglobe now in MATLAB R2020a

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In a previous post (here) I have shown how TopoToolbox is able to export data to kml-files which can be directly opened in Google Earth (or other digital globes such as ArcGIS Earth). Indeed, kml is a great way to share geographic data. However, if you want to visually explore your data, the step via kml and Google Earth may not be necessary any longer. Since its latest release, MATLAB’s Mapping Toolbox includes geoglobe, a geographic globe that allows navigating on the Earth surface and to add data. To this end, geoglobe will enable numerous applications that enhance the way we can explore data analyzed and generated using TopoToolbox.

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Landscapes Live

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#shareEGU20 is currently setting an example. Virtual conferences are an effective means to bring scientists together and to spur vivid discussions.

To keep this scientific exchange alive during COVID-19, Philippe Steer, Vivi Pedersen, Stefanie Tofelde, Pierre Valla, Charlie Shobe, and me (my role was actually very minor) have initiated Landscape Live, a new remote seminar series focused on sharing exciting geomorphology research throughout the international scientific community.

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shareEGU20

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egu.png

Only two days left before #shareEGU20 opens its digital gates. I surely won’t be able to be online during the whole event, but I’ve my personal schedule of displays which I’ll try to view and discuss online inbetween homeoffice, homeparenting, homeschooling, …

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New paper out: Divide mobility controls knickpoint migration

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In recent years, there has been a quite fierce debate about how landscapes evolve in response to lateral dynamics of river networks. These dynamics include laterally shifting rivers, their expansion or contraction in upstream and downstream direction, and the mobility of catchment divides. In fact, as we seek to gain insight into changes in climate and tectonics from the analysis of river networks, we often make the assumption that theses river networks are static, that their spatial configuration remains stable.

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Calculating Hack’s Law using TopoToolbox

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Hack’s Law describes an empirical relationship between river length and drainage area (Hack 1957). The functional relationship is a power function with the equation L = c A^h where L is the length of the longest stream from the outlet to the divide, A is the drainage area above a particular locality, c is a constant, and h is the scaling exponent (see figure).

hackslaw.png
Measuring stream length and drainage area (Hack 1957).

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